In order to improve the energy efficiency of Wireless Sensor Network (WSN),a WSN routing algorithm based on Optimal Number of Clusters and Improved Gravitational Search (ONCIGS) was proposed.Firstly,the optimal number of clusters was calculated according to the idea of uneven clustering,and the improved AGglomerative NESting (AGNES)algorithm was adopted to realize the reasonable clustering of network.Secondly,reverse learning mechanism and elite strategy were introduced into the gravitational search algorithm,and the force was adjusted adaptively based on population density to improve the search precision and speed up the convergence.Then,the standard deviation of residual energy of cluster heads was taken as the objective function to search the energy-balanced inter-cluster data forwarding path.The experimental results show that,compared with the Low Energy Adaptive Clustering Hierarchy (LEACH) routing algorithm and Distributed Energy Balanced Unequal Clustering (DEBUC) routing algorithm,the network life cycle of the proposed ONCIGS is prolonged by 41.94％ and 5.77％ respectively under the network scale of 100 m × 100 m,and it is prolonged by 76.60％ and 7.82％ respectively under the network scale of 200 m × 200 m.The proposed ONCIGS can effectively prolong network lifetime and improve energy efficiency.%为了提高无线传感器网络(WSN)的能量利用效率,提出一种基于最优簇数和改进引力搜索的WSN路由算法(ONCIGS).首先,根据非均匀分簇的思想计算最优簇数,并采用改进的凝聚嵌套(AGNES)算法实现网络的合理分簇;其次,将反向学习机制和精英策略思想引入到引力搜索算法中,并基于种群密度对作用力进行自适应调整,以提高搜索精度,加快收敛;然后,将簇头剩余能量的标准差作为目标函数,搜索能量均衡的簇间数据转发路径.实验结果表明,相比低功耗自适应集簇分层型(LEACH)路由算法和分布式能量均衡非均匀成簇(DEBUC)路由算法,ONCIGS在100 m×100 m网络规模下将网络生命周期分别延长41.94％和5.77％,在200 m×200 m网络规模下分别延长76.60％和7.82％.ONCIGS能够有效地延长网络寿命,提高能量效率.
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