Centralized Clustering Algorithm to Enhance Energy Consumption in Wireless Sensor Networks

نویسندگان

  • Mustafa Fuad Ismail
  • Dahlila Putri Dahnil
چکیده

A Wireless Sensor Networks (WSNs) composed of a large number of sensor nodes within a sensing geographical area. Energy consumption is considered a major WSNs issue. Therefore, a considerable number of researches have investigated various ways to reduce energy consumption. One of the best techniques used to reduce energy consumption is clustering. Clustering helps to improve the network performance through extending the battery lifetime. Our study improves the work on LEACH Enhancements for WSNs based on the energy model by introducing the K-means clustering approach to improve energy and increase network lifespan. The proposed approach divides the nodes into member nodes and cluster head nodes. The member nodes transmit data to the cluster head, whereas, the cluster head nodes are responsible for communication with the base station. This approach is a centralized election technique where the base station makes the decision for selecting the cluster heads based on the information received from each node. The advantage of the proposed technique is that the information of each node is only sent once to the base station during the initialization phase. The base station performs weightage calculation for all nodes and nodes with the highest weights are elected as cluster heads. The base station also decides the cluster members and the decisions are then transmitted to all nodes in the network. This research introduces weightage calculation based on three important parameters which are remaining energy, number of neighbor nodes and the node’s distance to base station. The proposed technique consists of three phases: Initialization Phase, Setup Phase, and Selection Phase. The results of our proposed technique shows significant improvement of the residual energy, the total energy consumption, the total alive nodes, and total packets delivered compared to LEACH Enhancement for WSNs based on the energy model technique. In conclusion, the results of this study show improvements and achieved the objectives of this paper.

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تاریخ انتشار 2017