scholarly journals Study on Selfish Node Incentive Mechanism with a Forward Game Node in Wireless Sensor Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Mohammed Ahmed Ahmed Al-Jaoufi ◽  
Yun Liu ◽  
Zhen-jiang Zhang ◽  
Lorna Uden

In a wireless sensor network, some nodes may act selfishly and noncooperatively, such as not forwarding packets, in response to their own limited resources. If most of the nodes in a network exhibit this selfish behavior, the entire network will be paralyzed, and it will not be able to provide normal service. This paper considers implementing the idea of evolutionary game theory into the nodes of wireless sensor networks to effectively improve the reliability and stability of the networks. We present a new model for the selfish node incentive mechanism with a forward game node for wireless sensor networks, and we discuss applications of the replicator dynamics mechanism to analyze evolutionary trends of trust relationships among nodes. We analyzed our approach theoretically and conducted simulations based on the idea of evolutionary game theory. The results of the simulation indicated that a wireless sensor network that uses the incentive mechanism can forward packets well while resisting any slight variations. Thus, the stability and reliability of wireless sensor networks are improved. We conducted numerical experiments, and the results verified our conclusions based on the theoretical analysis.

2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Yu Song ◽  
Zhigui Liu ◽  
Xiaoli He

Compared with traditional networks, WSNs have more limited resources such as energy, communication, computing, and storage. The problem of how to achieve energy saving, extend network life cycle, and improve network performance under these limited resources has always been an issue of great interest in WSN research. However, existing protocols do not consider that sensor nodes within the BS threshold may not be clustered. These nodes can directly transmit data to the BS. This simplifies the cluster routing process of the entire WSN and saves more energy. This paper introduces an efficient, and energy-efficient, clustering and equalization routing protocol called the PSOLB-EGT protocol. This protocol introduces a new approach by combining improved particle swarm optimization (PSO) and evolutionary game theory (EGT) algorithms to address the problem of maximizing the network lifetime. The operation of the wireless sensor network is divided into an initialization phase and a data transmission phase. In the initialization phase of the wireless sensor network, the improved PSO algorithm is used to establish clusters and select CHs in areas other than the BS threshold. Entering the data transmission phase, we analyze this problem from the perspective of game theory. We use improved noncooperative evolutionary game theory to build models to solve the problem of the energy waste caused by routing congestion. The proposed PSOLB-EGT protocol is intensively experimented with a number of topologies in various network scenarios, and the results are compared with the well-known cluster-based routing protocols that include the swarm intelligence-based protocols. The obtained results prove that the proposed protocol has increased 9%, 8%, and 5% compared with the ABC-SD protocol in terms of network life, network coverage, and amount of data transmitted, respectively.


Game Theory ◽  
2017 ◽  
pp. 337-352
Author(s):  
Mehran Asadi ◽  
Afrand Agah ◽  
Christopher Zimmerman

In this chapter, the authors examine the impacts of applying game theory on the network throughput, network voltage loss, and accuracy of malicious node detection in wireless sensor networks. Nodes in a wireless sensor network use our proposed protocol when deciding whether or not to forward packets they receive from other sensors in order to conserve power. Wireless sensor network nodes achieve this by optimizing their decision-making based on a framework using game theory. Defining a suitable cost and profit for routing and forwarding incoming packets and keeping a history of past behaviors of non-cooperating nodes gradually forces malicious nodes out of the wireless sensor network.In this chapter, the authors examine the impacts of applying game theory on the network throughput, network voltage loss, and accuracy of malicious node detection in wireless sensor networks. Nodes in a wireless sensor network use our proposed protocol when deciding whether or not to forward packets they receive from other sensors in order to conserve power. Wireless sensor network nodes achieve this by optimizing their decision-making based on a framework using game theory. Defining a suitable cost and profit for routing and forwarding incoming packets and keeping a history of past behaviors of non-cooperating nodes gradually forces malicious nodes out of the wireless sensor network.


Author(s):  
Mehran Asadi ◽  
Afrand Agah ◽  
Christopher Zimmerman

In this chapter, the authors examine the impacts of applying game theory on the network throughput, network voltage loss, and accuracy of malicious node detection in wireless sensor networks. Nodes in a wireless sensor network use our proposed protocol when deciding whether or not to forward packets they receive from other sensors in order to conserve power. Wireless sensor network nodes achieve this by optimizing their decision-making based on a framework using game theory. Defining a suitable cost and profit for routing and forwarding incoming packets and keeping a history of past behaviors of non-cooperating nodes gradually forces malicious nodes out of the wireless sensor network.In this chapter, the authors examine the impacts of applying game theory on the network throughput, network voltage loss, and accuracy of malicious node detection in wireless sensor networks. Nodes in a wireless sensor network use our proposed protocol when deciding whether or not to forward packets they receive from other sensors in order to conserve power. Wireless sensor network nodes achieve this by optimizing their decision-making based on a framework using game theory. Defining a suitable cost and profit for routing and forwarding incoming packets and keeping a history of past behaviors of non-cooperating nodes gradually forces malicious nodes out of the wireless sensor network.


2018 ◽  
Vol 7 (2.26) ◽  
pp. 25
Author(s):  
E Ramya ◽  
R Gobinath

Data mining plays an important role in analysis of data in modern sensor networks. A sensor network is greatly constrained by the various challenges facing a modern Wireless Sensor Network. This survey paper focuses on basic idea about the algorithms and measurements taken by the Researchers in the area of Wireless Sensor Network with Health Care. This survey also catego-ries various constraints in Wireless Body Area Sensor Networks data and finds the best suitable techniques for analysing the Sensor Data. Due to resource constraints and dynamic topology, the quality of service is facing a challenging issue in Wireless Sensor Networks. In this paper, we review the quality of service parameters with respect to protocols, algorithms and Simulations. 


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