Optimization Algorithm for Wireless Sensor Networks using K-means and Evolutionary Algorithm | ||||
| Port-Said Engineering Research Journal | ||||
| Article 17, Volume 17, Issue 1, March 2013, Page 146-152 PDF (409.47 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/pserj.2013.43756 | ||||
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| Authors | ||||
| R El-Awady1; Rehab Abdel-Kader2; Mohamed Tobal2 | ||||
| 1Faculty of Engineering, Mansoura University, Mansoura, Egypt | ||||
| 2Faculty of Engineering, Port-Said University, Port-Said, Egypt | ||||
| Abstract | ||||
| Recently, many new types of wireless networks have emerged for both civil and military, applications, such as wireless sensor networks, ad hoc networks, among others. In this paper , we mainly focus on static sensor networks .In these networks, every node is capable of sensing, data processing, and communication, and operates on its limited amount of battery energy consumed mostly transmission and reception and its radio transceiver. We propose a merged algorithm between Evolutionary Algorithm (EA) and K-means clustering. K-means divide the sensor network into K-clusters (K-known); EA finds the optimal Fitness of the network. The proposed algorithm determines the optimal number of clusters, cluster elements, and the head of each cluster. Thus, the total distance will be reduced and this will lead to energy saving and long life time network | ||||
| Keywords | ||||
| sensor networks; Clustering; K-means; Evolutionary Algorithm; Network life time | ||||
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