Clustering Algorithm In Wireless Sensor Networks Base On Energy-Aware

Wireless sensor network is highly cross-multidisciplinary research field,which has began to be studied Since 1990s. Now WSN has become the core industries of the Internet of Thing, and has brought a revolution in information perception and information gathering. Industry and research communities have been paying more and more attention to this field.Topology control is one of the key technology of WNSs, it can optimize the topology of the self-organization sensor networks, make the protocols of MAC layer and routing layer more efficient, improve the nodes'energy efficiency and the network lifecycle. Clustering algorithm is one of the important research direction of topology control technology for WSNs. Based on some certain rules ,the network is divided into several clusters, each cluster has a cluster head, which collects the data from sensor nodes, make fusion and then send the data to sink node. The main focus of the paper is as follow: In energy heterogeneous network, How to make the nodes clustering properly, and when the cluster head wants to send data to sink, How to make it energy-efficiency. To achieve this goal,EaDEEC, an Distributed Energy-aware and Efficient Clustering Algorithm is proposed.The proposed algorithm is divided into two parts, clustering strategy design and strategic design cluster head forwards the data. Clustering strategy which draws on the design of heterogeneous processing energies DEEC algorithm ideas, dynamically evaluated the ratio of residual energy of a particular node to the average energy of the network, and used the ratio to determine whether the node would become a cluster head, so those whom with higher network initial energy, the higher residual energy of nodes will have a higher probability to become cluster head; Forwarding strategy in the cluster header,EaDEEC used the energy-aware multi-hop between the clusters and sink, the cluster head's residual energy and communication cost between neighbor cluster heads will be considered, to ensure the energy efficiency of the link and the robustness of the network. Simulation results show EaDEEC algorithm in different network size, EaDEEC can work well in energy heterogeneous environment and has a longer survival time, a good network load balancing. But EaDEEC also has some shortcomings, such as how to balance the energy efficiency and network latency ,and it will be the future research directions.