基于多方议价博弈的机会网络高吞吐量低开销概率路由算法

High-throughput and low-overhead probabilistic routing based on multi-player bargaining game for opportunistic networks

针对含自私节点的机会网络中现有基于议价博弈的概率路由算法存在的消息单向传递影响转发概率提高、依赖虚拟货币进行交易削弱节点购买力以及消息交易过程有冗余交互的问题,提出一种基于多方议价博弈的高吞吐量低开销概率路由算法——HLPR-MG。HLPR-MG算法通过将节点两两博弈扩展为多方博弈以加快消息转发概率的提升,引入"以物易物"方式增强节点购买力,并且改进现有交互机制以减少博弈次数,从而达到提高网络吞吐量的和减小控制开销的效果。理论分析验证了HLPR-MG算法设计的有效性。仿真结果表明,与基于议价博弈的现有典型路由算法GSCP和BG相比,HLPR-MG算法的吞吐量和消息传送成功率至少提高了3.63%,而控制开销和平均端到端消息时延则分别降低超17.76%和4.03%。

To address the problems existing in the present probabilistic routing based on bargaining games, including unidirectional transmission of messages degrades the success ratio, depending on the virtual money decreases the purchasing power of nodes, and redundancy exists in the interaction process of messages, an routing algorithm based on multi-player bargaining game for opportunistic networks, HLPR-MG, was proposed. Through extending the two-player game to a multi-player bargaining game, introducing the barter trade to enhance purchasing power of nodes, and improving the existing interaction mechanism to reduce the times of game, proposed algorithm achieves the effect of increasing network throughput and decreasing control overhead. Theoretical analysis verifies the effectiveness of HLPR-MG, and simulation results show that HLPR-MG improves the network throughput and success ratio at least 3.63%, and reduces the control overhead and average end-to-end delay by more than 17.76% and 4.03%, respectively, as compared to the classical GSCP and BG algorithms.