인공벌군집을 적용한 무선네트워크 셀 그룹핑 설계
Cell Grouping Design for Wireless Network using Artificial Bee Colony
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In mobile communication systems, location management deals with the location determination of users in a network. One of the strategies used in location management is to partition the network into location areas. Each location area consists of a group of cells. The goal of location management is to partition the network into a number of location areas such that the total paging cost and handoff (or update) cost is a minimum. Finding the optimal number of location areas and the corresponding configuration of the partitioned network is a difficult combinatorial optimization problem. This cell grouping problem is to find a compromise between the location update and paging operations such that the cost of mobile terminal location tracking is a minimum in location area wireless network. In fact, this is shown to be an NP-complete problem in an earlier study. In this paper, artificial bee colony (ABC) is developed and proposed to obtain the best/optimal group of cells for location area planning for location management system. The performance of the artificial bee colony (ABC) is better than or similar to those of other population-based algorithms with the advantage of employing fewer control parameters. The important control parameter of ABC is only ‘Limit’ which is the number of trials after which a food source is assumed to be abandoned. Simulation results for 16, 36, and 64 cell grouping problems in wireless network show that the performance of our ABC is better than those alternatives such as ant colony optimization (ACO) and particle swarm optimization (PSO).
Abstract
In mobile communication systems, location management deals with the location determination of users in a network. One of the strategies used in location management is to partition the network into location areas. Each location area consists of a group of cells. The goal of location management is to partition the network into a number of location areas such that the total paging cost and handoff (or update) cost is a minimum. Finding the optimal number of location areas and the corresponding configuration of the partitioned network is a difficult combinatorial optimization problem. This cell grouping problem is to find a compromise between the location update and paging operations such that the cost of mobile terminal location tracking is a minimum in location area wireless network. In fact, this is shown to be an NP-complete problem in an earlier study. In this paper, artificial bee colony (ABC) is developed and proposed to obtain the best/optimal group of cells for location area planning for location management system. The performance of the artificial bee colony (ABC) is better than or similar to those of other population-based algorithms with the advantage of employing fewer control parameters. The important control parameter of ABC is only ‘Limit’ which is the number of trials after which a food source is assumed to be abandoned. Simulation results for 16, 36, and 64 cell grouping problems in wireless network show that the performance of our ABC is better than those alternatives such as ant colony optimization (ACO) and particle swarm optimization (PSO).
참고문헌 (18)
- 백동현, "유비쿼터스 환경에서 위치기반서비스의 활용성 연구", 산업경영시스템학회지, 30(3), pp.1~11 (2007), 한국산업경영시스템학회
- Bhattacharjee, P. S., "An Approach for Location Area Planning in a Personal Communication Services Network(PCSN)", IEEE Trans, On Wireless Communications, 3(4), pp.1176~1187 (2004)
- 변지환, "파티클군집최적화 방법을 적용한 위치관리시스템 최적 설계", 경영과학, 29(1), pp.143~152 (2012), 한국경영과학회
- 천수봉, "유비쿼터스 홈 네트워크 주거환경만족도 증진을 위한 구조방정식 모형 연구", 품질경영학회지, 35(4), pp.26~37 (2007), 한국품질경영학회
- Demirkol, I., "Location Area Planning and cell-to-switch assignment in cellular networks", IEEE Trans, On Wireless Communications, 3(3), pp.880~890 (2004)
- Hac, A., "Locating strategies for personal communication networks : A novel tracking strategy", IEEE J, Selected Areas in Comm., 15(8), pp.1425~1436 (1997)
- Karaboga, D., "A comparative study of Artificial Bee Colony algorithm", Applied Mathematics and Computation, 214(1), pp.108~132 (2009)
- Karaboga, D., "A powerful and efficient algorithm for numerical function optimization: artificial bee colony(ABC) algorithm", Journal of Global Optimization, 39(3), pp.459~471 (2007)
- Karaboga, D., "On the performance of artificial bee colony(ABC) algorithm", Applied Soft Computing, 8(1), pp.687~697 (2008)
- 김성수, "리포팅셀 위치 관리 시스템 최적 설계를 위한 개선된 이진 인공벌 군집 알고리즘 개발", Telecommunications Review, 22(2), pp.287~297 (2012), SK텔레콤[DOI]
- Kim, S., "A grouping biogeography-based optimization for location area planning", Neural Computing and Applications, 26(8), pp.2001~2012 (2015)
- 김성수, "개미군 최적화 방법을 이용한 Location Area Planning", 경영과학, 25(2), pp.73~80 (2008), 한국경영과학회
- Merchant, A., "Assignment of Cells to Switches in PCS Networks", IEEE, 1995, pp.3(5), 521~526
- Pierre, S., "Assigning Cells to Switches in Cellular Mobile Networks Using Taboo Search", IEEE Trans, on Systems, Man, and Cybernetics Part B : Cybernetics, 32(3), pp.351~356 (2002)
- Prajapati, N.B., "Dynamic location area planning in cellular network using Apriori algorithm", 2015 ICIC, pp.660~662 (2015)
- Quintero, A., "Evolutionary approach to optimize the assignment of cells to switches in personal communication networks", Computer Communications, 26(9), pp.927~938 (2003)
- 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)
- Taheri, J., "A Simulated Annealing approach for mobile location management", Computer Communications, 30(4), pp.714~730 (2007)
