한국정보통신학회논문지 (Journal of the Korea Institute of Information and Communication Engineering)

  • 제23권5호
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  • Pages.596-603
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  • 2019
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  • 2234-4772(pISSN)
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  • 2288-4165(eISSN)
한국정보통신학회 (The Korea Institute of Information and Commucation Engineering)
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무선 센서 네트워크에서 노드 재프로그래밍을 위한 타부 서치 알고리즘

A Tabu Search Algorithm for Node Reprogramming in Wireless Sensor Networks

  • Jang, Kil-woong (Department of Data Informatics, Korea Maritime and Ocean University)
  • 투고 : 2019.03.05
  • 심사 : 2019.03.18
  • 발행 : 2019.05.31
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초록

무선 센서 네트워크에서 배치된 노드의 기능을 변경하거나 갱신하기 위해 노드의 소프트웨어 코드를 업데이트하는 재프로그래밍 동작은 필수적이다. 본 논문은 무선 센서 네트워크에서 노드의 재프로그래밍을 목적으로 노드의 전송에너지를 최소화하는 최적화 알고리즘을 제안한다. 또한 네트워크의 수명을 오래 유지하기 위해 전체 노드의 에너지 소모를 균형있게 유지하도록 알고리즘을 설계한다. 본 논문에서는 많은 수의 노드가 배치된 무선 센서 네트워크에서 전송에너지의 최소화와 에너지 소모의 균형화를 위해 새로운 이웃해 생성방식을 가진 타부서치 알고리즘을 제안한다. 제안된 알고리즘은 적정한 수행 시간 내에 최적의 결과를 도출하도록 설계되었다. 제안된 타부서치 알고리즘의 성능은 노드의 전송에너지와 남은 에너지, 알고리즘 수행시간 측면에서 평가되었으며, 성능 평가 결과에서 이전의 방식에 비해 우수한 성능을 보였다.

A reprogramming operation is necessary to update the software code of the node to change or update the functionality of the deployed node in wireless sensor networks. This paper proposes an optimization algorithm that minimizes the transmission energy of a node for the purpose of reprogramming a node in wireless sensor networks. We also design an algorithm that keeps energy consumption of all nodes balanced in order to maintain the lifetime of the network. In this paper, we propose a Tabu search algorithm with a new neighborhood generation method for minimizing transmission energy and energy consumption in wireless sensor networks with many nodes. The proposed algorithm is designed to obtain optimal results within a reasonable execution time. The performance of the proposed Tabu search algorithm was evaluated in terms of the node's transmission energy, remaining energy, and algorithm execution time. The performance evaluation results showed better performance than the previous methods.

키워드

HOJBC0_2019_v23n5_596_f0001.png 이미지

Fig. 1 Node reprogramming process

HOJBC0_2019_v23n5_596_f0002.png 이미지

Fig. 2 Solution encoding structure

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Fig. 3 Move examples (a) network (b) current solution (c) delete move (d) change move

HOJBC0_2019_v23n5_596_f0004.png 이미지

Fig. 4 Total consumed energy (a) rmax = 15 (b) rmax = 20 (c) rmax = 25

HOJBC0_2019_v23n5_596_f0005.png 이미지

Fig. 5 Average execution time (a) rmax = 15 (b) rmax = 20 (c) rmax = 25

HOJBC0_2019_v23n5_596_f0006.png 이미지

Fig. 6 Remained Energy(rmax=15, N=200) (a) TS (b) SA (c) RA

참고문헌

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