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생물지리학적 최적화를 적용한 이동체 리포팅 셀 시스템 설계

Biogeography Based Optimization for Mobile Station Reporting Cell System Design

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주제분류산업공학

초록

Fast service access involves keeping track of the location of mobile users, while they are moving around the mobile network for a satisfactory level of QoS (Quality of Service) in a cost-effective manner. The location databases are used to keep track of Mobile Terminals (MT) so that incoming calls can be directed to requested mobile terminals at all times. MT reporting cell system used in location management is to designate each cell in the network as a reporting cell or a non-reporting cell. Determination of an optimal number of reporting cells (or reporting cell configuration) for a given network is reporting cell planning (RCP) problem. This is a difficult combinatorial optimization problem which has an exponential complexity. We can see that a cell in a network is either a reporting cell or a non-reporting cell. Hence, for a given network with N cells, the number of possible solutions is . We propose a biogeography based optimization (BBO) for design of mobile station location management system in wireless communication network. The number and locations of reporting cells should be determined to balance the registration for location update and paging operations for search the mobile stations to minimize the cost of system. Experimental results show that our proposed BBO is a fairly effective and competitive approach with respect to solution quality for optimally designing location management system because BBO is suitable for combinatorial optimization and multi-functional problems.

Abstract

Fast service access involves keeping track of the location of mobile users, while they are moving around the mobile network for a satisfactory level of QoS (Quality of Service) in a cost-effective manner. The location databases are used to keep track of Mobile Terminals (MT) so that incoming calls can be directed to requested mobile terminals at all times. MT reporting cell system used in location management is to designate each cell in the network as a reporting cell or a non-reporting cell. Determination of an optimal number of reporting cells (or reporting cell configuration) for a given network is reporting cell planning (RCP) problem. This is a difficult combinatorial optimization problem which has an exponential complexity. We can see that a cell in a network is either a reporting cell or a non-reporting cell. Hence, for a given network with N cells, the number of possible solutions is . We propose a biogeography based optimization (BBO) for design of mobile station location management system in wireless communication network. The number and locations of reporting cells should be determined to balance the registration for location update and paging operations for search the mobile stations to minimize the cost of system. Experimental results show that our proposed BBO is a fairly effective and competitive approach with respect to solution quality for optimally designing location management system because BBO is suitable for combinatorial optimization and multi-functional problems.

참고문헌 (12)

  1. 변지환, "BPSO를 이용한 리포팅 셀 위치관리시스템 최적 설계", 경영과학, 28(2), pp.53~62 (2011), 한국경영과학회
  2. Godim, P. R. L., "Genetic algorithms and the location area partitioning problem in cellular networks", Proc. IEEE 46th Vehicular Technology conf. Mobile Technology for the Human Race (1996)
  3. Hac, A., "Locating strategies for personal communication networks : A novel tracking strategy", IEEE J. Selected Areas in Comm, 15(8), pp.1425~1436 (1997)
  4. 김성수, "리포팅셀 위치 관리 시스템 최적 설계를 위한 개선된 이진 인공벌 군집 알고리즘 개발", Telecommunications Review, 22(2), pp.287~297 (2012), 에스케이텔레콤 (주)[DOI]
  5. 김성수, "인공벌군집을 적용한 무선네트워크 셀 그룹핑 설계", 한국산업경영시스템학회지, 39(2), pp.46~53 (2016), 한국산업경영시스템학회
  6. 김성수, "엘리티즘이 적용된 생물지리학적 최적화를 사용한 그리드 컴퓨팅 작업 스케줄링", 한국경영과학회지, 44(2), pp.43~52 (2019), 한국경영과학회[DOI]
  7. Simon, D., "Biogeography-based optimization", IEEE Transactions on Evolutionary Computation, 12(6), pp.702~713 (2008)
  8. Simon, D., "Population distributions in biogeography based optimization algorithms with elitism", 2009 IEEE International Conference on Systems, Man and Cybernetics, pp.991~996 (2009)
  9. Simon, D., "Analytical and numerical comparisons of biogeography-based optimization and genetic algorithms", Information Sciences, 181(7), pp.1224~1248 (2011)
  10. Subrata, R., "A comparison of three artificial life techniques for reporting cell planning in Mobile Computing", IEEE Trans. Parallel And Distributed Systems, 14(2), pp.142~153 (2003)
  11. Subrata, R., "Evolving cellular automata for location management in mobile computing networks", IEEE Trans. Parallel And Distributed Systems, 14(1), pp.13~26 (2003)
  12. Zomaya, A. Y., "Some observations on using meta-heuristics for efficient location management in mobile computing networks", Journal of Parallel and Distributed Computing, 63(1), pp.33~44 (2003)

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