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01-Applied Mathematics & Information Sciences
An International Journal
               
 
 
 
 
 
 
 
 
 
 
 
 
 

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Volumes > Volume 13 > No. S1

 
   

A Meta-Heuristic Particle Swarm Optimization-Based Energy Efficient Routing Protocol for MANET

PP: 359-370
doi:10.18576/amis/13S139
Author(s)
S. Rajalakshmi, S. Sendhilnathan, S. Sujatha,
Abstract
Various techniques have been used in MANET for improving the energy efficiency of routing between the mobile nodes. But, each mobile node is driven by a battery with an inadequate capacity. Due to this reason, the nodes fail to transfer data packets to the destination node which leads to the major drawback of link failure. Furthermore, this results in some problems such as high energy consumption and retransmission process. To overcome these problems, a Proficient Energy Saving Routing (PESR) protocol is proposed to obtain an unchanging energy-efficient routing with energy awareness knowledge. The Enriched Neighbor Discovery (END) mechanism and the Meta-Heuristic Particle Swarm Optimization (MHPSO) techniques are mainly used in this proposed protocol. The END mechanism is used to collect the nodes within a specified range to provide the shortest route for transmission. Whereas the Meta-Heuristic Particle Swarm Optimization (MHPSO) rule is used to discover the efficient route. In addition, a number of node parameters is initiated to evaluate the node stability and to save the energy of the network. The PESR protocol with an effective data communication route selection is finally calculated based on these estimated node parameters. From the results, this protocol achieved the maximum network lifetime, increased throughput and end-to-end delay with less energy consumption which reduce the packet loss rate and overhead. Thus the devised PESR protocol enriches its capability and outperforms other prevailing methodologies in terms of energy consumption, network lifetime, and throughput. Therefore, the proposed PESR protocol minimizes its energy consumption and improves the network lifetime.

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