The KIPS Transactions:PartC (정보처리학회논문지C)

Korea Information Processing Society (한국정보처리학회)
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A Token Based Clustering Algorithm Considering Uniform Density Cluster in Wireless Sensor Networks

무선 센서 네트워크에서 균등한 클러스터 밀도를 고려한 토큰 기반의 클러스터링 알고리즘

  • 이현석 (울산대학교 컴퓨터정보통신공학부) ;
  • 허정석 (울산대학교 컴퓨터정보통신공학부)
  • Received : 2010.02.16
  • Accepted : 2010.05.06
  • Published : 2010.06.30
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Abstract

In wireless sensor networks, energy is the most important consideration because the lifetime of the sensor node is limited by battery. The clustering is the one of methods used to manage network energy consumption efficiently and LEACH(Low-Energy Adaptive Clustering Hierarchy) is one of the most famous clustering algorithms. LEACH utilizes randomized rotation of cluster-head to evenly distribute the energy load among the sensor nodes in the network. The random selection method of cluster-head does not guarantee the number of cluster-heads produced in each round to be equal to expected optimal value. And, the cluster head in a high-density cluster has an overload condition. In this paper, we proposed both a token based cluster-head selection algorithm for guarantee the number of cluster-heads and a cluster selection algorithm for uniform-density cluster. Through simulation, it is shown that the proposed algorithm improve the network lifetime about 9.3% better than LEACH.

무선 센서 네트워크에서 센서노드의 수명은 배터리에 의해 제한되므로 에너지는 가장 중요한 고려사항이다. 클러스터링은 네트워크의 에너지 소비를 효율적으로 관리하는데 사용되는 방법 중 하나이며, LEACH는 대표적인 클러스터링 알고리즘이다. LEACH는 센서 노드들의 에너지 소비를 공평하게 분산시키기 위해 에너지 소모적 기능을 하는 클러스터 헤드를 매 라운드마다 무작위로 순환시키는 방법을 사용하고 있다. 클러스터 헤드의 무작위 선정은 매 라운드 최적의 클러스터 헤드 수를 보장해주지 못한다. 그리고 밀도가 높은 클러스터에 위치한 클러스터 헤드는 과부하 상태가 된다. 본 논문에서는 클러스터 헤드의 수를 보장하기 위한 토큰 기반의 클러스터 헤드 선정 알고리즘과 균등한 밀도의 클러스터 형성을 위한 클러스터 선택 알고리즘을 제안한다. 시뮬레이션을 통하여 제안하는 알고리즘이 LEACH 보다 네트워크 수명이 9.3%정도 연장됨을 보여주었다.

Keywords

References

  1. J. N. Al-Karaki, A. E. Karnal, 'Routing Techniques in wireless sensor networks : A Survey,' Wireless Communications, IEEE, Vol.11, No.6, pp.6-28, 2004. https://doi.org/10.1109/MWC.2004.1368893
  2. I. F. Akyldiz, W. Su, Y. Sankarusubramaniam, and E. Cyirci, ‘Wireless sensors networks: a survey,’ Computer Networks, Vol.38, No.4, pp.393-422, Aug., 2002. https://doi.org/10.1016/S1389-1286(01)00302-4
  3. K. Akkaya, M. Younis, ‘A survey on routing protocols for wireless sensor networks,’ Ad Hoc Networks, Vol.3, No.3, pp.325-349, 2005. https://doi.org/10.1016/j.adhoc.2003.09.010
  4. S. Bandyopadhyay and E. Coyle, 'An energy efficient hierarchical clustering algorithm for Wireless Sensor Networks,' in Proc. of INFOCOM 2003, vol. 3, pp.1713-1723, 2003. https://doi.org/10.1109/INFCOM.2003.1209194
  5. J. Kulik, W. R. Heinzelman, and H. Balakrishnan, ‘Negotiation-based protocols for disseminating information in wireless sensor networks,’ Wireless Networks, Vol.8, pp.169-185, 2002. https://doi.org/10.1023/A:1013715909417
  6. C. Intanagonwiwat, R. Govindan, and D. Estrin, 'Directed diffusion: a scalable and robust communication paradigm for sensor networks,' Proceedings of ACM MobiCom '00, Boston, MA, pp.56-67, 2000. https://doi.org/10.1145/345910.345920
  7. Y. Xu, J. Heidemann, D. Estrin, 'Geography-informed Energy Conservation for Ad-hoc Routing,' In Proceedings of the Seventh Annual ACM/IEEE International Conference on Mobile Computing and Networking, pp.70-84, 2001. https://doi.org/10.1145/381677.381685
  8. Y. Yu, D. Estrin, and R. Govindan, ‘Geographical and Energy-Aware Routing: A Recursive Data Dissemination Protocol for Wireless Sensor Networks,’ UCLA Computer Science Department Technical Report, UCLA-CSD TR-01-0023, May 2001.
  9. W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, ‘Energy-Efficient Communication Protocol for Wireless Microsensor Networks,’ Proceedings of HICSS, pp.3005-3014, Jan. 2000.
  10. W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, ‘An Application-Specific Protocol Architecture for Wireless Microsensor Networks,’ IEEE Transactions on Wireless Communications, Vol.1, No.4, pp.660-670, Oct., 2002. https://doi.org/10.1109/TWC.2002.804190
  11. A. Manjeshwar and D. P. Agarwal, 'TEEN: a routing protocol for enhanced efficiency in wireless sensor networks,' In 1st International Workshop on Parallel and Distributed Computing Issues in Wireless Networks and Mobile Computing, April, 2001. https://doi.org/10.1109/IPDPS.2001.925197
  12. T. Murata and H. Ishibuchi, 'Performance evaluation of genetic algorithm for flowshop scheduling problems,' Proc. 1st IEEE Conf. Evolutionary Computation, Vol.2, pp.812-817, June, 1994. https://doi.org/10.1109/ICEC.1994.349951
  13. J.M. Kim, S.H. Park, Y.J. Han and T.M. Chung, ‘CHEF: Cluster Head Election mechanism using Fuzzy logic in Wireless Sensor Networks,’ Advanced Communication Technology, pp.654-659, 2008.
  14. Yu Hu, Xiaorui Shen, Zhenhua Kang, 'Energy-Efficient Cluster Head Selection in Clustering Routing for Wireless Sensor Networks,' WiCom '09. 5th International Conference on Networking and Mobile Computing, Digital Object Identifier 10.1109/WICOM.2009.5303808, 2009.
  15. J.M. Hong, J.J. Kook, S.J. Lee, D.S. Kwon, S.H. Yi, ‘T-LEACH: The method of threshold-based cluster head replacement for wireless sensor networks,’ Information Systems Frontiers, Vol.11, No.5, pp.513-521, 2009. https://doi.org/10.1007/s10796-008-9121-4
  16. Z.G. Sun, Z.W. Zheng, S.J. Xu, 'An Efficient Routing Protocol Based on Two Step Cluster Head Selection for Wireless Sensor Networks,' WiCom '09. 5th International Conference on Networking and Mobile Computing, Digital Object Identifier 10.1109/WICOM.2009.5303948, 2009.