Improved algorithm of cluster-based routing protocols for agricultural wireless multimedia sensor networks

Zhang Fu, Liu Hongmei, Wang Jun, Qiu Zhaomei, Mao Pengjun, Zhang Yakun

Abstract


Low Energy Adaptive Clustering Hierarchy (LEACH) is a routing algorithm in agricultural wireless multimedia sensor networks (WMSNs) that includes two kinds of improved protocol, LEACH_D and LEACH_E. In this study, obstacles were overcome in widely used protocols. An improved algorithm was proposed to solve existing problems, such as energy source restriction, communication distance, and energy of the nodes. The optimal number of clusters was calculated by the first-order radio model of the improved algorithm to determine the percentage of the cluster heads in the network. High energy and the near sink nodes were chosen as cluster heads based on the residual energy of the nodes and the distance between the nodes to the sink node. At the same time, the K-means clustering analysis method was used for equally assigning the nodes to several clusters in the network. Both simulation and the verification results showed that the survival number of the proposed algorithm LEACH-ED increased by 66%. Moreover, the network load was high and network lifetime was longer. The mathematical model between the average voltage of nodes (y) and the running time (x) was concluded in the equation y=−0.0643x+4.3694, and the correlation coefficient was R2=0.9977. The research results can provide a foundation and method for the design and simulation of the routing algorithm in agricultural WMSNs.
Keywords: wireless sensor networks, routing protocol, LEACH algorithm, improved algorithm, cluster head, K-means clustering
DOI: 10.3965/j.ijabe.20160904.2261

Citation: Zhang F, Liu H M, Wang J, Qiu Z M, Mao P J, Zhang Y K. Improved algorithm of cluster-based routing protocols for agricultural wireless multimedia sensor networks. Int J Agric & Biol Eng, 2016; 9(4): 132－140.

Keywords


wireless sensor networks, routing protocol, LEACH algorithm, improved algorithm, cluster head, K-means clustering

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