An efficient probabilistic routing scheme based on game theory in opportunistic networks
Xueyang Qin, Xiaoming Wang, Liang Wang, Liang Wang, Yaguang Lin, Xinyan Wang, Xinyan Wang · Computer Networks · 2018
Routing is one of the most challenging problems in opportunistic networks (OppNets) because of the intermittence of the network connection. To address the issue, many routing schemes have been proposed, however, most of them assume that nodes are willing to forward messages for others. In fact, due to limited resources and poor social relations, nodes in OppNets may be selfish and not reluctant to participate in message forwarding. To tackle this issue, in this paper, we propose a Probabilistic Routing scheme based on Game Theory (PRGT) to stimulate cooperation among selfish nodes. Firstly, we introduce virtual money to buy the message for gaining more profits. Then, according to the historical meeting records among different nodes, we establish a Markov-based probability prediction model, in which the message carrier selects a node with higher probability of encountering the destination node as the relay node. Finally, a game theory approach is employed to simulate trading price for message forwarding. The simulation results demonstrate that our proposed routing scheme can effectively improve the delivery rate of messages and reduce network latency.