【摘要】 大规模无线自组织网络存在的自私节点或者恶意节点引起网络性能的降低,甚至导致网络不能正常工作,在网络层数据包路由过程中避免这些节点,对自私节点或者恶意节点进行隔离能够有效提高网络的安全性。本文提出一种安全感知的无线自组织网络路由优化算法SARO,SARO算法是一种改进的蚁群算法,该算法基于节点信任度统计参数建立安全感知的启发因子方程以及信息素更新方程,使数据包在路由过程中选择安全性较高的路径进行数据的路由转发,可对自私节点和恶意节点进行隔离,从而增强网络安全性,提高网络服务质量。仿真实验结果表明,SARO算法能够明显提高网络吞吐量,降低传输延迟,降低不良侦听率,具有较高的实用价值。更多还原

【Abstract】 Selfish nodes and malicious nodes in large-scale ad hoc networks lead to poor network performance and even paralyze the network.How to isolate these nodes from routing path is very important to improve the network security.A security aware routing optimization algorithm named SARO is proposed to achieve this goal.SARO is an improvement to ant optimization.It utilizes reputations from a reputation system to derive the pheromone trail refresh process and visible functions.Abnormal nodes are discarded from routing tables and packets are routed along paths with least abnormal nodes.SARO is a security enhancement to routing protocols,which can both improve security of network and enhance the network performance.更多还原