差额奖惩机制的WSNs节点信任演化模型

摘要

Aiming at issue of trust decisions among WSNs nodes which can affect WSNs instability,introduce an imbalance rewards and penalties mechanism.The unreliable factors exist in the real networks,introduce rate of the package loss,built on evolutionary trust model of WSNs nodes based on imbalance rewards and penalties mechanism.By the evolutionary trust model,deduce the nodes state of interaction.In the end,through the experimental analysis on various changes of nodes in the selection strategy,effect of the imbalance rewards and penalties mechanism on the evolution of the convergence time.Through the experiment,the effect of the imbalance rewards and penalties mechanism is verified by the results of WSNs,which is a kind of node's initial trust strategy.The imbalance rewards and penalties mechanism for the evolution of the slow convergence in the model mechanism,and can reduce the initial nodes selection strategy trust ratio,which provides the theory basis for the design WSNs trust mechanism.%针对目前无线传感器网络(WSNs)节点间信任决策导致网络不稳定的问题,引入了差额奖惩机制.在实际中,网络存在不可靠因素,加入丢包率,构建基于奖惩机制的信任演化模型.通过信任演化模型,推导出节点交互时的状态.通过实验分析了节点在选择策略时的各种变化以及差额奖惩机制对演化收敛时间起到的作用,通过实验验证了差额奖惩机制对WSNs中的善意节点最终收敛到信任策略所需节点初始信任策略比例数的要求所起到的作用.差额奖惩机制弥补了在无差额奖惩机制模型中演化收敛速度慢的问题,并且降低初始节点选择信任策略比例数的要求,为WSNs信任机制的设计提供了理论基础.