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Differential Evolution Algorithm with Diversified Vicinity Operator for Optimal Routing and Clustering of Energy

Subramaniam Sumithra1, T Aruldoss Albert Victoire1

  • 1Anna University, Regional Centre, Coimbatore, Tamilnadu 641047, India.

Thescientificworldjournal
|October 31, 2015
PubMed
Summary
This summary is machine-generated.

This study introduces an improved Differential Evolution algorithm for wireless sensor networks (WSN). The method optimizes clustering and routing to conserve energy and extend network lifespan.

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Wireless Sensor Networks (WSN) face challenges in optimal clustering and routing due to large network dimensions and increasing sensor node sizes.
  • Efficient energy consumption is critical for extending the operational lifetime of sensor nodes in WSNs.
  • Existing methods struggle to balance energy efficiency and data transmission delay in large-scale WSNs.

Purpose of the Study:

  • To propose a novel method for optimizing clustering and routing in large WSNs.
  • To enhance energy efficiency and prolong the network lifetime of WSNs.
  • To address the complexity and cumbersomeness of optimal route and cluster determination in large WSNs.

Main Methods:

  • The proposed method utilizes the Differential Evolution (DE) algorithm.
  • An improvised search operator, Diversified Vicinity Procedure (DVP), is introduced to model a trade-off between energy consumption and data packet delay.
  • The algorithm focuses on efficient energy consumption for cluster heads and data forwarding.

Main Results:

  • The proposed method achieves a reasonably better solution for the clustering and routing problem.
  • The obtained routes demonstrate comparatively lesser overall distance from gateways to the base station.
  • The method results in fewer data forwards, contributing to network efficiency.

Conclusions:

  • The developed method, integrating DE with DVP, effectively manages energy consumption in WSNs.
  • Numerical experiments validate the superiority of the proposed method over existing algorithms.
  • The approach significantly contributes to extending the network lifetime of wireless sensor networks.