Abstract
AbstractThe equilibrium use of energy is very important for wireless sensor networks (WSN) with limited energy in order to avoid premature network collapse. The existing methods either need too complex calculations for precise clustering, or are too simple to overburden a few cluster heads. In order to solve these problems, we proposed energy balanced clustering routing (EBCR) in this paper. It could maximize the WSN life in energy non-harvesting scenario or improve energy utilization efficiency in energy harvesting scenario without increasing the amount of calculations. It gives a complete solution to the process of cluster head election, clustering, and intercluster routing algorithm. Firstly, a light weight cluster head election and a distributed cluttering method are proposed by introducing dynamic cluster radius and intersection region node division schemes with new principles. Thus, lightweight distributed clustering achieves the advantages of balancing the burden of cluster heads and alleviating hot zone problem. Then we optimized the cluster cooperative routing algorithm by analyzing cooperation and competition among cluster heads. The intercluster cooperative routing algorithm greatly improves the transmission efficiency between cluster heads. Moreover, this paper analyzes the reasons why the algorithm achieves more balanced energy usage, higher energy efficiency, and fewer calculations compared to the existing mainstream algorithms. At last, simulation results show that EBCR algorithm has advantages in terms of network energy consumption, number of surviving nodes in energy non-harvesting scenario compared with the delay-constrained energy-efficient cluster-based multi-hop routing (DCEM) method. Simulation also gives EBCR algorithm performance under various energy harvesting scenarios, which is quite satisfactory in energy utilization efficiency comparing with DCEM method. EBCR algorithm has superior performance in terms of balanced energy usage, low computation complexity, and high energy efficiency.
Funder
National Natural Science Foundation of China
National Natural Science Foundation of China and Shanxi Provincial People's Government Jointly Funded Project of China for Coal Base and Low Carbon
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Computer Science Applications,Signal Processing
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