Abstract: In order to solve the problems that distributed routing algorithm consumes large amount of energy in the application of software-defined wireless sensor networks and the energy consumption of cluster head is unbalanced, this paper proposes an Extremum Disturbed Particle Swarm Optimization based Energy-Balanced Routing algorithm（tPSOEB）. The algorithm chooses the cluster head by considering the residual energy, position and energy balance information of the nodes, uses disturbance to improve the search performance of particle swarm optimization and builds different clusters according to the uneven cluster theory, one round global clustering and [k]-round local cluster head updating are adopted to save the energy consumption of clustering. When building the inter-cluster routing, the shortest routing tree is constructed in a centralized way according to the link energy consumption, the residual energy of nodes and the number of nodes in the cluster. Simulation results show that the algorithm can significantly improve the energy efficiency of the network and extend the network lifetime.

Key words: software-defined sensor networks, energy balance, uneven clustering, Particle Swarm Optimization（PSO）

摘要： 针对分布式路由算法在软件定义无线传感器网络中应用时能量消耗大以及簇头能耗不均衡问题，提出一种基于扰动粒子群优化的能耗均衡路由算法tPSOEB。该算法通过考虑节点的剩余能量、位置和能量均衡信息选择簇头，并引入扰动改进粒子群算法的搜索性能，然后用非均匀分簇的思想来构建大小不等的簇，每周期进行一轮全局分簇和[k]轮局部簇头更新，节省分簇时的能量消耗。在簇间路由建立时，根据链路能耗、节点剩余能量和簇内节点数，采用集中式方式构建最短路由树。仿真结果表明，tPSOEB能显著提高网络的能量使用率，延长网络寿命。

关键词: 软件定义传感器网络, 能耗均衡, 非均匀分簇, 粒子群优化（PSO）