Max k-Cut based Clustering Algorithm for Wireless Sensor Networks

무선 센서 네트워크에서의 Max k-Cut기반의 클러스터링 알고리즘

  • 김재환 (서강대학교 컴퓨터공학과) ;
  • 장형수 (서강대학교 컴퓨터공학과)
  • Published : 2009.04.15

Abstract

In this paper, we propose a novel centralized energy-efficient clustering algorithm, called "MCCA : Max k-Cut based Clustering Algorithm for Wireless Sensor Networks." The algorithm does not use location information and constructs clusters via a distributive Max k-Cut based cluster-head election method, where only relative and approximate distance information with neighbor nodes is used and nodes, not having enough energy, are excluded for cluster-heads for a specific period. We show that the energy efficiency performance of MCCA is better than that of LEACH, EECS and similar to BCDCP's by simulation studies.

본 논문에서는 Wireless Sensor Networks에서 Max k-Cut Problem을 기반으로 위치 정보를 사용하지 않고 클러스터 헤드를 적절히 분산하여 선출함으로써 에너지 효율적인 클러스터링을 하는 중앙처리 방식의 새로운 알고리즘 "MCCA : Max k-Cut based Clustering Algorithm for Wireless Sensor Networks"을 제안한다. MCCA는 이웃 노드와의 상대적이고 근사적인 거리 정보만을 사용하여 효율적으로 클러스터링을 하고 에너지가 적은 노드는 클러스터 헤드 선출에서 일정 기간 제외되는 방법을 사용함으로써 LEACH, EECS보다 에너지 효율이 증대됨과 GPS를 사용한 BCDCP와 에너지 효율이 비슷함을 실험을 통하여 보인다.

Keywords

References

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