Research On The Clustering Routing Algorithm Based On The Balanced Energy Consumption

With the widespread application of wireless sensor networks(WSN), the research on WSN routing algorithm has been attached great importance, and the appropriate use of node energy to improve the utilization has become one of the key issues for WSN. Therefore, the design of the routing algorithm with high efficiency and balanced load is important and valuable for the application of WSN. The clustering routing algorithm is researched in detail, the main problems existing in the conventional algorithms are analyzed, and accordingly two improved algorithms are proposed in the paper.First, the WSN balanced energy consumption clustering routing algorithm based on the K-means method is presented. In the algorithm, the K-means method is used to carry out the more balanced clustering, so as to balance energy consumption and lay a foundation for the longer life of WSN; in selecting cluster head, the statistical method is used to obtain the more dynamic multiple cluster head, and the dynamic queue TDMA method is used when the round of communications is distributed. These methods make WSN sub-state reduce the proportion in the entire life cycle greatly, which ensures the network synchronization failure to a large extent and improves the stability and reliability of WSN.Second, the hierarchical multi-hop clustering routing algorithm is proposed. Aiming at the hot spots resulted from the same cluster size in the balanced energy consumption clustering routing algorithm, the clustering ideas are inherited, the chained multi-hop mechanism is referred to, and the hierarchical network is carried out according to the communications cost of energy consumption. The higher energy efficiency is obtained, the problem of the network hot spots is solved, and the network survival time is prolonged by the algorithm.The simulation experiments show that these two improved algorithms are feasible, which improves the network load balancing significantly and solves the problem of network energy consumption effectively.