The development of wireless sensor networks (WSNs) has recently opened up a new and interesting area for the creation of new types of applications. WSNs consist of a large number of small sensing nodes that monitor their environment, process data if necessary (using microprocessors) and send/receive processed data to/from other sensing nodes. These sensing nodes, distributed in the environment, are connected to a sink node – in centralized networks – or to other sensing nodes via a network. In centralized networks, the sink collects sensor data to be used by the end user. In many cases, the sink is also capable of activating sensing nodes via broadcasting, by sending network policy and control information.
Here explanation of proposed work is done by two method first is by block diagram so it act as graphical representation of whole work while in second explanation of each step is done in word form. So reading this part make clear understanding of whole work in detail. In this work a approach is adopt for finding the best set of cluster center by using genetic algorithm with Teacher leaning Based optimization. Here whole work is depend on the random condition of the available energy present in different nodes In this work energy obtained from the nodes act as important feature for the cluster selection. TLBO algorithm find the best set of power resources for particular set of demands.
The wireless sensor networks continue to grow and become widely used in many applications. So, the need for security becomes vital. However, the wireless sensor network suffers from many constraints such as limited energy, processing capability, and storage capacity, etc. Consequently, many innovative security protocols and techniques have been developed to meet this challenge. The availability of sensor devices allow a wide variety of applications to emerge. However, the resource constrained nature of sensors raises the problem of energy: how to maximize network lifetime despite a very limited energy budget. This paper proposed a new approach of finding the cluster center of WSN (Wireless Sensor Network) for improving energy efficiency method. Here genetic algorithm was used which was named as TLBO (Teacher Learning Based optimization). Basic reason for the use of this algorithm was that it can adopt dynamic situation without any training. So based on the current node position and energy value with data transfer units one can easily configure WSN by finding good cluster center set among various nodes in very less time. Proposed work was compared with previous algorithm LEACH and it was obtained that proposed work of genetic algorithm have improved different evaluation parameters.
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