Journal of the Korea Academia-Industrial cooperation Society (한국산학기술학회논문지)

The Korea Academia-Industrial cooperation Society (한국산학기술학회)
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An Energy Efficient Clustering based on Genetic Algorithm in Wireless Sensor Networks

무선 센서 네트워크에서 유전 알고리즘 기반의 에너지 효율적인 클러스터링

  • Kim, Jin-Su (Division of Port & Logistics, TongMyong University)
  • Received : 2010.04.03
  • Accepted : 2010.05.13
  • Published : 2010.05.31
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Abstract

In this paper, I propose an Energy efficient Clustering based on Genetic Algorithm(ECGA) which reduces energy consumption by distributing energy overload to cluster group head and cluster head in order to lengthen the lifetime of sensor network. ECGA algorithm calculates the values like estimated energy cost summary, average and standard deviation of residual quantity of sensor node and applies them to fitness function. By using the fitness function, we can obtain the optimum condition of cluster group and cluster. I demonstrated that ECGA algorithm reduces the energy consumption and lengthens the lifetime of network compared with the previous clustering method by stimulation.

본 논문에서는 센서 네트워크의 수명을 길게 하기 위해 클러스터 헤드에 집중된 에너지 과부하를 클러스터 그룹 헤드와 클러스터 헤드로 분산시켜서 에너지 소모량을 감소시키는 유전 알고리즘 기반의 에너지 효율적인 클러스터링(ECGA: Energy efficient Clustering based on Genetic Algorithm)을 제안한다. ECGA 알고리즘은 예상 에너지 비용 합계, 센서 노드 에너지 잔량의 평균 및 표준 편차를 구하여 이를 적합도 함수에 적용하였다. 이 적합도를 이용하여 최적의 클러스터 그룹 및 클러스터를 형성한다. 실험을 통하여 ECGA 알고리즘이 이전의 클러스터링 기법보다 에너지 소모를 줄이고 네트워크의 수명을 연장시켰음을 보였다.

Keywords

References

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