Description:TITLE OF THE INVENTION: BITA-BASED SECURE AND ENERGY-EFFICIENT MULTI-HOP ROUTING IN IOT-WSN
FIELD OF THE INVENTION
[0001] The present invention relates to the field of Wireless Sensor Networks (WSNs) and the Internet of Things (IoT). More particularly, the present invention relates to a system of BITA-based secure and energy-efficient multi-hop routing in IoT-WSN.
BACKGROUND OF THE INVENTION
[0002] Wireless Sensor Networks (WSNs) have emerged as an essential component of modern technology, enabling a wide range of applications in environmental monitoring, healthcare, agriculture and smart cities. These networks consist of numerous sensor nodes that collect, process and transmit data to a central base station. However, the inherent constraints of WSNs, such as limited energy resources, computational capabilities and susceptibility to security threats, pose significant challenges to their efficiency and longevity. In addition, the rising adoption of IoT has intensified the demand for robust and reliable WSNs that can support seamless data transmission across diverse environments.
[0003] Conventional routing protocols in WSNs primarily focus on either energy efficiency or security but rarely achieve an optimal balance between the two. Energy-efficient protocols extend the network's operational lifespan but may compromise security, leaving the network vulnerable to attacks. Conversely, security-focused protocols often increase computational overhead and energy consumption, reducing the overall efficiency of the network. This situation shows the importance of finding creative ways to tackle these problems as a whole. The goal is to ensure communication in wireless sensor networks (WSNs) is both secure and energy-efficient, especially when dealing with limited resources.
[0004] So, the present invention provides a BITA-based secure and energy-efficient multi-hop routing system in IoT-WSN. The system applies the Beet Swarm Induced Tunicate Swarm Algorithm (BITA) to optimize Cluster Head (CH) selection by considering energy efficiency, security and communication costs. It establishes multi-hop communication paths to reduce energy consumption and support reliable data transmission.
[0005] However, there were lots of efforts made to improve routing efficiency and security in Wireless Sensor Networks (WSNs). Some of the references known to us are as follows:
Prior Arts:
[0006] US8547982B2 describes a system and method for a wireless sensor network with energy-efficient routing protocols that optimize communication between nodes, clusters and a central sink node. The method includes waking up nodes, monitoring keep-alive packets and assigning roles as cluster heads or member nodes based on signal strength and timeouts. Cluster heads transmit and relay data packets in a multi-hop manner to nodes topologically closer to the sink, ensuring efficient data transmission. Periodic role-switching between cluster heads and member nodes balances energy consumption. Unsynchronized nodes (UGNs) transmit data to the nearest cluster head upon receiving a keep-alive signal, which then forwards the data to the sink which enhances network longevity by maintaining synchronization through a single master clock and adapting to changing network conditions.
[0007] US20060178150A1 describes the system and method of transmitting data with minimum energy consumption in a wireless sensor network. The method involves configuring a tree structure when a new sink is added, by selecting an optimal path with minimal delay and energy consumption. Initially, a first sensor node is chosen based on the smallest delay cost, followed by determining whether a direct path to the sink is energy-efficient. If not, a second sensor node is selected to ensure minimal energy usage. The tree is then updated based on energy and delay cost comparisons, considering both direct and multi-hop paths. A set of predetermined conditions is used to evaluate the energy costs and delays for selecting the optimal path which ensures efficient data routing and energy conservation within the network.
[0008] US20080037560A1 describes the system and method of a solution for routing schemes in wireless communication, specifically in mobile terminals. The method involves receiving route probing signals from another mobile terminal, calculating the route cost to the destination mobile terminal based on system performance parameters and sending response messages with the calculated route cost. The mobile terminal forwards probing signals to other terminals, acquires route costs and compares these with the calculated cost. The best route is selected by evaluating the link cost through multiple hops. The route cost is determined using a formula that considers factors like the number of hops and the wireless route cost at each hop.
[0009] IN202441092971A describes the system and method of a multi-phase energy-efficient scheduling and routing system to enhance network lifespan in wireless body area networks. The invention proposes the TESLDAR protocol, which integrates the Jellyfish Updated Aquila Narrow ExploExpand (JUANE) method to address network issues such as hotspot-induced thermal stress, trustworthiness concerns, and congestion. The JUANE algorithm combines Jellyfish Optimization (JFO), inspired by the movement of jellyfish, and Aquila bird-inspired exploration-exploitation strategies to dynamically adapt to changing network conditions. It initiates candidate routes, ensuring efficient communication, and balances exploration and exploitation in route discovery. The algorithm achieves improved energy consumption, network lifetime, throughput, and data delivery ratio. JUANE outperforms existing techniques in ensuring reliable and timely data transmission, making it an effective solution for optimizing network performance.
[0010] State-of-the-art suffers from the following limitations:
[0011] The state of the art does not consider a BITA-based secure and energy-efficient multi-hop routing system for IoT-WSN. Traditional routing protocols primarily focus on either energy efficiency or security, often overlooking the need for an optimized approach that balances both aspects. Existing systems tend to rely on basic energy-efficient methods or security mechanisms, failing to provide a holistic solution for network reliability, longevity and defense against malicious attacks. So, the present invention addresses the gap in existing systems by providing a BITA-based secure and energy-efficient multi-hop routing system that optimizes Cluster Head (CH) selection while ensuring data transmission security. The Beet Swarm Induced Tunicate Swarm Algorithm (BITA) is used to evaluate multiple objectives such as energy efficiency, communication cost, and security to select the most suitable Cluster Heads. By optimizing CH selection, the system ensures efficient data transmission while minimizing energy consumption, improving overall network performance. The routing system enables multi-hop communication, allowing data to flow between nodes and the base station. A key component of the system is the Decision-Making Unit (DMU), which is equipped with an AI module to process data and analyze various parameters based on predefined thresholds. The AI module enhances the decision-making process by intelligently evaluating network conditions and suggesting optimal actions. Based on this analysis, the DMU triggers actions, such as sending alerts or recommendations to the user or network administrator. The controller, connected to the DMU, takes the necessary actions based on the decisions made, ensuring uninterrupted network operation. Alerts may include notifications about network performance, energy status or security breaches, enabling quick responses to potential issues.
OBJECTIVES OF THE INVENTION
[0012] The main objective of the present invention is to provide a secure and energy-efficient multi-hop routing system for IoT-WSN that optimizes Cluster Head (CH) selection using the Beet Swarm Induced Tunicate Swarm Algorithm (BITA).
[0013] Another objective of the present invention is to optimize Cluster Head (CH) selection by evaluating multiple competing objectives, including residual energy, inter-cluster distances, communication costs and security, ensuring balanced network operations.
[0014] Still, another objective of the present invention is to include a Multi-Objective Optimization Module based on BITA to handle competing objectives like minimizing energy consumption, reducing communication overhead, and enhancing data security.
[0015] Still, another objective of the present invention is to enable the Multi-Hop Routing Module to establish efficient communication paths between the selected Cluster Heads (CHs) and the Base Station (BS), reducing energy consumption and improving data transmission reliability.
[0016] Another objective of the present invention is to incorporate a Decision-Making Unit (DMU) equipped with an AI module to analyze data received from the Base Station, evaluate it against predefined thresholds and provide relevant information for the user.
[0017] Another objective of the present invention is to include a controller that generates a control signal based on the decisions made by the Decision-Making Unit (DMU), improving network reliability and security while providing real-time alerts and notifications to users or administrators regarding network performance, energy consumption and potential security breaches.
SUMMARY OF THE INVENTION
[0018] The present invention summary is easy to understand before the hardware and system enablement were illustrated in this present invention. There have been multiple possible embodiments that do not expressly point up in this method's present acknowledgment. Here, the conditions are used to explain the purpose of exacting versions or embodiments for understanding the present invention.
[0019] The main aspect of the present invention is a BITA-based secure and energy-efficient multi-hop routing system for IoT-WSN. The system uses the Beet Swarm Induced Tunicate Swarm approach to select optimal Cluster Heads (CHs) by evaluating multiple objectives such as energy efficiency, communication cost and security. The selection process ensures a balance between energy consumption, network stability, and communication reliability. After identifying the CHs, the Multi-Hop Routing Module establishes efficient communication paths that minimize energy usage while ensuring secure data transmission. The system also includes a Decision-Making Unit (DMU) equipped with an AI module, which processes the routing decisions and generates real-time alerts and reports for administrators and users, ensuring proactive management and maintaining optimal network performance.
[0020] Another aspect of the present invention is the Multi-Objective Optimization Module, which utilizes BITA to evaluate multiple factors such as residual energy, communication costs and security risks for selecting the most optimal Cluster Heads. The BITA method combines local search capabilities for energy-efficient operations with global exploration for improved communication reliability. The resulting fitness scores for each node determine the most suitable Cluster Heads for the network, ensuring extended system life and efficient resource use.
[0021] Still, another aspect of the present invention is the Multi-Hop Routing Module, which utilizes the selected Cluster Heads to establish communication paths to the Base Station (BS). This module calculates energy-efficient routes and ensures that the data transmission process does not overload any node, optimizing the overall performance of the IoT-WSN network. The routing method selects paths that minimize energy consumption, guaranteeing both network reliability and data security.
[0022] Further aspect of the present invention is the Decision-Making Unit (DMU) equipped with an AI module, which plays an essential role in evaluating the data received from the Base Station. This unit compares the data against predefined thresholds to assess key parameters such as network performance, energy usage and security levels. By processing the incoming data, the DMU identifies any deviations or potential issues in the system.
[0023] Additionally, another aspect of the present invention includes a controller that generates control signals based on the decisions made by the Decision-Making Unit. This controller helps improve network reliability and security by ensuring that all actions, such as path reconfigurations or alert activations, are carried out in real time. Alerts and notifications are sent to administrators regarding performance, energy usage and security breaches, enabling timely responses to potential issues and facilitating management of the IoT-WSN system.
BRIEF DESCRIPTION OF THE DRAWINGS
[0024] The accompanying drawings, which are incorporated, constitute a part of the specification, illustrate the invention's embodiment, and the description serves to explain the principles of the invention.
[0025] Various embodiments will be described under the appended drawings, which are provided to illustrate the present invention.
[0026] Figure 1 illustrates the block diagram of the present invention as provided in the present invention.
[0027] Figure 2 illustrates the flow diagram of the present invention as provided in the present invention.
[0028] Figure 3 illustrates the schematic diagram of the cluster head selection in wireless sensor networks based on BITA as provided in the present invention.
[0029] Figure. 4 illustrates the block diagram of a BITA-based Cluster Head Selection System for Wireless Sensor Networks.
DETAILED DESCRIPTION OF THE INVENTION
[0030] The present invention is easily understood with references, detailed descriptions, block diagrams, and figures. Here, various embodiments have been discussed regarding the block diagram, architecture and other references. Some embodiments of this invention, illustrating its features, will now be discussed, and the disclosed embodiments are merely exemplary of the invention that may be embodied in various forms.
[0031] Nowadays, the growing adoption of Internet of Things (IoT) technology has led to the proliferation of Wireless Sensor Networks (WSNs) across various sectors, such as healthcare, agriculture and smart cities. These networks consist of numerous distributed sensor nodes that collect and transmit data, enabling real-time monitoring and decision-making. However, the increasing complexity of IoT-WSNs poses significant challenges, particularly in terms of energy efficiency, communication reliability and security. As sensor nodes are typically powered by limited energy sources, maintaining network longevity without compromising performance remains a critical concern. Furthermore, security remains a paramount issue, as these networks are often susceptible to various cyber threats, which could lead to data breaches and network disruptions. As a result, new methods and techniques are continually being explored to address these challenges, ensuring the scalability, efficiency, and security of IoT-WSNs.
[0032] So, the present invention provides a BITA-based secure and energy-efficient multi-hop routing system for IoT-WSN. It addresses the critical challenges of energy consumption, communication efficiency and network security in wireless sensor networks. The system utilizes the Beet Swarm Induced Tunicate Swarm Algorithm (BITA) as a multi-objective optimization technique to select optimal Cluster Heads (CHs) based on factors such as energy efficiency, communication costs and security. BITA combines local search for energy-efficient operations with global exploration for improved communication reliability. This ensures that the network operates efficiently, extending the overall lifespan of the system while maintaining secure data transmission. By evaluating and selecting the best-suited Cluster Heads, BITA optimizes the network's performance, balancing energy consumption, stability and security.
[0033] The multi-hop routing system works by utilizing the selected Cluster Heads (CHs) to establish energy-efficient communication paths between sensor nodes and the Base Station (BS). By optimizing the communication paths, the system ensures reliable and secure data transmission, reducing the energy consumption of individual nodes and preventing network congestion. The routing mechanism prioritizes energy-saving paths while also ensuring that no node is overloaded with excessive data traffic. The Decision-Making Unit (DMU), equipped with an AI module, is responsible for monitoring the system's performance. It analyzes the data received from the Base Station and compares it to predefined thresholds to assess the current state of the network.
[0034] To further enhance network management, the system includes a controller that generates control signals based on the decisions made by the DMU. This controller ensures that the necessary actions, such as reconfiguring communication paths or triggering alerts, are executed in real-time. Alerts are sent to administrators, informing them of any significant issues related to energy usage, performance, or security, allowing for quick response and resolution of potential problems.
[0035] In this embodiment of the present invention, as shown in the figure.1 refers to the block diagram of the present invention which comprises sensor nodes (101), cluster formation (102), Multi-objective Optimization Module (103), Cluster Head Selection Module (104), Multi-hop routing module (105), Base station (106), Decision-making unit – AI Module (107) and controller (108).
[0036] In this embodiment of the present invention, Figure 1 illustrates the block diagram of the present invention. The diagram represents a system designed to manage and optimize a Wireless Sensor Network (WSN) by organizing sensor nodes, selecting cluster heads and establishing reliable communication paths. The sensor nodes (101) are the fundamental units of the WSN, responsible for collecting environmental data such as temperature, humidity and other relevant metrics from their surroundings. Each sensor node also monitors its energy levels to assess its capability to continue functioning within the network. Once the data is gathered, it is transmitted to the designated Cluster Head (CH). The cluster formation module (102) organizes the sensor nodes into clusters based on factors such as proximity to each other and energy efficiency. This clustering process helps optimize the network’s structure by minimizing communication overhead, reducing energy consumption and improving data aggregation. The nodes within each cluster communicate with their respective Cluster Head (104), which coordinates the network’s operation within that cluster.
[0037] The multi-objective optimization module (103) utilizes BITA (Bee and Tunicate Swarm-Inspired Algorithm) to optimize the selection of Cluster Heads (CHs), considering multiple factors such as energy efficiency, communication costs and network coverage which ensures that the network operates efficiently, maintains stable communication and reduces energy consumption over time. Based on the output of the optimization module, the cluster head selection module (104) selects the most suitable sensor nodes to serve as Cluster Heads (CHs). These CHs are responsible for managing communication within their respective clusters and aggregating the data received from the sensor nodes. The selection process ensures that the most capable nodes are chosen to maintain the network’s overall performance.
[0038] The multi-hop routing module (105) establishes communication paths between the sensor nodes and the Base Station (BS) (106) using a multi-hop routing strategy. Data is relayed from one node to another until it reaches the Base Station, ensuring reliable data transmission over long distances and optimizing energy usage by selecting the most reliable routes for data transmission. The Base Station serves as the central point of communication within the network, receiving data from the sensor nodes through the established communication paths and possibly forwarding it to external systems for further analysis.
[0039] The Decision-Making Unit (DMU) equipped with an AI module (107) analyzes the data received from the Base Station (106), compares it to predefined thresholds and generates reports or triggers actions based on predefined rules. It provides valuable information about the network’s performance, energy consumption and security status, helping administrators or users make informed decisions for managing the system. The Controller (108) manages and oversees the operation of the entire system, taking decisions or instructions generated by the DMU (107) and implementing actions such as generating a control signal to reconfigure the network, adjusting parameters, or initiating other necessary operations to maintain efficiency and security. Finally, the system can send alerts to the administrator or users (109) regarding critical events or anomalies within the system, such as network performance issues, energy consumption anomalies, or potential security breaches, prompting timely intervention to address any problems.
[0040] In this embodiment of the present invention, as shown in the figure.2 refers to the flow chart of the present invention detailing the steps involved in the process.
[0041] Figure 2 illustrates the flow chart of the present invention, which outlines the process of optimizing and managing a Wireless Sensor Network (WSN) using the BITA-based approach for Cluster Head (CH) selection, energy-efficient multi-hop routing and data aggregation. The process begins with the Cluster Formation step, where sensor nodes in the network are grouped into clusters based on their proximity and energy levels which ensures that the network is organized reliably, improving the overall communication and energy usage within the system.
[0042] Once the clusters are formed, the Input Parameters to Optimization Module step follows, where specific parameters like energy consumption, communication costs and coverage area are provided to the optimization module. This data is used to Select the Cluster Heads Using BITA, a process guided by the BITA algorithm, which determines the most suitable nodes to act as Cluster Heads. The BITA approach evaluates various factors to ensure that the selected Cluster Heads are capable of efficiently managing their respective clusters while also considering energy efficiency and network performance.
[0043] Next, the system checks whether the selected Cluster Head is energy-efficient. If the answer is Yes, the process proceeds to set up Multi-Hop Routing. This ensures that the communication between nodes in the network occurs in a way that minimizes energy consumption while still allowing reliable data transmission to the Base Station (BS). The routing strategy utilizes multiple hops, where data is relayed through intermediate nodes before reaching its final destination, reducing the energy burden on any single node. After setting up the routing paths, the network moves to the Data Aggregation and Transmission phase, where sensor nodes collect environmental data, aggregate it at the Cluster Head and transmit it to the Base Station.
[0044] If, however, the selected Cluster Head is not energy-efficient, the system loops back to Recalculate CH Selection, where the optimization process is repeated to select a more suitable Cluster Head. Once the data is successfully transmitted, the Decision-Making Unit (DMU) equipped with an AI module receives the data, processes it, and generates actionable insights about the network's performance, energy usage, and potential issues. The process then ends, ensuring that the system continuously adapts and optimizes based on real-time conditions.
[0045] In this embodiment of the present invention, as shown in the figure.3 refers to the Schematic diagram of the cluster head selection in wireless sensor networks based on BITA which comprises a cluster head, cluster member, base station and BITA optimization module.
[0046] In this embodiment of the present invention, Figure 3 illustrates the schematic diagram of the cluster head selection in wireless sensor networks based on BITA (Beet Swarm Induced Tunicate Swarm Algorithm). The diagram highlights the structure of the network and its interactions, where the base station serves as the central communication hub that connects to the cluster heads. The cluster heads are responsible for managing the data collection from the cluster members and optimizing the flow of information within the network.
[0047] The diagram presents the base station as a central node with communication links directed toward the cluster heads, each of which manages a specific set of cluster members, represented by the filled circles. The cluster heads, shown as open circles, serve as intermediate nodes between the base station and the members. They collect and aggregate data from the cluster members and transmit it to the base station, ensuring a reliable flow of information.
[0048] The BITA optimization module utilizes the Beet Swarm Induced Tunicate Swarm Algorithm to select the most suitable cluster heads based on specific criteria, such as node energy levels, distance to the base station, and overall network efficiency. By selecting the optimal cluster heads, the network achieves improved performance in terms of energy consumption, communication overhead and data transmission reliability which enables better scalability and energy efficiency in wireless sensor networks, particularly for applications that require long-term deployment in remote or challenging environments, such as environmental monitoring or military surveillance.
[0049] In this embodiment of the present invention, as shown in the figure.4 refers to the Block Diagram of a BITA-Based Cluster Head Selection System for Wireless Sensor Networks which comprises a Node initialization (401), Cluster formation (402), Fitness calculation (403), BITA Optimization process (404) and Multi-Hop Routing Setup (407).
[0050] In this embodiment of the present invention, Figure 4 illustrates the Block Diagram of a BITA-Based Cluster Head Selection System for Wireless Sensor Networks. The diagram outlines a step-by-step process involved in selecting optimal cluster heads (CH) in wireless sensor networks using the Beet Swarm Induced Tunicate Swarm Algorithm (BITA). Each block in the diagram represents a specific phase of the system, from node initialization to establishing communication paths between the base station and the cluster heads.
[0051] In this embodiment of the present invention, Figure 4 illustrates the Block Diagram of a BITA-Based Cluster Head Selection System for Wireless Sensor Networks. The diagram outlines a structured process for selecting the optimal cluster heads (CH) in wireless sensor networks using the Beet Swarm Induced Tunicate Swarm Algorithm (BITA). The process begins with Node Initialization (401), where each node is assigned a unique ID, initial energy levels and operational parameters. This initialization ensures the network is set up correctly and prepares the nodes for their roles within the system.
[0052] Once the nodes are initialized, the system proceeds to Cluster Formation (402), where nodes are grouped based on their proximity and energy levels. This step is essential for creating efficient communication paths and ensuring that the network is organized in a way that minimizes energy consumption and communication overhead. The nodes are grouped in such a way that those with similar characteristics, such as proximity, are clustered together, helping to optimize data transmission. For example, in the diagram, nodes like Node 1 (4021), Node 2 (4021), Node 3 (4021), and Node 4 (4021) are assigned to the same cluster based on their proximity and energy levels.
[0053] Following cluster formation, the Fitness Calculation (403) phase evaluates the nodes based on four key measures: Measure 1 Residual Energy (4031), Measure 2 Communication Cost (4032), Measure 3 Security Metrics (4033), and Measure 4 Proximity (4034). These measures assess the performance and suitability of each node for becoming a cluster head. By evaluating the nodes against these criteria, the system can determine which nodes have the highest potential to perform well as cluster heads, ensuring that the network operates efficiently in terms of energy consumption and data reliability.
[0054] The BITA Optimization Process (404) plays an essential role in selecting the optimal cluster heads. The Beet Swarm Algorithm (4041) and Tunicate Swarm Algorithm (4042) are used to optimize the selection process by considering the fitness measures of each node. A Local Search for CH Candidates (405) is then performed to identify the most suitable candidates for the role of cluster head which ensures that only the best-performing nodes are selected, contributing to the overall reliability of the network.
[0055] Finally, after selecting the cluster heads, the system moves to CH Selection (406) and Multi-Hop Routing Setup (407). In the CH Selection phase, the node with the highest fitness score is chosen as the cluster head. Following this, Multi-Hop Routing Setup (407) establishes communication paths between the cluster heads and the base station, ensuring reliable data transmission from the sensor nodes to the base station, with the cluster heads acting as intermediaries which ensure that the network remains scalable, supporting long-term deployments in remote or challenging environments. , Claims:We Claim,
1. A wireless sensor network system (100) designed to optimize the selection of cluster heads and communication within a network of sensor nodes, comprising: (i) a plurality of sensor nodes (101) configured to collect environmental data and monitor their energy levels; (ii) a cluster formation module (102) to group sensor nodes into clusters based on proximity and energy levels; (iii) a cluster head selection module (104) configured to select the most suitable nodes to serve as cluster heads, responsible for managing communication and data aggregation within the clusters; (iv) a multi-hop routing module (105) for establishing communication paths between sensor nodes and a base station (106), ensuring reliable data transmission through multi-hop routing; (v) a base station (106) for receiving data transmitted by the sensor nodes and processing it for further analysis; (vi) a controller (108) configured to generate a control signal based on the decisions generated by the decision-making unit (107) to maintain the efficiency and security of the system, characterized in that,
a) a multi-objective optimization module (103) utilizes BITA (Bee and Tunicate Swarm-Inspired Algorithm) to optimize the selection of cluster heads based on multiple factors, including energy efficiency, communication cost, and network coverage; and
b) a decision-making unit (107) equipped with an AI module analyzes data from the base station (106) and triggers actions based on predefined thresholds, such as network reconfiguration or sending alerts for network anomalies.
2. The wireless sensor network system (100) as claimed in Claim 1, wherein the said cluster head selection module (104) selects the most capable sensor nodes to act as cluster heads, based on their energy levels, communication capabilities and proximity to other nodes, ensuring reliable performance of the network.
3. The wireless sensor network system (100) as claimed in Claim 1, wherein the said multi-hop routing module (105) establishes communication paths between sensor nodes and the base station (106) by selecting reliable routes that optimize energy consumption during data transmission.
4. The wireless sensor network system (100) as claimed in Claim 1, wherein the said controller (108) generates control signals based on the decision made by the decision-making unit equipped with an AI module (107) and executes actions, such as adjusting parameters, optimizing the network, or initiating necessary operations to ensure the network remains secure.