中文摘要：

这份报纸建议一个新奇精力为大规模的有效不相等的聚类算法试图只要，平衡节点电源消费并且延长网络一生的无线传感器网络(WSN ) 可能。我们的途径在精力上集中有效不相等的聚类计划和内部簇的路由协议。在一方面，考虑每个节点象精力水平，基于车站的距离和本地密度那样的本地信息，我们使用模糊逻辑系统决定一个节点成为簇头和估计的机会相应胜任半径。在另一方面，适应 max-min 蚂蚁殖民地优化被用来构造在簇头和基础车站(BS ) 之间的精力知道的内部簇的路由，它平衡簇头的精力消费并且减轻发生在多跳跃 WSN 路由协议到大程度的热点问题。证实实验结果显示了建议聚类的算法比象低精力那样的另外的方法有更优异的性能适应聚类层次(沥滤) 并且精力有效不相等的聚类(EEUC ) 。

英文摘要：

This paper proposes a novel energy efficient unequal clustering algorithm for large scale wireless sensor network （WSN） which aims to balance the node power consumption and prolong the network lifetime as long as possible. Our approach focuses on energy efficient unequal clustering scheme and inter-cluster routing protocol. On the one hand, considering each node＇s local information such as energy level, distance to base station and local density, we use fuzzy logic system to determine one node＇s chance of becoming cluster head and hand, adaptive max-min ant colony optimization is used to estimate the corresponding competence radius. On the other construct energy-aware inter-cluster routing between cluster heads and base station （BS）, which balances the energy consumption of cluster heads and alleviates the hot spots problem that occurs in multi-hop WSN routing protocol to a large extent. The confirmation experiment results have indicated the proposed clustering algorithm has more superior performance than other methods such as low energy adaptive clustering hierarchy （LEACH） and energy efficient unequal clustering （EEUC）.