In this study using black hole algorithm (BHA), we determine the number and location of the cluster heads to the best optimization. Fitting the criterion will be based on the minimum consumed energy of each node in the network in every data transmission operation period that will be led to the creation of a balance in energy consumption of cluster heads and consequently longer life of network | International Journal of Computer Networks and Communications Security VOL. 2, NO. 12, DECEMBER 2014, 443–447 Available online at: ISSN 2308-9830 Optimization of Energy Consumption in Clustered Nodes of WSN Using the Black Hole Algorithm Masoum Farahmandian1 and Abdolreza Hatamlou2 1 Department of Computer Engineering, Urmia Branch, Islamic Azad University, Urmia, Iran 2 Department of Computer Engineering, Khoy Branch, Islamic Azad University, Khoy, Iran E-mail: 1gmasafat@, 2hatamlou@ ABSTRACT Nowadays due to the low cost and easy communication, Wireless Sensor Networks (WSN) have many uses for supervisory activities in a variety of environments. The limitation of the energy available in the nodes of the networks is the main problem that affects the survival of the network. Studies have shown that with the creation of control on the number and location of the cluster heads on, the efficiency of energy can increase which results in increase of the life of the network. However, due to the dynamic nature of the issue and due to continuous changes in cluster heads in any of the network activity, this issue is not applicable to classical methods of modeling. In this study using black hole algorithm (BHA), we determine the number and location of the cluster heads to the best optimization. Fitting the criterion will be based on the minimum consumed energy of each node in the network in every data transmission operation period that will be led to the creation of a balance in energy consumption of cluster heads and consequently longer life of network. Keywords: Wireless Sensor Networks, BHA, Classification of Clusters, Cluster Heads, Energy Balance, Optimization. 1 INTRODUCTION In recent years, the electronic and telecommunication technologies development, has led to the construction of the small and relatively inexpensive sensors. In spite of their small size, these sensors have the ability of calculation, data measurement and .
