摘要
好的分簇算法能够有效减少网络能耗和提高网络可靠性,但是簇间负载的不均衡性和通信的不可靠性会严重影响分簇算法的性能.针对这个问题,该文首先提出了一个负载均衡感知的无线传感器网络容错分簇算法.该方法引入了遗传算法的随机两点交叉算子和随机单点变异算子,从而设计了一种以种群粒子优劣为依据的自适应惯性权重调整策略,并提出了一种自适应的离散粒子群优化算法.算法设计同时考虑负载均衡和能量消耗两个优化目标,给出一种基于自适应离散粒子群优化的簇首选举机制;其次,为了保证网络上数据传输的可靠性,以最小生成树为基础,提出了一种用于保证簇首二连通性的簇间连通算法,通过消除网络中的割点,以保证网络的二连通性.仿真实验结果表明,该文提出算法在负载均衡和二连通性上有较好的性能,能有效减少了网络能耗,延长网络生命周期,并提高网络可靠性.
Good clustering algorithm can effectively reduce network energy consumption and improve the reliability of network. However, load unbalance and communication unreliability between the clusters have significant impacts on the performance of the clustering algorithm. In this paper, a fault-tolerance clustering algorithm with load-balance aware was proposed to solve these problems. Base on the quality of the particles in the population, an adaptive discrete parti- cle swarm optimization （ADPSO） with an adaptive adjustment strategy for inertia weight was designed, using the randomly two-point crossover operator and random one-point mutation operator of the genetic algorithm. We introduced a cluster head selection mechanism based on ADPSO for optimizing both of the two objects, load balancing and energy consumption in the algorithm. Moreover, to guarantee the reliability of data transmission, an inter cluster connectivity algorithm based on local minimum spanning tree was constructed, which ensured the two-connectivity by eliminating cut point in the network. The experimental results demonstrate that the proposed algorithm can aehieve better performance on load balancing and two-conneetivity, effectively reducing the energy consumption, prolonging the lifetime of the network and improving the network reliability.
出处
《计算机学报》
EI
CSCD
北大核心
2014年第2期445-456,共12页
Chinese Journal of Computers
基金
国家"九七三"重点基础研究发展规划项目基金(2009CB320503)
国家自然科学基金(61103175)
教育部科学技术研究重点项目基金(212086)
福建省科技创新平台建设基金(2009J1007)资助~~
关键词
无线传感器网络
分簇算法
负载均衡
粒子群优化
二连通性
物联网中图法
wireless sensor mlzatlonl two-connectivity
network
clustering algorithm
load balancing
particle swarm opti Internet of Things
