基于贝叶斯联合博弈的无线网络路由算法

Wireless Network Routing Algorithm based on Bayesian Joint Game Theory

在移动自组织网络中节点自私性难辨,而自私节点不尽全力转发数据会降低网络的可靠性。基于此,将联合博弈论建立在动态贝叶斯框架下,形成了一种基于贝叶斯联合博弈的数据传输算法。算法首先根据各节点的信念更新值发现不良节点;然后根据不良节点预估网络环境,计算各个预估环境的联合信念概率并归一化为联合体存在概率,计算各联合体下各节点的安全效益值,得到所对应的合约;接着运用先验中期拒绝找到贝叶斯稳态合约;最后通过设置安全容量计算权值的方式惩处不良节点,保证联合体内各节点安全容量和收益最大化。仿真结果表明,与其他两种算法相比,所提算法不仅有较少的路由延迟和控制开销比,还有较高的数据包投递率,有效降低了不良节点对网络的不利影响。

In self-organizing networks,nodes are less self-identical,while self-serving nodes do not do their best to forward data to reduce the reliability of the network.Based on this,the joint game theory is established in the dynamic Bayesian framework,and a data transmission algorithm based on Bayesian game is formed.The algorithm first finds out the bad nodes according to the beliefs of each node,and then calculates the joint belief probability of each predicated environment and normalizes the joint existence probability according to the prediction of the network environment by the bad nodes.Next,we calculate the security benefit values of each joint under each joint,and obtain the corresponding contract.Then we use a priori medium to refuse to find the Bayesian steady state contract.Finally,the bad nodes are punished by setting the security capacity to calculate the weights,to ensure that the security capacity and benefits of each node in the federation are maximized and the data is effectively forwarded.The simulation results show that,compared with the other two algorithms,the proposed algorithm not only has less routing delay and control overhead,but also has a higher packet delivery rate,which effectively reduces the adverse effects of the bad nodes on the network.