Description:[001] The present invention relates to the field of Internet of Things (IoT) technology, with a specific focus on enhancing the performance and energy efficiency of IoT devices that utilize Wi-Fi for communication. More specifically, the invention addresses the challenges of power consumption, communication quality, and security management in IoT networks, particularly in resource-constrained environments.
[002] This invention also falls within the domains of wireless communication, machine learning, and network security, as it introduces a novel algorithm designed to optimize the use of available resources in IoT devices by monitoring network conditions and adjusting device behavior accordingly. The algorithm leverages machine learning techniques, specifically the Random Forest classifier, to predict communication quality and adjust power consumption modes dynamically, thus extending the operational life of IoT devices.
[003] Additionally, the invention incorporates advancements in Identity Management Systems (IdM) to provide secure authentication and access control for IoT devices. The modified IdM system ensures the secure transmission of data between IoT devices and the network, addressing key concerns related to cybersecurity in IoT environments. The invention is particularly suited for use in networks where multiple IoT devices are simultaneously connected, such as smart cities, industrial automation, healthcare, and home automation systems.
[004] In summary, this invention lies at the intersection of IoT performance optimization, power management, and security, aiming to provide a comprehensive solution for improving the efficiency and safety of IoT systems in Wi-Fi networks.
BACKGROUND OF THE INVENTION
[005] The rapid proliferation of the Internet of Things (IoT) has introduced a wide variety of devices into interconnected networks, significantly influencing modern communication and automation systems. These IoT devices, often deployed in diverse environments and applications such as smart homes, healthcare, industrial automation, and smart cities, typically rely on wireless communication technologies like Wi-Fi for data transmission.
[006] Despite their widespread use, IoT devices are constrained by limited power resources, small form factors, and low computational capacities. These limitations impose significant challenges, particularly in managing power consumption, maintaining high network performance, and ensuring robust security across the network.
[007] One of the primary concerns for IoT devices utilizing Wi-Fi is power consumption. Most IoT devices operate on battery power and require long operational lifespans, making efficient energy management crucial. Conventional power-saving modes, such as those in Wi-Fi communication standards, often fail to address the dynamic nature of network traffic and the varying quality of wireless connections.
[008] As a result, IoT devices either consume excessive power when network conditions are poor or experience delays when they enter extended sleep modes, particularly in time-sensitive applications. This inefficiency leads to reduced device lifetime, which is a critical drawback in deployments where frequent maintenance or battery replacement is not feasible.
[009] Another challenge associated with IoT networks is maintaining a high Quality of Service (QoS). IoT devices must balance multiple performance parameters such as throughput, latency, and packet loss, especially in environments where multiple devices contend for limited wireless bandwidth. In many cases, congested Wi-Fi networks experience increased latency and reduced throughput, which can critically impact the performance of IoT applications that demand real-time data transmission, such as in industrial control systems or healthcare monitoring. Traditional power-saving algorithms tend to exacerbate these issues by prioritizing energy efficiency at the expense of communication quality.
[010] In addition to performance concerns, the security of IoT networks is a growing area of focus. IoT devices, due to their resource-constrained nature, are particularly vulnerable to security threats such as unauthorized access, data breaches, and malicious attacks. Standard authentication and authorization protocols used in traditional networks are often too resource-intensive for IoT devices, making it difficult to ensure both secure communication and efficient performance. The absence of a tailored Identity Management (IdM) system for IoT networks further complicates the issue, as IoT devices require lightweight yet effective security mechanisms that can accommodate their limited processing and power capabilities.
[011] The existing methods and systems for managing the performance and security of IoT devices in Wi-Fi environments have proven insufficient in addressing these critical challenges. Current solutions do not provide an optimal balance between energy efficiency, communication quality, and security, leaving IoT devices either prone to excessive power consumption or vulnerable to security threats. Furthermore, traditional approaches do not adequately account for the diverse and dynamic conditions in which IoT devices operate, particularly in dense, congested network environments.
[012] There is, therefore, a pressing need for an innovative method and system that can simultaneously improve the energy efficiency, communication performance, and security of IoT devices operating in Wi-Fi networks. Such a solution would enable IoT devices to conserve power without compromising their communication quality or security, thereby extending their operational lifetimes and enhancing their overall effectiveness in various applications.
[013] This invention seeks to address these challenges by proposing an algorithm that leverages machine learning for network performance prediction, combined with an enhanced Identity Management system to ensure secure and efficient operation of IoT devices in Wi-Fi environments.
SUMMARY OF THE INVENTION
[014] The present invention introduces a novel method and system designed to improve the performance and efficiency of Internet of Things (IoT) devices that utilize Wi-Fi for communication. The invention addresses two critical challenges faced by IoT devices: limited power resources and the need for reliable network communication, particularly in environments with a high density of connected devices. Additionally, the invention integrates enhanced security measures to ensure that the communication between IoT devices and networks is protected from unauthorized access. These improvements are achieved through the proposed IoT-QoS algorithm, which optimizes resource management and network performance without sacrificing device security.
[015] ne key aspect of the invention is its approach to energy management in IoT devices. The IoT-QoS algorithm continuously monitors the energy levels of the device and the quality of network communication based on metrics such as the Received Signal Strength Indicator (RSSI) and Packet Delivery Ratio (PDR). Using machine learning techniques, specifically the Random Forest classifier, the algorithm predicts the quality of the network connection. When the communication quality is poor or the device’s energy level drops below a specified threshold, the algorithm dynamically adjusts the device’s power mode by transitioning the wireless card into sleep mode. This sleep mode conserves energy, particularly in environments with frequent network congestion, without significantly affecting the performance of time-sensitive applications.
[016] In addition to energy management, the invention addresses the security needs of IoT devices by integrating a modified Identity Management (IdM) system. This system enhances both authentication and access control, ensuring that only authorized users and devices can access the IoT network. The IdM system employs two levels of encryption to secure communications: a Key Encryption Key (KEK) to encrypt the session content and a Master Key Key (MKK) to encrypt the KEK itself. This layered encryption scheme protects data transmitted over the network and reduces the computational load on the IoT device by offloading privacy policies to external servers.
[017] The IoT-QoS algorithm also incorporates measures to ensure that time-sensitive data is transmitted with minimal delay. By implementing a priority-based data transmission system, the algorithm assigns higher priority to critical data, enabling IoT devices to gain quicker access to the wireless medium. This reduces latency even in congested network environments, ensuring that performance standards are met for applications that require real-time responsiveness.
[018] Overall, the invention provides a comprehensive solution to enhance the performance, efficiency, and security of IoT devices operating in Wi-Fi environments. It effectively balances the need for low power consumption with the demand for high-quality service and secure communication, making it particularly useful for IoT devices with limited resources in dense network environments.
BRIEF DESCRIPTION OF THE DRAWINGS
[019] The accompanying figures included herein, and which form parts of the present invention, illustrate embodiments of the present invention, and work together with the present invention to illustrate the principles of the invention Figures:
[020] Figure 1 - illustrates the essential components of the Identity Management (IdM) system used in IoT devices, Figure 2 - illustrates the working mechanism of the proposed IoT-QoS algorithm and Figure 3 - illustrates a graph represents the energy consumption of IoT devices as the number of devices and sleep duration increase.
[021] Figure 4 - illustrates that IoT devices employing the proposed algorithm experience lower response times, even under heavy network load, thanks to its priority access scheme and optimized packet aggregation, Figure 5 - this graph displays the network delay as the number of IoT devices increases. It contrasts the delay experienced by devices utilizing the IoT-QoS algorithm versus those using conventional approaches. and Figure 6 - this graph depicts the throughput (data transfer rate) of the IoT devices as the number of connected devices grows.
DETAILED DESCRIPTION OF THE INVENTION
[022] The present invention provides a novel method and system, referred to as the IoT-QoS Algorithm, designed to enhance the performance of Internet of Things (IoT) devices operating in Wi-Fi networks. The invention specifically addresses key challenges related to power consumption, communication quality, and security, which are prevalent in traditional IoT systems. This dual-pronged approach—combining advanced resource management with enhanced security mechanisms—ensures that IoT devices maintain high performance even under constrained resources such as limited battery life and bandwidth.
Power and Resource Management Mechanism
[023] One of the critical components of this invention is the power and resource management mechanism, which optimizes the energy consumption of IoT devices while preserving the Quality of Service (QoS) parameters. IoT devices are often battery-powered and operate in environments with high wireless congestion, where poor communication quality can lead to excessive energy use. To overcome these challenges, the invention employs a machine learning-based system that dynamically predicts communication quality and adjusts the device’s power modes accordingly.
[024] The communication quality is assessed using two key metrics: Received Signal Strength Indicator (RSSI) and Packet Delivery Ratio (PDR). The RSSI measures the power of the received signal, providing an indicator of the connection quality between the IoT device and the Wi-Fi access point. The PDR represents the ratio of successfully delivered packets over the total packets sent, which further indicates the network performance. These metrics are processed through a Random Forest classifier that predicts whether the communication quality is adequate for data transmission or if the device should enter a power-saving mode.
[025] When the algorithm detects poor communication quality—either through low RSSI or a low PDR—the IoT device’s wireless card enters a sleep mode to conserve energy. The device remains in this low-power state until the communication quality improves or there is a critical need to wake up for data transmission. This intelligent management of the wireless card allows the IoT device to significantly extend its battery life without compromising its ability to communicate when necessary. The sleep intervals are dynamically adjusted based on network conditions, with the system ensuring that devices in poor network environments stay in sleep mode for extended periods to optimize power usage.
[026] The power consumption model for the IoT devices is based on the following equation:

Where:
• are the power consumption rates during transmitting, receiving, idle, and sleeping modes, respectively.
• are the durations spent in each of these modes.
• represents the total operation time.
[027] The above model ensures that the wireless card operates in a highly efficient manner, with its operating mode being dynamically adjusted based on real-time communication quality predictions. This significantly reduces the energy consumption of IoT devices, particularly in congested networks where the wireless medium is often contested by multiple devices.
Communication Quality Prediction
[028] The IoT-QoS Algorithm relies heavily on machine learning techniques to predict the quality of network communication. The Random Forest classifier is used to analyze the RSSI and PDR values and make real-time decisions about the communication quality. If the predicted communication quality is poor, the wireless card is transitioned into a low-power sleep state. However, if the quality is deemed sufficient, the wireless card stays active and ready for data transmission.
[029] This dynamic adjustment of the wireless card’s power mode based on communication quality predictions allows the IoT device to avoid unnecessary power consumption during periods of poor connection. For instance, in cases where the network is heavily congested, the system minimizes the power spent in contention for the wireless medium, allowing the device to conserve battery life until the network conditions improve.
[030] In addition, the algorithm distinguishes between different types of data, with time-sensitive data being given priority. For time-sensitive applications, the system minimizes the sleep intervals and allows for faster data transmission by granting the IoT device higher access priority to the wireless medium. This is particularly useful in applications like industrial monitoring, where delays in data transmission could result in critical system failures.
Security Mechanism
[031] The second key component of the invention is the modified Identity Management (IdM) system, which is designed to enhance the security of IoT devices. Traditional IoT devices face significant challenges when it comes to securing communications, as they often lack the processing power to implement robust security measures. The invention addresses this by introducing a lightweight IdM system that ensures both authentication and access authorization for IoT devices in the network.
[032] The IdM system in this invention is modified to include contextual parameters such as user identity, role, activities, physical location (via GPS), and virtual location (via IP address). These parameters help create a more secure environment by controlling access based on the device's context. The system also incorporates two encryption levels:
1. Key Encryption Key (KEK): This key is used to encrypt the content of the messages exchanged during communication sessions.
2. Master Key Key (MKK): This key encrypts the KEK itself, providing an additional layer of security.
[033] The encryption process follows the ANSI X.9.17 standard for managing the distribution of keys, ensuring that all communication is secure without imposing significant computational overhead on the IoT device. By offloading the privacy policy and key management processes to external servers, the system minimizes the burden on the resource-constrained IoT devices, allowing them to focus on their primary functions.
[034] The modified IdM system also supports Single Sign-On (SSO), enabling IoT devices to authenticate once and maintain secure communication throughout the session without requiring re-authentication for every transaction. This is particularly beneficial for IoT devices that frequently communicate over the network, as it reduces the overhead associated with repeated authentication processes.
Data Transmission and Aggregation
[035] The IoT-QoS Algorithm further optimizes the performance of IoT devices by implementing a data aggregation mechanism that reduces the amount of data transmitted over the network. When multiple packets of data are ready for transmission, the algorithm aggregates these packets into a single transmission, reducing the number of transmission operations and thus saving power.
[036] Moreover, the algorithm prioritizes time-sensitive data and ensures that it is transmitted with minimal delay. The priority-based Medium Access Control (MAC) protocol ensures that IoT devices using the IoT-QoS Algorithm are granted higher priority in accessing the wireless medium. This is achieved by assigning a shorter back-off time to these devices, allowing them to transmit data more quickly than traditional devices that follow the standard binary exponential back-off protocol. This method significantly reduces the transmission delay for critical data, making the system suitable for applications where real-time data transmission is essential.
[037] In summary, the IoT-QoS Algorithm presents an innovative approach to managing the limited resources of IoT devices while ensuring high-quality communication and robust security. By utilizing machine learning techniques to predict communication quality and intelligently adjust power modes, the invention significantly extends the battery life of IoT devices. Simultaneously, the modified IdM system provides a secure and efficient authentication and authorization process, safeguarding the network without imposing heavy computational demands on the IoT devices. This invention is particularly advantageous in environments with high network congestion and time-sensitive data transmission requirements, making it a critical advancement in the field of IoT technology.
[038] The introduction of a modified Identity Management (IdM) system ensures that security is not sacrificed for efficiency. By integrating advanced encryption techniques and contextual information in authentication and authorization processes, the system provides enhanced protection for IoT devices in an increasingly vulnerable digital landscape. This two-level encryption approach offers a secure and reliable method for managing sensitive data, making the IoT-QoS algorithm particularly suited for applications where security and privacy are paramount.
[039] The results from the simulation models further affirm the effectiveness of the IoT-QoS algorithm. Devices utilizing this algorithm outperformed traditional methods in terms of lower energy consumption, reduced latency, and improved throughput, particularly under high network congestion. The algorithm's ability to prioritize time-sensitive data transmissions ensures that critical applications can function seamlessly, even in challenging network conditions.
[040] In light of these findings, the IoT-QoS algorithm presents a valuable solution for improving the efficiency and security of IoT devices. Its applicability to a wide range of IoT use cases makes it a promising advancement in the field. Future work can explore the integration of emerging technologies such as blockchain and Software-Defined Networks (SDN) to further enhance the security and scalability of IoT systems. Ultimately, this approach sets a new standard for managing the complex balance between energy conservation, performance, and security in IoT networks.
, Claims:1. A method for improving the performance of Internet of Things (IoT) devices in Wi-Fi networks by predicting network communication quality and adjusting power consumption based on said prediction.
2. A system for optimizing power consumption in IoT devices using Wi-Fi communication, wherein a machine learning model monitors real-time network conditions and adjusts device power modes accordingly.
3. A method for reducing power consumption in IoT devices by dynamically switching the wireless card to a sleep mode when communication quality drops below a predefined threshold.
4. A system for enhancing Quality of Service (QoS) in IoT devices by utilizing machine learning techniques to predict communication quality based on Received Signal Strength Indicator (RSSI) and Packet Delivery Ratio (PDR).
5. A method for prioritizing network access for IoT devices based on the type of data being transmitted, where time-sensitive data is given higher access priority to minimize delays.
6. A method for reducing latency in IoT devices by adjusting transmission intervals and sleep durations based on real-time analysis of network traffic and communication quality.
7. A system for secure communication in IoT networks that employs a modified Identity Management (IdM) system for authentication and access authorization, utilizing contextual data to determine access permissions.
8. A method for encrypting data in IoT devices using a double encryption scheme, where two keys are used to secure communication: one for encrypting the session content and another for encrypting the first key.
9. A system for managing the energy consumption of IoT devices by integrating a Random Forest classifier to predict network communication quality and trigger power-saving modes.
10. A method for extending the operational lifespan of IoT devices by adjusting power modes, managing sleep intervals, and predicting communication quality based on real-time network conditions.