Abstract
The selfish behaviors of nodes (or selfish nodes) cause packet loss, network congestion or even void regions in real-time wireless sensor networks, which greatly decrease the network performance. Previous methods have focused on detecting selfish nodes or avoiding selfish behavior, but little attention has been paid to regulating selfish behavior. In this paper, a Game Theory-based Real-time & Fault-tolerant (GTRF) routing protocol is proposed. GTRF is composed of two stages. In the first stage, a game theory model named VA is developed to regulate nodes’ behaviors and meanwhile balance energy cost. In the second stage, a jumping transmission method is adopted, which ensures that real-time packets can be successfully delivered to the sink before a specific deadline. We prove that GTRF theoretically meets real-time requirements with low energy cost. Finally, extensive simulations are conducted to demonstrate the performance of our scheme. Simulation results show that GTRF not only balances the energy cost of the network, but also prolongs network lifetime.
Highlights
Wireless sensor networks (WSNs) are deployed in a variety of environments for reporting periodical events [1,2]
We propose a game theory selfish node prevention protocol for real-time WSNs, in the following we will respectively introduce the state of the art of real-time routing protocols and game theory in the WSN area
Since a real-time wireless sensor network is required to have fault-tolerant properties, we propose the following methods to mark whether a node is a faulty node
Summary
Wireless sensor networks (WSNs) are deployed in a variety of environments for reporting periodical events [1,2]. The side effect of selfish nodes is terrible, especially in real-time transmission. The VA model is designed to designate cluster heads, achieve fault tolerance, balance the energy cost and regulate the behaviors of cluster members. The jumping transmission model is developed to guarantee the real-time transmission and regulate the behaviors of cluster heads. It can avoid the influences of void regions. (2) To regulate nodes’ behaviors within clusters, we develop a VA model, which forces selfish nodes to spontaneously behave as normal nodes so as to maximize their profits. (3) To control nodes’ behaviors among cluster heads, we introduce a jumping transmission model. We proved that behaving as normal nodes is a Nash Equilibrium strategy for selfish cluster heads.
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