Description:FORM 2
THE PATENTS ACT, 1970
(39 of 1970)
&
THE PATENT RULES, 2003

COMPLETE SPECIFICATION
(See Section 10 and Rule 13)

Title of Invention:
A METHOD AND SYSTEM FOR MANAGING NODE SELECTION IN A WIRELESS NETWORK

APPLICANT:
PROBUS SMART THINGS PRIVATE LIMITED
An Indian entity having address as:
63, III Floor, DSIDC Complex, Okhla Industrial Area - Phase- I New Delhi – 110020, India

The following specification particularly describes the invention and the manner in which it is to be performed.

CROSS-REFERENCE TO RELATED APPLICATIONS AND PRIORITY
[0001] The present application does not claim priority from any other patent application.
TECHNICAL FIELD
[0002] The presently disclosed embodiments are related, in general, to a wireless communication networks. More particularly, the presently disclosed embodiments are related to methods and systems for managing node selection in a distributed wireless network.
BACKGROUND
[0003] This section is intended to introduce the reader to various aspects of art (the relevant technical field or area of knowledge to which the invention pertains), which may be related to various aspects of the present disclosure that are described or claimed below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present disclosure. Accordingly, it should be understood that these statements in this background section are to be read in this light, and not as admissions of prior art. Similarly, a problem mentioned in the background section.
[0004] Wireless mesh networks are widely used in a range of applications, including smart cities, industrial IoT, environmental monitoring, smart grids, and agricultural automation. These networks are typically characterized by their decentralized architecture, where each node communicates directly or indirectly with other nodes, forming a multi-hop communication path without relying on a centralized base station. This structure allows for resilience, scalability, and self-healing capabilities, making mesh networks ideal for large-scale, distributed environments.
[0005] However, traditional wireless mesh networks face several challenges. One significant limitation is the lack of real-time relay node selection based on current network conditions. Many existing systems rely on static routing or pre-configured paths that do not adapt to changes in network topology, link quality, or node availability. This approach can lead to congestion, packet loss, and high latency, especially when the network topology changes due to node mobility, power constraints, or environmental interference.
[0006] Furthermore, many conventional mesh systems depend on centralized control for managing network paths, which introduces a single point of failure and increases the control overhead, reducing overall network resilience and scalability. Centralized systems also struggle to efficiently manage large-scale deployments, where thousands of nodes must coordinate without overwhelming the network with control traffic.
[0007] Another critical challenge is the lack of real-time connectivity metrics in existing relay selection approaches. Traditional systems typically do not consider key metrics such as signal strength, link quality, network congestion, device role, node stability, and historical performance data when selecting relay nodes. This can result in poor path selection, where weak or unreliable nodes are chosen as relays, leading to high packet loss, reduced throughput, and dropped connections.
[0008] Additionally, energy efficiency remains a major concern in IoT and sensor networks. Without intelligent relay selection, nodes may consume excessive power by transmitting through suboptimal paths, significantly reducing the battery life of connected devices. This is particularly problematic in remote monitoring applications where devices may be battery-powered and expected to operate for extended periods without human intervention.
[0009] The scalability of traditional mesh networks is also limited by their reliance on fixed routing tables and static network configurations. As the number of nodes in the network increases, the overhead of maintaining accurate routing tables can become a significant bottleneck, reducing overall network throughput and efficiency.
[0010] Many conventional solutions also lack support for IPv6 multicast, which is critical for efficient metric broadcasting in large-scale mesh deployments. Without multicast support, networks must rely on inefficient flooding techniques or point-to-point broadcasts, which significantly increase latency and network traffic.
[0011] Furthermore, many existing systems lack intelligent relay selections for relay node selection. Instead, they often rely on simplistic, single-parameter metrics such as signal strength or distance, without considering more complex factors like link stability, node reliability, historical performance, or real-time congestion. This can lead to suboptimal relay selection, resulting in network instability and degraded performance.
[0012] In view of the above challenges, there is a need for a more adaptive, decentralized approach to relay node selection in wireless mesh networks, one that can dynamically assess real-time connectivity metrics, intelligently select optimal relay paths, and scale to support large, distributed network deployments.
[0013] Further limitations and disadvantages of conventional and traditional approaches will become apparent to one of skill in the art, through comparison of described systems with some aspects of the present disclosure, as set forth in the remainder of the present application and with reference to the drawings.
SUMMARY
[0014] This summary is provided to introduce concepts related to a system for managing relay node selection in a wireless network and a method thereof and the concepts are further described below in the detailed description. This summary is not intended to identify essential features of the claimed subject matter nor is it intended for use in determining or limiting the scope of the claimed subject matter.
[0015] According to embodiments illustrated herein, a method for managing relay node selection by a first node in a wireless network is disclosed. Further, the method may be implemented by an electronic device including a processor and a memory communicatively coupled to the processor, with the memory configured to store processor-executable programmed instructions. Further, the method may comprise a step of identifying connectivity metrics of the first node. Further, the method may comprise a step of determining a connectivity status of the first node. Further, the method may comprise a step of transmitting a request to a plurality of nodes in the wireless network, based on the connectivity status, for seeking connectivity metrics of the plurality of nodes. Further, the method may comprise a step of receiving the connectivity metrics of each of the plurality of nodes. Further, the method may comprise a step of identifying a relay node from the plurality of nodes based on the connectivity metrics of each of the plurality of nodes. Further, the method may comprise a step of transmitting a signal to the relay node for transmission to a server.
[0016] According to embodiments illustrated herein, a system managing relay node selection by the first node in the wireless network is disclosed. Further, the system may comprise the processor and the memory communicatively coupled with the processor. Further, the memory may be configured to store programmed instructions that cause the processor to perform the following operations. Further, the processor may be configured to identify the connectivity metrics of the first node. Further, the processor may be configured to determine the connectivity status of the first node. Further, the processor may be configured to transmit the request to the plurality of nodes in the wireless network, based on the connectivity status, for seeking connectivity metrics of the plurality of nodes. Further, the processor may be configured to receive the connectivity metrics of each of the plurality of nodes. Further, the processor may be configured to identify the relay node from the plurality of nodes based on the connectivity metrics of each of the plurality of nodes. Further, the processor may be configured to transmit the signal to the relay node for transmission to the server.
[0017] According to embodiments illustrated herein, a non-transitory computer-readable storage medium having stored thereon, a set of computer-executable instructions causing a computer comprising one or more processors to perform steps. Further, a step may comprise identifying the connectivity metrics of the first node. Further, a step may comprise determining the connectivity status of the first node. Further, a step may comprise transmitting the request to the plurality of nodes in the wireless network, based on the connectivity status, for seeking connectivity metrics of the plurality of nodes. Further, a step may comprise receiving the connectivity metrics of each of the plurality of nodes. Further, a step may comprise identifying the relay node from the plurality of nodes based on the connectivity metrics of each of the plurality of nodes. Further, a step may comprise transmitting the signal to the relay node for transmission to the server.
[0018] The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description.
BRIEF DESCRIPTION OF DRAWINGS
[0019] The accompanying drawings illustrate the various embodiments of systems, methods, and other aspects of the disclosure. Any person with ordinary skills in art will appreciate that the illustrated element boundaries (e.g., boxes, groups of boxes, or other shapes) in the figures represent one example of the boundaries. In some examples, one element may be designed as multiple elements, or multiple elements may be designed as one element. In some examples, an element shown as an internal component of one element may be implemented as an external component in another, and vice versa. Further, the elements may not be drawn to scale.
[0020] Various embodiments will hereinafter be described in accordance with the appended drawings, which are provided to illustrate and not to limit the scope in any manner, wherein similar designations denote similar elements, and in which:
[0021] FIG. 1 is a block diagram that illustrates a system (100) for managing relay node selection by a first node in a wireless network, in accordance with an embodiment of present subject matter.
[0022] FIG. 2 is a block diagram that illustrates various components of an application server (104) configured for performing steps of managing relay node selection by the first node in the wireless network, in accordance with an embodiment of the present subject matter.
[0023] FIG. 3 is a flowchart that illustrates a method (300) for managing relay node selection by the first node in the wireless network, in accordance with an embodiment of the present subject matter.
[0024] FIG. 4 illustrates a block diagram (400) of an exemplary computer system for implementing embodiments consistent with the present subject matter.
DETAILED DESCRIPTION
[0025] The present disclosure may be best understood with reference to the detailed figures and description set forth herein. Various embodiments are discussed below with reference to the figures. However, those skilled in the art will readily appreciate that the detailed descriptions given herein with respect to the figures are simply for explanatory purposes as the methods and systems may extend beyond the described embodiments. For example, the teachings presented, and the needs of a particular application may yield multiple alternative and suitable approaches to implement the functionality of any detail described herein. Therefore, any approach may extend beyond the particular implementation choices in the following embodiments described and shown.
[0026] References to “one embodiment,” “at least one embodiment,” “an embodiment,” “one example,” “an example,” “for example,” and so on indicate that the embodiment(s) or example(s) may include a particular feature, structure, characteristic, property, element, or limitation but that not every embodiment or example necessarily includes that particular feature, structure, characteristic, property, element, or limitation. Further, repeated use of the phrase “in an embodiment” does not necessarily refer to the same embodiment. The terms “comprise”, “comprising”, “include(s)”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, system or method that comprises a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or system or method. In other words, one or more elements in a system or apparatus preceded by “comprises… a” does not, without more constraints, preclude the existence of other elements or additional elements in the system or apparatus. Further, the terms “portable device”, “measuring device”, or any other variations thereof, are intended to cover a similar device.
[0027] An objective of the present disclosure is to provide a method and system for managing relay node selection by a first node in a wireless network.

[0028] An objective of the present disclosure is to provide the method and system for managing relay node selection by the first node in the wireless network, which enables efficient, secure, and dynamic selection of relay nodes based on real-time connectivity metrics, thereby improving overall network performance and data transmission reliability.
[0029] Another objective of the present disclosure is for selecting relay nodes based on comprehensive connectivity metrics, including signal strength, link quality, latency, node stability, historical performance data, and network congestion levels, to ensure optimal path selection and reduced data transmission delays.
[0030] Yet another objective of the present disclosure is to enable multicast-based communication for both transmitting requests and receiving connectivity metrics over IPv6, enhancing scalability and reducing overhead in dense wireless networks.
[0031] Yet another objective of the present disclosure is to facilitate secure, authenticated communication between nodes, ensuring that only trusted nodes participate in the relay selection process, thereby minimizing the risk of unauthorized data interception.
[0032] Yet another objective of the present disclosure is to provide a scoring algorithm for evaluating potential relay nodes based on current connectivity metrics and historical relay performance, ensuring consistent and high-quality data forwarding in dynamic network environments.
[0033] Yet another objective of the present disclosure is to enable adaptive relay node selection based on real-time network conditions, including link quality, node stability, and historical relay performance, allowing the system to dynamically adjust to changing network topologies and traffic patterns.
[0034] FIG. 1 is a block diagram that illustrates a system (100) for managing relay node selection by a first node in a wireless network, in accordance with an embodiment of present subject matter. The system (100) typically includes a database server (102), an application server (104), a communication network (106), and one or more portable devices (108). The database server (102), the application server (104), and the one or more portable devices (108) are typically communicatively coupled with each other via the communication network (106). In an embodiment, the communication network (106) may comprise a wireless mesh network, a peer-to-peer network, or a combination of wireless protocols suitable for multi-hop communication. In another embodiment, the application server (104) may communicate with the database server (102), and the one or more portable devices (108) using one or more protocols such as, but not limited to, Hypertext Transfer Protocol (HTTP), Transmission Control Protocol/Internet Protocol (TCP/IP)/User Datagram Protocol (UDP), Wireless Application Protocol (WAP), Bluetooth Low Energy (BLE), and the like, to communicate with one another.
[0035] In one embodiment, the database server (102) may refer to a computing device configured to store and manage connectivity metrics, identification information, and historical relay performance data associated with the plurality of portable devices (108). The database may store this data in a structured format that supports real-time retrieval and update operations during relay node selection.
[0036] In an embodiment, the database server (102) may include a special-purpose operating system and database management software specifically configured to perform one or more database operations on the stored connectivity and performance data. Examples of database operations may include, but are not limited to, Select, Insert, Update, and Delete. In an embodiment, the database server (102) may include specialized hardware components optimized for concurrent data access and high-throughput operations to support real-time relay selection processes. In an embodiment, the database server (102) may be realized through various technologies such as, but not limited to, Microsoft® SQL Server, Oracle®, IBM DB2®, Microsoft Access®, PostgreSQL®, MySQL®, SQLite®, distributed databases (e.g., Apache Cassandra, MongoDB), or any equivalent platform capable of supporting structured or semi-structured data models. In an embodiment, the database server (102) may be configured to utilize the application server (104) for managing relay node selection in the wireless network. Additionally, the database server (102) may interface with the application server (104) to enable processing logic, such as dynamic grouping of nodes based on updated metrics, device roles, and network topology changes, to support optimal relay node selection under real-time conditions.
[0037] A person with ordinary skills in art will understand that the scope of the disclosure is not limited to the database server (102) as a separate entity. In an embodiment, the functionalities of the database server (102) can be integrated into the application server (104) or into the one or more portable devices (108).
[0038] In an embodiment, the application server (104) may refer to a computing device or a software framework hosting the application or a software service. In an embodiment, the application server (104) may be implemented to execute procedures such as, but not limited to, programs, routines, or scripts stored in one or more memories for supporting the hosted application or the software service. In an embodiment, the hosted application or the software service may be configured to perform one or more predetermined operations. In an embodiment, the application server (104) may refer to a computing device or a software framework configured to facilitate managing relay node selection by a first node in a wireless network. The application server (104) may be implemented to execute instructions, routines, or programs stored in one or more memories to perform functions such as coordinating communication among the first node and a plurality of nodes, processing connectivity metrics, and identifying a relay node. The application server (104) may be realized through various types of application servers such as, but are not limited to, a Java application server, a .NET framework application server, a Base4 application server, a PHP framework application server, or any other application server framework.
[0039] In an embodiment, the application server (104) may be configured to assist the first node in performing one or more steps, such as identifying connectivity metrics of the first node, determining a connectivity status of the first node, and coordinating the transmission of a request to a plurality of nodes in the wireless network based on the connectivity status. The application server (104) may further be configured to receive the connectivity metrics from each of the plurality of nodes, and to assist in identifying a relay node from among the plurality of nodes based on the received connectivity metrics. In some embodiments, the application server (104) may additionally be involved in facilitating the transmission of a signal from the first node to the relay node for subsequent transmission to a server. The application server (104) may maintain or access records through the database server (102) to support the decision-making process involved in the relay node selection.
[0040] In an embodiment, the communication network (106) may correspond to a communication medium through which the application server (104), the database server (102), and the one or more portable devices (108), including the first node and the plurality of nodes in the wireless network may communicate with each other. Such a communication may be performed in accordance with various wired and wireless communication protocols. Examples of such wired and wireless communication protocols include, but are not limited to, Transmission Control Protocol and Internet Protocol (TCP/IP), User Datagram Protocol (UDP), Hypertext Transfer Protocol (HTTP), Wireless Application Protocol (WAP), File Transfer Protocol (FTP), ZigBee, EDGE, infrared IR), IEEE 802.11, 802.16, 2G, 3G, 4G, 5G, 6G, 7G cellular communication protocols, and/or Bluetooth (BT) communication protocols. The communication network (106) may either be a dedicated network or a shared network. Further, the communication network (106) may include a variety of network devices, including routers, bridges, servers, computing devices, storage devices, and the like. The communication network (106) may include, but is not limited to, the Internet, intranet, a cloud network, a Wireless Fidelity (Wi-Fi) network, a Wireless Local Area Network (WLAN), a Local Area Network (LAN), a cable network, the wireless network, a telephone network (e.g., Analog, Digital, POTS, PSTN, ISDN, xDSL), a telephone line (POTS), a Metropolitan Area Network (MAN), an electronic positioning network, an X.25 network, an optical network (e.g., PON), a satellite network (e.g., VSAT), a packet-switched network, a circuit-switched network, a public network, a private network, and/or other wired or wireless communications network configured to carry data.
[0041] In an embodiment, the one or more portable devices (108) may refer to one or more nodes in the wireless network. In one embodiment, a typical node consists of an embedded microcontroller with a wireless radio supporting IPv6 mesh, a 4G modem connected via UART, and FreeRTOS-based firmware. In one embodiment, the one or more portable devices (108) may refer to one of a utility meter, electricity meter, gas meter, water meter, hybrid meters, digital meter, prepaid meter, postpaid meter, residential meter, commercial meter, industrial meter, routers, modems, sensors, Internet-of-Things (IoT) devices. The one or more portable devices (108) may comprise of one or more processors and one or more memory. The one or more memories may include computer readable code that may be executable by one or more processors to perform steps for managing relay node selection by a first node in a wireless network. In an embodiment, the one or more portable devices (108) may present a web user interface for managing relay node selection by a first node in a wireless network using the application server (104). Example web user interfaces presented on the one or more portable devices (108) to display information about the data. Examples of the one or more portable devices (108) may include, but are not limited to, a personal computer, a laptop, a computer desktop, a personal digital assistant (PDA), a mobile device, a tablet, or any other computing device.
[0042] In an embodiment, the one or more portable devices (108) may refer to computing devices configured to operate as nodes in the wireless network, including the first node and the plurality of nodes. Each portable device (108) may be equipped with communication interfaces, sensors, processors, memory, and power sources to support wireless communication, data processing, and relay functionalities. The portable devices (108) may be capable of identifying connectivity metrics such as signal strength, signal quality, and link quality parameters, and may be configured to evaluate their own connectivity status within the wireless network. In certain scenarios, a portable device (108) may function as the first node, responsible for initiating a request for connectivity metrics from other nodes. The portable devices (108) may include, but are not limited to, handheld diagnostic tools, IoT-enabled sensors, mobile terminals, embedded controllers, field equipment with wireless modules, or any other electronic device capable of participating in a wireless mesh or ad-hoc communication network. In an embodiment, the portable devices (108) may support IPv6-based communication, multicast messaging, and various wireless protocols, thereby enabling dynamic and distributed relay node selection without centralized coordination.
[0043] The system (100) can be implemented using hardware, software, or a combination of both, which includes using where suitable, one or more computer programs, mobile applications, or “apps” by deploying either on-premises over the corresponding computing terminals or virtually over cloud infrastructure. The system (100) may include various micro-services or groups of independent computer programs which can act independently in collaboration with other micro-services. The system (100) may also interact with a third-party or external computer system. Internally, the system (100) may be the central processor of all scheduled events for managing relay node selection by a first node in a wireless network of the system.
[0044] FIG. 2 illustrates a block diagram illustrating various components of the application server (104) configured for performing stepwise for managing relay node selection by the first node in the wireless network, in accordance with an embodiment of the present subject matter. Further, the FIG. 2 is explained in conjunction with the FIG. 1. Here the application server (104) preferably includes a processor (202), a memory (204), a transceiver (206), an Input/Output (208), a user interface (UI) unit (210), an identification unit (212), a connectivity management unit (214), a node selection unit (216) and a signal transmission unit (218).The processor (202) is further preferably communicatively coupled to the memory (204), the transceiver (206), the Input/Output unit (208), the UI unit (210), the identification unit (212), the connectivity management unit (214), the node selection unit (216) and the signal transmission unit (218), while the transceiver (206) is preferably communicatively coupled to the communication network (106).
[0045] The processor (202) comprises suitable logic, circuitry, interfaces, and/or code that may be configured to execute a set of instructions stored in the memory (204), and may be implemented based on several processor technologies known in the art. The processor (202) works in coordination with the transceiver (206), the Input/Output unit (208), the UI unit (210), the identification unit (212), the connectivity management unit (214), the node selection unit (216). Examples of the processor (202) include, but not limited to, standard microprocessor, microcontroller, central processing unit (CPU), an X86-based processor, a Reduced Instruction Set Computing (RISC) processor, an Application- Specific Integrated Circuit (ASIC) processor, and a Complex Instruction Set Computing (CISC) processor, distributed or cloud processing unit, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions and/or other processing logic that accommodates the requirements of the present invention.
[0046] The memory (204) comprises suitable logic, circuitry, interfaces, and/or code that may be configured to store the set of instructions, which are executed by the processor (202). Preferably, the memory (204) is configured to store one or more programs, routines, or scripts that are executed in coordination with the processor (202). Additionally, the memory (204) may include any computer-readable medium or computer program product known in the art including, for example, volatile memory, such as static random-access memory (SRAM) and dynamic random-access memory (DRAM), and/or non-volatile memory, such as read only memory (ROM), erasable programmable ROM, a Hard Disk Drive (HDD), flash memories, Secure Digital (SD) card, Solid State Disks (SSD), optical disks, magnetic tapes, memory cards, virtual memory and distributed cloud storage. The memory (204) may be removable, non-removable, or a combination thereof. Further, the memory (204) may include routines, programs, objects, components, data structures, etc., which perform particular tasks or implement particular abstract data types. The memory (204) may include programs or coded instructions that supplement applications and functions of the system (100). In one embodiment, the memory (204), amongst other things, serves as a repository for storing data processed, received, and generated by one or more of the programs or the coded instructions. In yet another embodiment, the memory (204) may be managed under a federated structure that enables adaptability and responsiveness of the application server (104).
[0047] The transceiver (206) comprises suitable logic, circuitry, interfaces, and/or code that may be configured to receive, process or transmit information, data or signals, which are stored by the memory (204) and executed by the processor (202). The transceiver (206) is preferably configured to receive, process or transmit, one or more programs, routines, or scripts that are executed in coordination with the processor (202). The transceiver (206) is preferably communicatively coupled to the communication network (106) of the system (100) for communicating all the information, data, signal, programs, routines or scripts through the network. The transceiver (206) may be configured to receive a request for managing relay node selection by a first node in a wireless network.
[0048] The transceiver (206) may implement one or more known technologies to support wired or wireless communication with the communication network (106). In an embodiment, the transceiver (206) may include, but is not limited to, an antenna, a radio frequency (RF) transceiver, one or more amplifiers, a tuner, one or more oscillators, a digital signal processor, a Universal Serial Bus (USB) device, a coder-decoder (CODEC) chipset, a subscriber identity module (SIM) card, and/or a local buffer. Also, the transceiver (206) may communicate via wireless communication with networks, such as the Internet, an Intranet and/or a wireless network, such as a cellular telephone network, a wireless local area network (LAN) and/or a metropolitan area network (MAN). Accordingly, the wireless communication may use any of a plurality of communication standards, protocols and technologies, such as: Global System for Mobile Communications (GSM), Enhanced Data GSM Environment (EDGE), wideband code division multiple access (W-CDMA), code division multiple access (CDMA), time division multiple access (TDMA), Bluetooth, Wireless Fidelity (Wi-Fi) (e.g., IEEE 802.11a, IEEE 802.11b, IEEE 802.11g and/or IEEE 802.11n), voice over Internet Protocol (VoIP), Wi-MAX, a protocol for email, instant messaging, and/or Short Message Service (SMS).
[0049] The input/output (I/O) unit (208) comprises suitable logic, circuitry, interfaces, and/or code that may be configured to receive or present information. The input/output unit (208) comprises various input and output devices that are configured to communicate with the processor (202). Examples of the input devices include, but are not limited to, a keyboard, a mouse, a joystick, a touch screen, a microphone, a camera, and/or a docking station. Examples of the output devices include, but are not limited to, a display screen and/or a speaker. The I/O unit (208) may include a variety of software and hardware interfaces, for example, a web interface, a graphical user interface, and the like. The I/O unit (208) may allow the system (100) to interact with the user directly or through the portable devices (108). Further, the I/O unit (208) may enable the system (100) to communicate with other computing devices, such as web servers and external data servers (not shown). The I/O unit (208) can facilitate multiple communications within a wide variety of networks and protocol types, including wired networks, for example, LAN, cable, etc., and wireless networks, such as WLAN, cellular, or satellite. The I/O unit (208) may include one or more ports for connecting a number of devices to one another or to another server. In one embodiment, the I/O unit (208) allows the application server (104) to be logically coupled to other portable devices (108), some of which may be built in. Illustrative components include tablets, mobile phones, desktop computers, wireless devices, etc.
[0050] In one embodiment, the input/output (I/O) unit (208) of the application server (104) may be configured to manage transmission and reception of data between the first node and the plurality of nodes in the wireless network. The I/O unit (208) may be configured to transmit a request to the plurality of nodes based on the connectivity status of the first node, in order to seek connectivity metrics of the plurality of nodes. Additionally, the I/O unit (208) may be configured to receive the connectivity metrics from the plurality of nodes. The connectivity metrics may include parameters such as signal quality, signal strength, or link reliability. Based on the received metrics, the I/O unit (208), in conjunction with a processing unit (202), may enable identification of a suitable relay node among the plurality of nodes. Further, the I/O unit (208) may transmit a signal to the identified relay node for forwarding to a server, thereby facilitating reliable communication from the first node despite limited direct connectivity.
[0051] Further, the UI unit (210) of the application server (104), is disclosed. In an embodiment, the UI unit (210) of the application server (104) may include, but not limited to an application interface, a web interface, a graphical user interface (GUI) and a touch user interface. The UI unit (210) may be configured to enable a user to interact with the system (100) via one or more portable devices (108). For example, the UI unit (210) may facilitate the display of connectivity metrics of the first node, relay node selection status, and transmission logs related to communication with the plurality of nodes in the wireless network. The UI unit (210) may also support configurations or visual monitoring of signal strength, connectivity status, and other network health indicators as processed by the application server (104). In some embodiments, the user may utilize the UI unit (210) to initiate a relay node selection process, view the current or historical relay performance data, or override default relay selections based on policy or application needs.
[0052] In another embodiment, the identification unit (212) of the application server (104) is disclosed. Further, the identification unit (212) may be configured to identify connectivity metrics of the first node in a wireless network. Further, the connectivity metrics may comprise at least one of a node identification information, connectivity channel, signal strength, signal quality, link quality, latency, network load, time of last metric update, historical relay performance data, device role, node state, node stability status, connectivity availability, network congestion, or a combination thereof. In one embodiment, the node identification information may include at least one of a device name, a device identifier, a device type, or a network address. In one embodiment, the signal strength may correspond to at least one of a received signal strength indication (RSSI), a reference signal received power (RSRP), a reference signal received quality (RSRQ), a signal-to-noise ratio (SNR), or a combination thereof. In one embodiment, the link quality may include at least one of expected transmission count (ETX), packet error rate (PER), average round-trip time (RTT), or a combination thereof. In one embodiment, the connectivity availability may be based on at least one of connection uptime, handoff stability, or network congestion levels. Furthermore, the historical relay performance data may include at least one of average data transmission rate, relay selection frequency, average link uptime, or previous relay node failures. In one embodiment, the identification unit (212) may use this information to evaluate the current communication condition of the first node before initiating relay selection operations.
[0053] In another embodiment, the identification unit (212) may be configured to determine a connectivity status of the first node. In one embodiment, the identification unit (212) may determine the connectivity status of the first node based on the identified connectivity metrics. The connectivity status may indicate whether the first node’s communication capability meets a predefined threshold or requires assistance. The determination may be based on comparing one or more connectivity metrics against threshold values or using heuristic or machine learning models to classify connectivity status. In an exemplary embodiment, the determination may be based on comparing the connectivity metrics with at least one predetermined threshold parameter selected from signal strength threshold, latency threshold, or network congestion threshold. In one embodiment, the signal strength threshold may be set to a value below which the communication link quality is considered insufficient for direct transmission. In one embodiment, the latency threshold may correspond to a maximum allowable delay for communication to meet quality-of-service requirements. In one embodiment, the network congestion threshold may reflect the acceptable limit of network traffic load beyond which performance degradation is anticipated. In another embodiment, the identification unit (212) may use one or more of these thresholds individually or in combination to classify the connectivity status as acceptable or degraded, thereby triggering subsequent relay node discovery or direct communication strategies. In another embodiment, the thresholds may be configurable based on network policies, application requirements, or environmental conditions and may be dynamically adjusted based on historical data or machine learning predictions.
[0054] In one embodiment, the identification unit (212) may broadcast the connectivity metrics of the first node to the plurality of nodes in the wireless network. In one embodiment, the broadcasting may be performed by transmitting a structured diagnostic message over a multicast IPv6 address, enabling efficient dissemination of the information to multiple nodes simultaneously. In one embodiment, the structured diagnostic message may encapsulate relevant connectivity parameters such as signal strength, latency, link quality, and network load in a predefined data format or protocol. In one embodiment, the use of multicast IPv6 addressing may facilitate scalability and reduce network overhead by avoiding redundant unicast transmissions. Furthermore, the identification unit (212) may periodically or event-triggered broadcast this information to ensure that neighbouring nodes have up-to-date data necessary for relay selection and network optimization.

[0055] The identification unit (212) may transmit a request to a plurality of nodes in the wireless network, based on the determined connectivity status of the first node. The request may solicit connectivity metrics from the plurality of nodes for evaluating their suitability as relay nodes. The transmission of the request may be conditional on the connectivity status, such that the request is sent only when the first node’s connectivity status indicates suboptimal communication conditions.
[0056] In one embodiment, the transmission of the request may be conditional, occurring only when the connectivity status indicates suboptimal communication conditions, such as a significant degradation in signal quality or a complete cellular outage. To minimize network congestion and overhead, each node in the network may periodically monitor its own cellular connectivity and may broadcast signal status updates selectively. For example, a node may broadcast its connectivity metrics only upon detecting a significant change in signal quality or upon losing cellular connectivity and requiring relay assistance. In one embodiment, this selective broadcasting approach reduces unnecessary signalling traffic in the mesh network. Further, the identification unit (212) may employ a request-response mechanism for relay selection. In another embodiment, when the first node detects poor cellular connectivity, it may multicast a request message to neighbouring nodes within the mesh network. This request may include a unique identifier associated with the first node to correlate responses accurately. In another embodiment, neighbouring nodes receiving the request may respond with their respective connectivity metrics, such as signal strength and connection status. Upon receiving these responses, the identification unit (212) may evaluate the metrics to select an optimal relay node that can facilitate reliable data transmission for the first node. In another embodiment, this targeted request-response strategy ensures that relay node selection is performed efficiently and only, when necessary, thereby preserving network resources and improving overall communication robustness.
[0057] In another embodiment, the connectivity management unit (214) of the application server (104) is disclosed. Further, the connectivity management unit (214) may be configured to receive the connectivity metrics of each of the plurality of nodes in the wireless network. In another embodiment, the connectivity metrics may be received in response to the request broadcasted by the identification unit (212), and may include signal strength indicators, latency measurements, link quality estimates, or other node status parameters. In another embodiment, the connectivity management unit (214) may organize this information based on unique node identifiers and maintain temporal consistency by discarding outdated metrics or applying timestamps for synchronization.
[0058] In one embodiment, the wireless network may correspond to a wireless mesh network, IPv6 enabled wireless mesh network, an ad-hoc wireless network, a multi-hop wireless network, a self-organizing network (SON), a decentralized wireless network, a peer-to-peer wireless network, Open Thread, cellular network, NB-IoT, Ethernet, Wi-FI or a combination thereof. In another embodiment, the plurality of nodes may be connected to the first node in the wireless network. In another embodiment, the first node may be different from the plurality of nodes in the wireless network.
[0059] In one embodiment, the connectivity management unit (214) may be configured to authenticate the plurality of nodes prior to receiving their connectivity metrics, thereby ensuring secure and trusted relay node selection. The authentication process may involve verifying digital signatures, certificates, or pre-shared credentials of peer nodes before accepting and processing their reported metrics.
[0060] In one embodiment, the connectivity management unit (214) may maintain a neighbour table that stores the latest received connectivity metrics from authenticated peer nodes. This table may be updated dynamically as new metric reports are received, and may be used to support relay node selection decisions or perform health checks on mesh network participants. Additionally, the connectivity management unit (214) may store both the first node’s and each peer node’s connectivity metrics in a local or cloud-based database for auditability, historical trend analysis, or predictive decision-making.
[0061] In one embodiment, the node selection unit (216) of the application server (104) is disclosed. The node selection unit (216) may be configured to identify a relay node from among the plurality of nodes based on the received connectivity metrics of the plurality of nodes. The selection may be performed by evaluating multiple connectivity parameters, such as signal strength (e.g., RSSI, RSRP), latency, link quality (e.g., ETX, PER), and historical performance indicators, to determine the most suitable node for relaying the signal. The selection logic may include ranking nodes according to weighted scoring models or machine-learned policies trained to maximize transmission success, energy efficiency, or route stability. The node selection unit (216) may also consider context-aware factors such as device role, current node load, or proximity to the destination server. In some embodiments, redundant relay candidates may be pre-identified as fallback options to ensure uninterrupted communication in case of primary node failure.
[0062] In another embodiment, the node selection unit (216) may be configured to identify the relay node from the plurality of nodes based on a dynamically computed relay score. The node selection unit (216) may gather connectivity metrics for each node, comprising information related to both Mesh and Cellular diagnostics. These connectivity metrics may include parameters such as cellular signal quality, mesh latency, network load, link quality, node stability, and priority of the data to be transmitted. The node selection unit (216) may assign dynamic weights to each parameter in response to current network conditions. For example, if the cellular connectivity across nodes is highly variable, the weights assigned to mesh latency and link quality may be increased to prioritize relay stability.
[0063] In one embodiment, a scoring mechanism may apply the following adaptive weights to calculate the relay score for each node mentioned in the table below:
Parameter Adaptive Weight Range
Cellular Signal Quality (RSRP, RSRQ, SNR) 30% – 50%
Mesh Latency (Hop Count or RTT) 10% – 25%
Network Load (4G Throughput + Queue Size) 10% – 20%
Link Quality (ETX, Link Margin) 10% – 20%
Node Uptime and Stability 10% – 15%
Data Priority Modifier +X% (Context-based)
[0064] The weights may be normalized and summed to calculate a raw relay score for each candidate node.
[0065] In one embodiment, the node selection unit (216) may calculate the relay score for each node by applying the dynamically weighted parameters through a scoring technique such as a linear weighted sum or a rule-based evaluation model. In another embodiment, the relay score may then be adjusted by applying penalties or bonuses to reflect real-time network conditions or node history. In an exemplary embodiment, for instance, a node may receive a penalty if it recently experienced a relay failure or is currently overloaded. Conversely, a node may receive a bonus if it has a history of successful relays or has low queue occupancy. In an exemplary embodiment, this scoring mechanism may allow the system to reflect both present and past performance of potential relay candidates, leading to more reliable relay selection. In an exemplary embodiment, for instance, a node with consistent successful transmission over the past N cycles may receive a +10% boost. In an exemplary embodiment, this dynamic adjustment of scores may ensure a context-aware and resilient relay node selection.
[0066] In one embodiment, the node selection unit (216) may perform secondary evaluation criteria in case of relay score ties between multiple nodes. Such criteria may include selecting the node with the lowest recent transmission latency, the most stable uptime, or the lowest recent packet drop rate. Additionally, the node selection unit (216) may implement load balancing strategies to prevent overloading any single node. For example, in scenarios where multiple candidate nodes have equivalent scores or strong connectivity, the node selection unit (216) may use a round-robin approach to cycle relay selection or may choose the node advertising the lowest current transmission load. Each node may periodically broadcast its current transmission statistics (e.g., mesh queue length, cellular throughput) to aid in this load balancing process.
[0067] In one embodiment, the node selection unit (216) may finalize the selection of the relay node based on the highest adjusted relay score, considering all primary and secondary selection parameters. This ensures that the most optimal node based on a blend of signal quality, responsiveness, reliability, and load distribution is chosen to forward the signal toward the intended server.
[0068] In another embodiment, identifying the relay node from the plurality of nodes may comprise selecting the node with the highest adjusted relay score based on primary and secondary selection criteria. The primary criterion may prioritize nodes with strongest cellular signal strength, obtained from parameters such as RSRP or RSRQ. In the event of a tie in relay scores, the system may apply secondary criteria including lowest mesh latency based on hop count or round-trip time (RTT), lowest current network load, determined from ongoing transmission activity, and relay reliability score derived from historical relay performance data. Each node may periodically broadcast its updated load and status, enabling dynamic, context-aware relay selection.
[0069] In one embodiment, identifying the connectivity metrics of the first node may be performed periodically within a predefined time interval or initiated on-demand based on system events. For example, the identification unit (212) may trigger the metric update when the node boots up or re-joins the mesh, or when a change in link status or signal strength is detected or upon receiving a metric request from neighbouring nodes or the application server. This flexible approach may allow the system to maintain current awareness of node conditions without unnecessary network overhead.
[0070] In one embodiment, each node in the wireless network may correspond to one of a wide range of devices including, but not limited to: utility meters (electricity meters, water meters, gas meters), digital meters (prepaid/postpaid), hybrid smart meters, Internet-of-Things (IoT) nodes, routers, modems, embedded wireless sensors, or combinations thereof. In one implementation, a typical node may include an embedded microcontroller with a wireless radio supporting IPv6 mesh communication (e.g., OpenThread), a 4G modem interfaced over UART, Lightweight real-time operating system (e.g., FreeRTOS). Such architecture may support low-power operation, reliable mesh communication, and real-time diagnostic processing required for optimal relay selection.
[0071] In one embodiment, the signal transmission unit (218) of the application server (104) is disclosed. The signal transmission unit (218) may be configured to transmit a signal to the identified relay node for onward transmission to a target server. The signal may contain diagnostic data, application payloads, or control instructions, and may be transmitted using a secure transport mechanism such as UDP over IPv6 with optional DTLS encryption. In some embodiments, the signal may be packetized and include IPv6 extension headers to support routing, fragmentation, or quality-of-service features. The signal transmission unit (218) may also monitor the status of the relay transmission (e.g., via acknowledgments or health pings) and may trigger re-selection of a relay node in case of delivery failure. In one embodiment, the signal transmission unit (218) may work in conjunction with the connectivity management unit (214) to log the transaction and update node performance history for future relay decisions.
[0072] In one embodiment, transmitting the request to the plurality of nodes, receiving the connectivity metrics from the plurality of nodes, and transmitting the signal to the relay node, may be performed using the User Datagram Protocol (UDP) over IPv6 within the wireless network. In another embodiment, each transmitted packet may include an extension header that supports advanced routing functionalities or fragmented delivery, allowing large data payloads to be efficiently segmented and reassembled by receiving nodes. In another embodiment, nodes within the network may reassemble fragmented packets and manage data forwarding to ensure reliable and orderly communication. Utilizing UDP over IPv6 may enable low-latency, connectionless transmission suitable for real-time relay node selection and signal forwarding while maintaining scalability and robustness in the wireless mesh environment.
[0073] In one embodiment, the signal transmission unit (218) may be configured to implement a fail-safe mechanism to ensure reliable data delivery through the selected relay node. In another embodiment, the fail-safe mechanism may include timeout and retry logic, in which if no acknowledgment is received from the selected relay within a predefined time, the first node may reattempt transmission with another candidate node using exponential backoff to prevent congestion. In another embodiment, the fail-safe mechanism may include redundant relay transmission, in which the system may send the data to both the top-ranked and second-ranked relay nodes for redundancy. In another embodiment, the fail-safe mechanism may include local data queuing in which if all candidate nodes are unavailable or unresponsive, the first node may locally queue the data and retry periodically, discarding it only upon exceeding retry limits or running out of storage space. In another embodiment, the fail-safe mechanism may include health check broadcasting, in which if nodes may periodically exchange health status (e.g., connectivity and uptime metrics) to keep the neighbour tables updated for future relay selections.
[0074] In one embodiment, the signal transmission unit (218) may further be configured to dynamically respond to mobility and changing signal conditions during data transmission. In another embodiment, when nodes are mobile (e.g., mounted on vehicles), the system may monitor the signal quality of the current relay node in real-time. In another embodiment, if the relay node’s signal quality degrades during transmission, feedback may be sent to the originating node to pause transmission or switch to a more optimal node from the previously evaluated list. In another embodiment, this adaptive mechanism ensures robust delivery even in mobile environments with rapidly varying connectivity.
[0075] A person skilled in the art will understand that the scope of the disclosure should not be limited to a single domain and using the aforementioned techniques. Further, the examples provided in supra are for illustrative purposes and should not be construed to limit the scope of the disclosure.
[0076] Referring to FIG. 3, a flowchart that illustrates a method (300) for managing relay node selection by the first node in the wireless network, in accordance with at least one embodiment of the present subject matter. The method (300) may be implemented by the application server (104) including the processor (202) and the memory (204) communicatively coupled to the processor (202) and the memory (204) is configured to store processor-executable programmed instructions, caused the processor (202) to perform the following steps.
[0077] At step (302), the processor (202) may be configured for identifying a connectivity metrics of the first node.
[0078] At step (304), the processor (202) may determine a connectivity status of the first node.
[0079] At step (306), based on the determined connectivity status, the processor (202) transmits a request to a plurality of nodes in the wireless network, for seeking connectivity metrics of the plurality of nodes.
[0080] At step (308), the processor (202), may receive the connectivity metrics of each of the plurality of nodes.
[0081] At step (310), the processor (202), may identify a relay node from the plurality of nodes based on the received connectivity metric of each of the plurality of nodes.
[0082] At step (312), the processor (202), may transmit a signal to the selected relay node for forwarding to a remote server.
[0083] Let us delve into a detailed working example of the present disclosure.
[0084] Example 01: A smart utility meter installed in a residential area functions as a first node within a decentralized wireless mesh network. The meter periodically assesses its own connectivity parameters, including signal strength, link stability, and data queue status, thereby identifying its own connectivity metrics. Upon determining that its current connection to the central utility server via a direct link (e.g., cellular or wired) is weak or unavailable, the meter initiates a relay request broadcast to its neighbouring devices, which include other meters and IoT-enabled nodes deployed in the vicinity.
[0085] Each of the neighbouring devices, upon receiving the request, compiles and returns a set of connectivity metrics to the requesting meter. These metrics include real-time cellular signal strength (e.g., RSRP, RSRQ), mesh latency (measured in hop count or RTT), link quality indicators (such as ETX), recent relay success rate, and current transmission load. The requesting meter stores these responses locally and begins evaluating potential relay candidates using a dynamic scoring algorithm.
[0086] Each candidate node is assigned a relay score calculated using a weighted formula. The weightings are determined based on current network conditions. For instance, in a high-congestion environment, the weights for network load and latency are increased, while in a low-connectivity zone, greater weight is assigned to link stability and cellular quality. One exemplary scoring breakdown is as follows:
Parameter Weight (%)
Cellular Signal Quality 40%
Mesh Latency 20%
Network Load 15%
Link Quality 15%
Historical Relay Stability 10%
[0087] Based on the relay scores, the requesting node selects the candidate with the highest adjusted score. In case of a tie, secondary criteria are applied in the following order, that is lowest mesh latency, lowest current data transmission load, and longest historical uptime as a successful relay. This ensures the selection of not only the most capable node but also the most reliable one under current network conditions.
[0088] Upon identifying the optimal relay node, the original meter transmits the data packet to the selected node. The packet includes routing metadata and a retry flag in case transmission fails. The relay node is responsible for forwarding the packet to the server using its available backhaul channel (e.g., cellular modem).
[0089] In the event the transmission to the relay fails or no acknowledgment is received within a timeout window, the requesting meter initiates a fail-safe protocol. It selects the next-best candidate based on the previously computed scores and retries the transmission with exponential backoff. If no suitable node is available, the data is locally stored in a buffer and re-evaluated after a predetermined interval.
[0090] The entire process, from connectivity assessment to final transmission, is logged and monitored. Periodic health checks between neighbouring meters ensure that up-to-date connectivity status is maintained in the node's internal neighbour table, thus enabling rapid adaptation to any topology changes such as device failure, congestion, or newly added nodes.
[0091] Example 02: Smart Water Meter Deployment in a Rural Mesh Network
[0092] In a rural smart metering scenario, multiple water meters are deployed across a geographically dispersed village where cellular coverage is intermittent. Each meter is equipped with a communication module that supports both short-range mesh networking and long-range cellular fallback.
[0093] A particular water meter (first node) is located near the edge of the village, where its own direct cellular connectivity is degraded due to terrain. The meter needs to transmit usage data to a central utility server. Before initiating transmission, the meter identifies its own connectivity metrics, including cellular signal strength, packet drop rate, and last successful transmission timestamp. Based on these metrics, the meter determines that its connectivity status is "weak" and initiates relay node discovery.
[0094] The meter then transmits a request to a plurality of nearby meters (plurality of nodes) within its mesh communication range, requesting their current connectivity metrics for possible relay support. Each nearby meter responds with the following metrics:
1. Signal strength to cellular network
2. Historical relay success rate
3. Number of hops to reach the server
4. Current queue length (ongoing transmissions)
5. Time of last successful message relayed
[0095] Upon receiving responses, the first meter applies a dynamic scoring function to identify the most suitable relay node. The relay score is computed based on weighted factors:
1. Stronger cellular signal contributes positively
2. Lower latency (measured via hop count) is favored
3. Lower transmission queue depth is rewarded
4. Nodes with a history of successful relays receive a performance bonus
5. Nodes with recent successful communication receive a time-weighted boost
[0096] The meter selects the node with the highest adjusted relay score as the relay node and transmits the signal (usage data packet) to that node. The selected node then forwards the data to the utility server over its cellular connection.
[0097] To ensure reliability, if the first meter does not receive an acknowledgment from the relay node within a predefined timeout, it retries with the next-best candidate based on the relay score. In critical transmission cases, the meter may also transmit the data to both the top and second-best nodes simultaneously (redundant routing).
[0098] Additionally, each meter stores its most recent connectivity metrics and periodically broadcasts these updates in the mesh. This ensures all nodes maintain a near real-time understanding of their neighbours’ performance, allowing quick re-selection if the network or connectivity conditions change (e.g., due to weather or terrain shifts). This working example illustrates how a smart meter operating in a remote environment can dynamically select the most reliable relay node using real-time connectivity metrics.
[0099] This working example illustrates a practical implementation of the method (300), enabling dynamic, context-aware relay node selection that improves data delivery reliability, supports load balancing, and ensures continued service even in fluctuating or degraded network conditions.
[00100] A person skilled in the art will understand that the scope of the disclosure is not limited to scenarios based on the aforementioned factors and using the aforementioned techniques, and that the examples provided do not limit the scope of the disclosure.
[00101] FIG. 4 illustrates a block diagram of an exemplary computer system (401) for implementing embodiments consistent with the present disclosure.
[00102] Variations of computer system (401) may be used for managing relay node selection in the wireless network. The computer system (401) may comprise a central processing unit (“CPU” or “processor”) (402). The processor (402) may comprise at least one data processor for executing program components for executing user or system generated requests. A user may include a person, a person using a device such as those included in this disclosure, or such a device itself. Additionally, the processor (402) may include specialized processing units such as integrated system (bus) controllers, memory management control units, floating point units, graphics processing units, digital signal processing units, or the like. In various implementations the processor (402) may include a microprocessor, such as AMD Athlon, Duron or Opteron, ARM’s application, embedded or secure processors, IBM PowerPC, Intel’s Core, Itanium, Xeon, Celeron or other line of processors, for example. Accordingly, the processor (402) may be implemented using mainframe, distributed processor, multi-core, parallel, grid, or other architectures. Some embodiments may utilize embedded technologies like application-specific integrated circuits (ASICs), digital signal processors (DSPs), or Field Programmable Gate Arrays (FPGAs), for example.
[00103] Processor (402) may be disposed in communication with one or more input/output (I/O) devices via I/O interface (403). Accordingly, the I/O interface (403) may employ communication protocols/methods such as, without limitation, audio, analog, digital, monoaural, RCA, stereo, IEEE-1394, serial bus, universal serial bus (USB), infrared, PS/2, BNC, coaxial, component, composite, digital visual interface (DVI), high-definition multimedia interface (HDMI), RF antennas, S-Video, VGA, IEEE 802.n /b/g/n/x, Bluetooth, cellular (e.g., code-division multiple access (CDMA), high-speed packet access (HSPA+), global system for mobile communications (GSM), long-term evolution (LTE), WiMAX, or the like, for example.
[00104] Using the I/O interface (403), the computer system (401) may communicate with one or more I/O devices. For example, the input device (404) may be an antenna, keyboard, mouse, joystick, (infrared) remote control, camera, card reader, fax machine, dongle, biometric reader, microphone, touch screen, touchpad, trackball, sensor (e.g., accelerometer, light sensor, GPS, gyroscope, proximity sensor, or the like), stylus, scanner, storage device, transceiver, video device/source, or visors, for example. Likewise, an output device (405) may be a user’s smartphone, tablet, cell phone, laptop, printer, computer desktop, fax machine, video display (e.g., cathode ray tube (CRT), liquid crystal display (LCD), light- emitting diode (LED), plasma, or the like), or audio speaker, for example. In some embodiments, a transceiver (406) may be disposed in connection with the processor (402). The transceiver (406) may facilitate various types of wireless transmission or reception. For example, the transceiver (406) may include an antenna operatively connected to a transceiver chip (example devices include the Texas Instruments® WiLink WL1283, Broadcom® BCM4750IUB8, Infineon Technologies® X-Gold 618-PMB9800, or the like), providing IEEE 802.11a/b/g/n, Bluetooth, FM, global positioning system (GPS), and/or 2G/3G/5G/6G HSDPA/HSUPA communications, for example.
[00105] In some embodiments, the processor (402) may be disposed in communication with a communication network (408) via a network interface (407). The network interface (407) is adapted to communicate with the communication network (408). The network interface (407) may employ connection protocols including, without limitation, direct connect, Ethernet (e.g., twisted pair 10/100/1000 Base T), transmission control protocol/internet protocol (TCP/IP), token ring, or IEEE 802.11a/b/g/n/x, for example. The communication network (408) may include, without limitation, a direct interconnection, local area network (LAN), wide area network (WAN), wireless network (e.g., using Wireless Application Protocol), or the Internet, for example. Using the network interface (407) and the communication network (408), the computer system (401) may communicate with devices such as shown as a laptop (409) or a mobile/cellular phone (410). Other exemplary devices may include, without limitation, personal computer(s), server(s), fax machines, printers, scanners, various mobile devices such as cellular telephones, smartphones (e.g., Apple iPhone, Blackberry, Android-based phones, etc.), tablet computers, desktop computers, eBook readers (Amazon Kindle, Nook, etc.), laptop computers, notebooks, gaming consoles (Microsoft Xbox, Nintendo DS, Sony PlayStation, etc.), or the like. In some embodiments, the computer system (501) may itself embody one or more of these devices.
[00106] In some embodiments, the processor (402) may be disposed in communication with one or more memory devices (e.g., RAM 413, ROM 414, etc.) via a storage interface (412). The storage interface (512) may connect to memory devices including, without limitation, memory drives, removable disc drives, etc., employing connection protocols such as serial advanced technology attachment (SATA), integrated drive electronics (IDE), IEEE-1394, universal serial bus (USB), fiber channel, small computer systems interface (SCSI), etc. The memory drives may further include a drum, magnetic disc drive, magneto-optical drive, optical drive, redundant array of independent discs (RAID), solid-state memory devices, or solid-state drives, for example.
[00107] The memory devices may store a collection of program or database components, including, without limitation, an operating system (416), user interface application (417), web browser (418), mail client/server (419), user/application data (420) (e.g., any data variables or data records discussed in this disclosure) for example. The operating system (416) may facilitate resource management and operation of the computer system (401). Examples of operating systems include, without limitation, Apple Macintosh OS X, UNIX, Unix-like system distributions (e.g., Berkeley Software Distribution (BSD), FreeBSD, NetBSD, OpenBSD, etc.), Linux distributions (e.g., Red Hat, Ubuntu, Kubuntu, etc.), IBM OS/2, Microsoft Windows (XP, Vista/7/8, etc.), Apple iOS, Google Android, Blackberry OS, or the like.
[00108] The user interface (417) is for facilitating the display, execution, interaction, manipulation, or operation of program components through textual or graphical facilities. For example, user interfaces (417) may provide computer interaction interface elements on a display system operatively connected to the computer system (401), such as cursors, icons, check boxes, menus, scrollers, windows, or widgets, for example. Graphical user interfaces (GUIs) may be employed, including, without limitation, Apple Macintosh operating systems’ Aqua, IBM OS/2, Microsoft Windows (e.g., Aero, Metro, etc.), Unix X-Windows, or web interface libraries (e.g., ActiveX, Java, JavaScript, AJAX, HTML, Adobe Flash, etc.), for example.
[00109] In some embodiments, the computer system (401) may implement a web browser (418) stored program component. The web browser (418) may be a hypertext viewing application, such as Microsoft Internet Explorer, Google Chrome, Mozilla Firefox, Apple Safari, or Microsoft Edge, for example. Secure web browsing may be provided using HTTPS (secure hypertext transport protocol), secure sockets layer (SSL), Transport Layer Security (TLS), or the like. Web browsers may utilize facilities such as AJAX, DHTML, Adobe Flash, JavaScript, Java, or application programming interfaces (APIs), for example. In some embodiments the computer system (401) may implement a mail client/server (419) stored program component. The mail server (419) may be an Internet mail server such as Microsoft Exchange, or the like. The mail server may utilize facilities such as ASP, ActiveX, ANSI C++/C#, Microsoft .NET, CGI scripts, Java, JavaScript, PERL, PHP, Python, or WebObjects, for example. The mail server (419) may utilize communication protocols such as internet message access protocol (IMAP), messaging application programming interface (MAPI), Microsoft Exchange, post office protocol (POP), simple mail transfer protocol (SMTP), or the like. In some embodiments, the computer system (401) may implement a mail client (420) stored program component. The mail client (420) may be a mail viewing application, such as Apple Mail, Microsoft Entourage, Microsoft Outlook, or Mozilla Thunderbird.
[00110] In some embodiments, the computer system (401) may store user/application data (421), such as the data, variables, records, or the like as described in this disclosure. Such databases may be implemented as fault-tolerant, relational, scalable, secure databases such as Oracle or Sybase, for example. Alternatively, such databases may be implemented using standardized data structures, such as an array, hash, linked list, struct, structured text file (e.g., JSON, XML), table, or as object-oriented databases (e.g., using ObjectStore, Poet, Zope, etc.). Such databases may be consolidated or distributed, sometimes among the various computer systems discussed above in this disclosure. It is to be understood that the structure and operation of any computer or database component may be combined, consolidated, or distributed in any working combination.
[00111] Furthermore, one or more computer-readable storage media may be utilized in implementing embodiments consistent with the present invention. A computer-readable storage medium refers to any type of physical memory on which information or data readable by a processor may be stored. Thus, a computer-readable storage medium may store instructions for execution by one or more processors, including instructions for causing the processor(s) to perform steps or stages consistent with the embodiments described herein. The term “computer readable medium” should be understood to include tangible items and exclude carrier waves and transient signals, i.e., non-transitory. Examples include Random Access Memory (RAM), Read- Only Memory (ROM), volatile memory, non-volatile memory, hard drives, Compact Disc (CD) ROMs, Digital Video Disc (DVDs), flash drives, disks, and any other known physical storage media.
[00112] The present disclosure addresses the inefficiencies and limitations of traditional relay node selection methods, which often rely on static routing protocols and manual node prioritization for managing data transmission in wireless networks. These conventional approaches are prone to network congestion, communication delays, and suboptimal resource allocation, particularly in large-scale and dynamic environments. Traditional systems typically lack the ability to dynamically adjust to real-time changes in signal quality, link stability, network congestion, and node availability, leading to inefficient data routing and reduced overall network performance. Additionally, they often fail to incorporate historical performance data when selecting relay nodes, resulting in inconsistent link quality and frequent transmission failures, especially when network conditions fluctuate unexpectedly. By relying on fixed node hierarchies and predefined routing paths, these conventional methods struggle to efficiently manage large volumes of real-time data, leading to underutilized resources and increased latency as traffic patterns evolve.
[00113] To overcome these challenges, the disclosed system introduces an automated and adaptive approach for relay node selection, leveraging real-time connectivity metrics and intelligent scoring algorithms to optimize data routing. The system automatically transmits requests to nearby nodes, receives real-time connectivity data, and dynamically selects the optimal relay node based on a comprehensive analysis of metrics such as signal strength, link quality, latency, network load, and historical performance data. This data-driven approach significantly reduces the need for manual intervention, enhancing the efficiency and reliability of data transmission. By continuously monitoring network conditions and adjusting relay node selection in response to changing topologies and device states, the system minimizes transmission delays, prevents network congestion, and ensures optimal resource utilization, even in complex, distributed networks.
[00114] Further, this automation-driven solution provides seamless, accurate, and scalable relay node selection, significantly reducing network overhead and operational costs. By replacing manual configuration with automated node scoring and dynamic relay selection, the system eliminates common bottlenecks, reduces transmission errors, and ensures consistent performance in high-density networks. The integration of real-time monitoring and adaptive scoring enables the system to self-optimize in response to network changes, enhancing the stability and efficiency of communication across the network. This approach ensures uninterrupted data flow, improved scalability, and better resource allocation, making it particularly suitable for applications ranging from smart metering to industrial IoT and decentralized sensor networks.
[00115] Various embodiments of the disclosure encompass numerous advantages, including a method and system for managing relay node selection by a first node in a wireless network. The disclosed method and system have several technical advantages, including but not limited to the following:
• Decentralized Operation: Facilitates dynamic and autonomous relay node selection without the need for centralized coordination, enhancing scalability and fault tolerance.
• Resilient Communication: Enables reliable data transmission in partially connected or dynamically changing networks, improving communication robustness even in harsh or mobile environments.
• Cost Efficiency: Reduces infrastructure costs by minimizing the need for dedicated 4G or 5G modules, leveraging local mesh communication for efficient data routing.
• Optimized Network Utilization: Efficiently handles real-time sensor data, reducing latency and improving response times for critical applications like industrial automation, remote monitoring, and emergency communication.
• Seamless Compatibility: Compatible with various IPv6 mesh stacks and embedded platforms, ensuring broad applicability across different IoT, industrial, and smart infrastructure deployments.
• Scalable Multicast Communication: Utilizes multicast over IPv6 for both request and response messages, reducing network overhead and enhancing scalability in dense device environments.
• Enhanced Security: Provides secure, authenticated communication, ensuring that only trusted nodes participate in the relay process, reducing the risk of unauthorized data interception.
[00116] In summary, the disclosed method and system effectively address the technical challenges of relay node selection in distributed wireless networks by providing a highly automated, scalable, and intelligent approach. By leveraging real-time connectivity metrics, dynamic node scoring, and multicast communication over IPv6, the system ensures optimal network performance and efficient resource utilization. The integration of advanced algorithms, such as weighted scoring for evaluating relay nodes based on signal quality, link quality, historical performance, and network congestion levels, minimizes transmission delays, enhances reliability, and supports seamless data transfer across diverse network topologies. Additionally, the system's ability to adapt to real-time network changes, coupled with its flexible support for various wireless communication protocols, allows it to handle high device densities and complex network environments. This approach not only improves network scalability and reduces operational costs, but also ensures uninterrupted service in applications ranging from smart metering and industrial IoT to decentralized sensor networks, thereby significantly enhancing overall operational efficiency and user satisfaction.
[00117] The claimed invention of a method and system for managing relay node selection by a first node in a wireless network involves tangible components, processes, and functionalities that interact to achieve specific technical outcomes. The system integrates various elements such as processors, memory, databases, modelling, real-time fast processing, unnecessary data omitting and informed displaying techniques to effectively manage the relay node selection in the wireless network.
[00118] The present disclosure introduces a non-trivial combination of technologies and methodologies that provide a technical solution for a technical problem. While individual components like processors, databases, encryption, authorization and authentication are well-known in the field of computer science, their integration into a comprehensive system for managing relay node selection in the wireless network brings about improvement and technical advancement in the field of smart meters and other related services.
[00119] In light of the above-mentioned advantages and the technical advancements provided by the disclosed method and system for managing relay node selection in the wireless network, the claimed steps as discussed above are not routine, conventional, or well understood in the art, as the claimed steps enable the following solutions to the existing problems in conventional technologies. Further, the claimed steps clearly bring an improvement in the functioning of the device itself as the claimed steps provide a technical solution to a technical problem.
[00120] The present disclosure may be realized in hardware, or a combination of hardware and software. The present disclosure may be realized in a centralized fashion, in at least one computer system, or in a distributed fashion, where different elements may be spread across several interconnected computer systems. A computer system or other apparatus adapted for carrying out the methods described herein may be suited. A combination of hardware and software may be a general-purpose computer system with a computer program that, when loaded and executed, may control the computer system such that it carries out the methods described herein. The present disclosure may be realized in hardware that comprises a portion of an integrated circuit that also performs other functions.
[00121] A person with ordinary skills in the art will appreciate that the systems, modules, and sub-modules have been illustrated and explained to serve as examples and should not be considered limiting in any manner. It will be further appreciated that the variants of the above disclosed system elements, modules, and other features and functions, or alternatives thereof, may be combined to create other different systems or applications.
[00122] Those skilled in the art will appreciate that any of the aforementioned steps and/or system modules may be suitably replaced, reordered, or removed, and additional steps and/or system modules may be inserted, depending on the needs of a particular application. In addition, the systems of the aforementioned embodiments may be implemented using a wide variety of suitable processes and system modules, and are not limited to any particular computer hardware, software, middleware, firmware, microcode, and the like. The claims can encompass embodiments for hardware and software, or a combination thereof.
[00123] While the present disclosure has been described with reference to certain embodiments, it will be understood by those skilled in the art that various changes may be made, and equivalents may be substituted without departing from the scope of the present disclosure. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the present disclosure without departing from its scope. Therefore, it is intended that the present disclosure is not limited to the particular embodiment disclosed, but that the present disclosure will include all embodiments falling within the scope of the appended claims.
, C , Claims:WE CLAIM
1. A method (300) for managing relay node selection by a first node in a wireless network, wherein the method (300) comprises:
identifying (302) a connectivity metrics of the first node;
determining (304) a connectivity status of the first node;
transmitting (306) a request to a plurality of nodes in the wireless network, based on the connectivity status, for seeking connectivity metrics of the plurality of nodes;
receiving (308) the connectivity metrics of each of the plurality of nodes;
identifying (310) a relay node from the plurality of nodes based on the connectivity metrics of each of the plurality of nodes; and
transmitting (312) a signal to the relay node for transmission to a server.
2. The method (300) as claimed in claim 1, wherein the connectivity metrics comprise at least one of node identification information, connectivity channel, signal strength, signal quality, link quality, latency, network load, time of last metric update, historical relay performance data, device role, node state, node stability status, connectivity availability, network congestion or a combination thereof; wherein the signal strength corresponds to at least one of a received signal strength indication (RSSI), a reference signal received power (RSRP), a reference signal received quality (RSRQ), a signal-to-noise ratio (SNR), or a combination thereof; wherein the link quality corresponds to at least one of expected transmission count (ETX), packet error rate (PER), average round-trip time (RTT), or a combination thereof; wherein the connectivity availability corresponds to at least one of connection uptime, handoff stability, network congestion levels, or a combination thereof; wherein the node identification information for each node comprise at least one of a device name, a device identifier, a device type, a network address, or a combination thereof; and historical relay performance data correspond to at least one of average data transmission rate, relay selection frequency, average link uptime, previous relay node failures, or a combination thereof.
3. The method (300) as claimed in claim 1, comprises broadcasting the connectivity metrics of the first node to the plurality of nodes in the wireless network.
4. The method (300) as claimed in claim 1, wherein determining (304) the connectivity status corresponds to comparing the connectivity metrics with at least one predetermined threshold parameter selected from signal strength threshold, latency threshold, or network congestion threshold.
5. The method (300) as claimed in claim 1, wherein transmitting (306) the request to the plurality of nodes and receiving (308) the connectivity metrics from each of the plurality of nodes and transmitting (312) the signal to the relay node, are performed via User Datagram Protocol (UDP) over IPv6 protocol in the wireless network.
6. The method (300) as claimed in claim 1, comprising authenticating the plurality of nodes prior to receiving (308) the connectivity metrics to ensure secure relay node selection.
7. The method (300) as claimed in claim 1, wherein the wireless network corresponds to a wireless mesh network, IPv6 enabled wireless mesh network, an ad-hoc wireless network, a multi-hop wireless network, a self-organizing network (SON), a decentralized wireless network, a peer-to-peer wireless network, Open Thread, cellular network, NB-IoT, Ethernet, Wi-FI, or a combination thereof; wherein the plurality of nodes is connected to the first node in the wireless network, wherein the first node is different from the plurality of nodes in the wireless network.
8. The method (300) as claimed in claim 1, comprises storing the connectivity metrics of the plurality of nodes and the connectivity metrics of the first node in a database.
9. The method (300) as claimed in claim 1, wherein identifying (310) the relay node from the plurality of nodes comprises:
dynamically providing weights to each of one or more parameters from the connectivity metrics;
calculating a relay score for each node from the plurality of nodes based on the dynamically provided weights utilizing a scoring technique;
applying penalties and bonus to adjust the relay score for each node from the plurality of nodes based on one of current network condition, recent connection failure, current relay load, successful relay, historical relay performance data; and
selecting the relay node from the plurality of nodes with highest adjusted relay score.
10. The method (300) as claimed in claim 1, wherein identifying (302) the connectivity metrics of the first node is performed either periodically within a predefined time period or on the request from either of the plurality of nodes.
11. The method (300) as claimed in claim 1, wherein the one or more nodes corresponds to one of a utility meter, electricity, meter, gas meter, water meter, hybrid meters, digital meter, prepaid meter, postpaid meter, residential meter, commercial meter, industrial meter, routers, modems, sensors, Internet-of-Things (IoT) device and a combination thereof.
12. A system (100) for managing relay node selection by a first node in a wireless network, wherein the system (100) comprising:
a processor (202);
a memory (204) communicatively coupled with the processor (202), the memory (204) configured to store executable instructions that, when executed by the processor (202), cause the processor (202) to:
identify (302) a connectivity metrics of the first node;
determine (304) a connectivity status of the first node;
transmit (306) a request to a plurality of nodes in the wireless network, based on the connectivity status, for seeking connectivity metrics of the plurality of nodes;
receive (308) the connectivity metrics of each of the plurality of nodes;
identify (310) a relay node from the plurality of nodes based on the connectivity metrics of each of the plurality of nodes; and
transmit (312) a signal to the relay node for transmission to a server.
13. A non-transitory computer-readable storage medium having stored thereon, a set of computer-executable instructions causing a computer comprising one or more processors to perform steps comprising:
identifying (302) a connectivity metrics of a first node;
determining (304) a connectivity status of the first node;
transmitting (306) a request to a plurality of nodes in a wireless network, based on the connectivity status, for seeking connectivity metrics of the plurality of nodes;
receiving (308) the connectivity metrics of each of the plurality of nodes;
identifying (310) a relay node from the plurality of nodes based on the connectivity metrics of each of the plurality of nodes; and
transmitting (312) a signal to the relay node for transmission to a server.
Dated this 13th day of June 2025

ABHIJEET GIDDE
AGENT FOR THE APPLICANT
IN/PA- 4407