Collaboration Of Sensor Nodes Research Articles

Swarm Intelligence-Optimized Energy Management for Prolonging the Lifetime of Wireless Sensor Networks

Recent technological and industrial progress has enabled the development of small, high-performing, energy-saving, affordable sensor nodes that possess the potential to adapt, be self-aware, and self-organize. These nodes are designed for versatile communications applications. Sensor networks for sustainable development focus on the ways in which sensor network technology can enhance social development and improve living standards without causing harm to the environment or depleting natural resources. Wireless sensor networks (WSNs) offer undeniable benefits in various fields, including the military, healthcare, traffic monitoring, and remote image sensing. Given the constraints of sensor networks, varying degrees of security are necessary for these critical applications, posing difficulties in the implementation of conventional algorithms. The issue of security has emerged as a primary concern in the context of IoT and smart city applications. Sensor networks are often regarded as the fundamental building blocks of IoTs and smart cities. The WSN encompasses a routing algorithm, network strength, packet loss, energy loss, and various other intricate considerations. The WSN also addresses intricate matters such as energy usage, a proficient approach for picking cluster heads, and various other concerns. The recent growth of Wireless Sensor Networks (WSNs) has made it increasingly difficult to ensure the trustworthiness and reliability of data due to the distinct features and limitations of nodes. Hostile nodes can easily damage the integrity of the network by inserting fake and malicious data, as well as launching internal attacks. Trust-based security is employed to detect and identify rogue nodes, providing a robust and adaptable protection mechanism. Trust evaluation models are crucial security-enhancement mechanisms that enhance the reliability and collaboration of sensor nodes in wireless sensor networks. This study recommends the use of DFA UTrust, a unique trust technique, to effectively satisfy the security requirements of WSNs.

A secure and dependable trust assessment (SDTS) scheme for industrial communication networks

Due to tamper-resistant sensor nodes and wireless media, Industrial Wireless Sensor Networks (WSNs) are susceptible to various security threats that severely affect industrial/business applications. The survival of sensor networks is highly dependent on the flourishing collaboration of sensor nodes. Trust management schemes seem to be realistic and promising techniques to improve security as well as cooperation (dependability) among sensor nodes by estimating the trust level (score) of individual sensor nodes. This research paper presents a well-organized and motivating secure, dependable trust assessment (SDTS) scheme for industrial WSNs to cope with unexpected behavior such as an on–off attack, bad-mouthing attack, garnished attack, etc., by employing robust trust evaluation components based on success ratio and node misbehaviour. SDTS incorporates an interesting trust evaluation function in which the trust range can be adjusted in accordance with the application requirement. SDTS include direct communication trust, indirect communication trust, data trust, and misbehavior-based trust to defend the multiple internal attacks. SDTS works according to the behavior of nodes, i.e., whether the sensor nodes are interacting frequently or not. Moreover, abnormal attenuation and dynamic slide lengths are incorporated in the proposed model (SDTS) to deal with various natural calamities and internal attacks. SDTS is compared against three recent state-of-the-art methods and found efficient in terms of ease of trust assessment, false-positive rate (2.5%), false-negative rate (2%), attack detection rate (90%), detection accuracy (91%), average energy consumption (0.40 J), and throughput (108 Kbps) under the load of 500 sensor nodes with 50% malicious nodes. Investigational results exhibit the potency of the proposed scheme.

Strip-based deployment with cooperative communication to achieve connectivity and information coverage in wireless sensor networks

Coverage and connectivity in wireless sensor network have been studied extensively in existing research works with physical and information coverage. The optimal deployment to achieve both information coverage and connectivity, on arbitrary values of the ratio of rc and rs, has been studied in previous work; meanwhile, the extended strip-based deployment based on information coverage is also studied. Either information coverage or cooperative communication could exploit collaboration of sensor nodes to improve the efficiency of deployment, while how good is strip-based deployment with both information coverage and cooperative communication is worth to be measured when the value of rc/ rs is varied. In this article, the relationship between the density of sensors needed to achieve physical or information coverage and connectivity and the variety of rc/ rs is derived in closed form for strip-based deployment of wireless sensor networks with cooperative communication. Then, a summary of different combinations of coverage and connectivity is provided, that physical or information coverage with or without cooperative communication could be employed to achieve full coverage and connectivity for strip-based deployment. Finally, some new strategy could be proposed based on the fusion of physical and information coverage to improve strip-based deployment. Some numerical results are provided to show the efficiency of all schemes to help researchers design more effective deployment schemes.

Energy‐aware cooperative and distributed channel estimation schemes for wireless sensor networks

SummaryIt is a fact that energy consumption is a key issue in wireless sensor networks. In order to improve the energy efficiency of network utilization, distributed power control methods are advocated. However, the sensors are deployed randomly, which results in the channel gains that are difficult to be obtained; thus, how to estimate channel gains accurately to increase node communication efficiency and reduce energy consumption is the motivation of our work. In this paper, a cooperative and distributed algorithm based on diffusion least mean square (LMS) is firstly proposed to estimate channel gain by utilizing the equality and collaboration of sensor nodes. Its objective is to enhance the accuracy and convergence of the estimation process. Because the presented globe‐based scheme is unrealistic for practical utilization, two distributed estimation algorithms are investigated for different network scenarios, namely, exchange diffusion combine LMS and exchange combine diffusion LMS. Simulation results demonstrate the effectiveness of our methods. Copyright © 2015 John Wiley & Sons, Ltd.