GIR: An Opportunistic Network Routing Algorithm Based on Game Theory

Abstract

A large number of routing algorithms in Opportunistic Networks are based on the assumption that nodes are free to help other nodes forward messages. However, when the Opportunistic Network is applied to an urban environment, the nodes will have certain social attributes. In many cases, a node can decide whether to execute the routing policy or not. Due to the limited resources and poor social relationships, nodes may be unwilling to forward messages from other nodes and have strong motivation to implement selfish policies. As a result, increased network latency reduces message delivery rates and affects the overall network performance. In order to solve this problem, we propose a perceptual routing protocol to promote node cooperation from the perspective of game theory. Specifically, We introduce the concept of virtual currency and construct a price function, and nodes can obtain a certain virtual currency through cooperation. In the process of message forwarding, we consider the change of link degree and energy of node (the energy exists in the form of electricity in this paper), and use them as factors of the trading node quotation. The trading node finally makes it through the multiple rounds of bargaining games, so that the proposed game between both sides reaches the Nash equilibrium. Experiments show that the algorithm outperforms Epidemic, EPSR, MINEIRO and ICRP algorithms in terms of delivery rate, average latency and energy consumption. According to the simulation experiments, the average delivery ratio of GIR algorithm is 0.68, which is 13% higher than that of the epidemic algorithm. In terms of average delay, 7% is better than ICRP algorithm. INDEX TERMS Cooperation, Routing algorithm, Nash equilibrium, Selfish.