针对无线传感网负载均衡问题并考虑在数据收集流量模式下节点的负载与距离数据收集节点Sink的跳数相关的特点,提出了一种基于梯度的非均匀分簇算法。通过构建符合实际流量模式的分簇拓扑结构,寻求网络的负载均衡,在一定程度上缓解近Sink的网络拥塞(“热区”)问题。分析此种数据汇集模式的数据流量特性,给出了节点至Sink跳数(梯度)与其负载流量的关系;从不同梯度的簇头负载与相同梯度的负载两方面着手,设计了负载平衡的非均匀分簇调整算法(WUC),依据节点自身的梯度确定分簇的规模,以多权值优化的方式成簇。仿真结果表明,网络中不同梯度的簇头流量负载标准差降低了9倍左右,网络的负载平衡有了显著的改善。

In consideration of the characteristics that loads of nodes and hops to Sink are interrelated in data gathering traffic model,a grade-based unequal clustering algorithm is proposed to solve the load-balancing problem of wireless sensor networks.A traffic-mode-based clusterinig topologic structure is built to realize the load balancing of network and to relieve the traffic congestion around Sink(“Hot Spot” problem). Based on the analysis of the data gathering traffic model,the relationship between the hops to Sink and the load of Cluster Heads(CHs) is given.Then,a grade-based load-balancing clustering algorithm for a wireless sensor network is prensented,in which the cluster size is based on nodes’ grade and the cluster head selection uses mulit-weight.Simulation results show that the standard deviations of CHs’ load with different grades are reduced by 9 times,so that the load balance of the wireless sensor network is improved effectively.