传感器网络中基于模糊理论和蚁群的路由算法

ROUTING ALGORITHM IN WIRELESS SENSOR NETWORK BASED ON FUZZY THEORY AND ANT COLONY

在蚁群算法基础上引入模糊理论的概念,提出基于模糊理论和蚁群BFTAC(Based on Fuzzy Theory and Ant Colony)的路由算法。BFTAC算法前向蚂蚁在路径探索中,通过模糊综合评判法选择下一跳节点;信息素更新过程中,成功到达汇聚节点转化的后向蚂蚁根据对应的前向蚂蚁携带的网络信息增强路径信息素,而未成功到达的要削弱信息素;数据传输时,采用低能量节点休眠工作机制,以此达到均衡网络节点的能耗的目的。仿真实验表明,与基于能量有效蚁群算法(EEABR)进行比较,相同条件下BFTAC算法有效地减少了网络平均能量消耗,增强了网络节点的存活率。

Based on ant colony algorithm we introduced the concept of fuzzy theory,and proposed a routing algorithm which is based on fuzzy theory and ant colony. In the algorithm,the forward ant selects the next hop node using fuzzy comprehensive evaluation method when exploring the path. In the update process of pheromone,the backward ants whom successfully reach the aggregation node and converted will enhance the path pheromones according to the network information carried by the forward ants,while whom failed to reach have to weaken the pheromone. In data transmission the algorithm uses low energy nodes dormant working mechanism to achieve the goal of balancing the energy consumption of network nodes. Simulation results showed that comparing with energy-efficient ant-based routing（ EEABR） algorithm,this algorithm effectively reduced the average energy consumption of the network and enhanced the survival of network nodes under the same conditions.