Conference Paper

Genetic algorithm based approach for cluster formation in wireless sensor networks

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Abstract

In wireless sensors networks (WSNs) the efficient use of the sensors' energy is a key point to extend the network lifetime. In the literature there are several different techniques to reduce the energy consumption of the sensors. Sensor node clustering is one of these techniques commonly used. However, finding an optimal clustering in WSNs is a NP-Hard problem, thus heuristics and metaheuristics are the appropriate methods to find good clustering in reasonable computational time. In this work we propose the application of a simple and efficient metaheuristic based on genetic algorithms to obtain near-optimal clustering. We develop a clustering protocol to simulate the clusters formation and data transmission. The good performance of our protocol is compared with the well-known and commonly used clustering protocols for WSNs: LEACH and LEACH-C. The obtained results reveal that the genetic algorithm determines better clusters extending the network lifetime.

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... In [75], Firefly algorithm is used to find unknown nodes with optimal solution. These class of papers [76][77][78][79] belong to Genetic Algorithm. In [80], Beehive Optimization (BHO) approach is used to increase the lifetime of a network. ...
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Over the past few decades, one of the important advancements in wireless communication is low cost and limited power devices known as wireless sensor networks (WSNs). Sensor nodes are used to transmit data but have limited amount of energy. As the transmission takes place, energy gets depleted. So energy consumption and network lifetime are the major challenges in a WSN. Much research has been done in the past years to determine an optimal path between source and destination nodes, which will result in maximizing energy conservation of a network. However, the challenge is to create a routing algorithm that takes into consideration the major issues of minimizing energy consumption and maximizing network lifetime. Various optimization techniques are available to determine a routing path between a source node and destination node. In this article, we look into the details of routing in WSN using different optimization techniques. This article provides us a comprehensive summary of the previous studies in field of WSN during the span of 2010–2019. The results provided in this article provide the future insight for researchers to fill in existing gaps in the WSN research field and to find new research trends in this area.
... In [75], Firefly algorithm is used to find unknown nodes with optimal solution. These class of papers [76][77][78][79] belong to Genetic Algorithm. In [80], Beehive Optimization (BHO) approach is used to increase the lifetime of a network. ...
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