DOI QR코드

DOI QR Code

Performance Analysis of Improved ZMHB Algorithms for Wireless Networks

무선망에서 개선된 ZMHB 알고리즘의 성능 평가

  • Published : 2004.10.01

Abstract

Handoff is one of the most important features for the user's mobility in a wireless cellular communication system. It is related to resource reservation at nearby cells. Resource reservation to the new connection point should occur prior to handoff to enable the user to receive the data or services at the new location, at the same level of service as at the previous location. For the efficient resource reservation, mobility prediction has been reported as an effective means to decrease the call dropping probability and to shorten the handoff latency in a wireless cellular environment. A recently proposed algorithm, ZMHB, makes use of the history of the user's positions within the current cell to predict the next cell. But, the prediction of the ZMHB algorithm is found to be 80∼85% accurate for regular and random movements. In this paper, we propose a new improved ZMHB mobility prediction algorithm, which is called Detailed-ZMHB that uses detailed-zone-based tracking of mo-bile users to predict user movements. The effectiveness of the proposed algorithm is then demonstrated through a simulation.

핸드오프는 무선 셀룰러 환경에서 사용자의 이동성(Mobility)을 유지해줄 수 있는 가장 중요한 기술중의 하나이다. 핸드오프 기술은 사용자가 이동할 주변 셀에 대한 대역폭 예약과 관련이 있다. 또한, 대역폭 예약은 사용자가 이동한 새로운 영역에서 이전 영역에서와 같은 레벨의 데이터나 서비스를 받기 위해서 핸드오프 이전에 실시되어야 한다. 이러한 무선 셀룰러 환경에서 효과적으로 대역폭을 사용하기 위하여 사용자의 이동성을 예측하는 기술은 핸드오프 호의 실패율(Dropping Probability)과 핸드오프 지연(Latency)을 줄이는 효과적인 방법이다. 최근에 제시된 ZMHB 알고리즘은 기존의 알고리즘과는 달리 셀 내부의 이동 경로를 저장한 히스토리를 이용하여 사용자가 이동할 셀을 예측하였다. 그러나, 모든 사용자에 대하여 80~85% 정도의 예측 정확도만을 보인다. 본 논문에서는 ZMHB 알고리즘에서 사용하는 존(Zone)을 세분화하여 이동 패턴을 저장하고, 이를 예측에 이용하는 Detailed-ZMHB 예측 알고리즘을 제안하고 성능 평가 결과를 보인다.

Keywords

References

  1. A. Jayasuriya, J. Asenstorfer, 'Mobility Prediction Model for Cellular Networks Based on The Observed Traffic Patterns,' in Proc. International Conference on Wireless and Optical Communication, 2002
  2. H. Kim and C. Moon, 'A Rerouting Strategy for Handoff on ATM-based Transport Network,' in Proc. IEEE 47th Vehicular Technology Conference, pp.285-289, 1997 https://doi.org/10.1109/VETEC.1997.596365
  3. S. Bush, 'A Control and Management Network for Wireless ATM Systems,' in Proc. IEEE ICC'96, pp.459-463, 1996 https://doi.org/10.1109/ICC.1996.542240
  4. J. Chan, R. De Silva and A. Senevirance, 'A QoS Adaptive Mobility Prediction Scheme for Wireless Networks,' In Proc. IEEE GLOBECOM'98, pp.1414-1419, Nov., 1998 https://doi.org/10.1109/GLOCOM.1998.776573
  5. J. Chan, et al., 'A Hybrid Handoff Scheme with Prediction Enhancement for Wireless ATM Network,' in Proc. APCC'97, pp.494-498, Dec., 1997
  6. V. Bharghavan and J. Mysore, 'Profile Based Next-cell Prediction in Indoor Wireless LAN,' in Proc. IEEE SICON'97, Apr., 1997
  7. G. Liu and G. Maguire Jr., 'A Class of Mobile Motion Prediction Algorithms for Wireless Mobile Computing and Communications,' in ACM/Baltzer MONET, Vol.1, No.2, pp.113-121, 1996 https://doi.org/10.1007/BF01193332
  8. T. Liu, P. Bahl and I. Chlamtac, 'Mobility Modeling, Location Tracking and Trajectory Prediction in Wireless ATM Networks,' IEEE JAC, Vol.16, No.6, pp.922-936, Aug., 1998 https://doi.org/10.1109/49.709453
  9. D. Levine, I. Akyildiz and M. Naghshineh, 'A Resource Estimation and Call Admission Algorithm for Wireless Multimedia Networks Using the Shadow Cluster Concept,' IEEE/ACM Trans. on Networking, Vol.5, No.1, pp.1-12, Feb., 1997 https://doi.org/10.1109/90.554717
  10. A Practical User Mobility Prediction Algorithm for Supporting Adaptive QoS in Wireless Networks, IEEE International Conference on Networks, pp.104-110, Sep., 1999 https://doi.org/10.1109/ICON.1999.796167
  11. J. Jannink, D. Lam, N. Shivakumar, J. Widom and D. Cox, 'Efficient and Flexible Location Management Techniques for Wireless Communication System,' ACM/Baltzer Wrieless Networks, Vol.3, No.5, pp.361-374, 1997 https://doi.org/10.1023/A:1019186024044
  12. W. Cui and X. Shen, 'User Movement Tendency Prediction and Call Admission Control for Mobile Cellular Networks,' in Proc. IEEE ICC'2000, pp.670-674 https://doi.org/10.1109/ICC.2000.853584
  13. F. Erbas, J. Steuer, K. Kyamakya, D. Eggesieker and K. Jobmann, 'A Regular path Recognition Method and Prediction of User Movements in Wireless Networks,' VTC Fall 2001, Mobile Technology for Third Millenium https://doi.org/10.1109/VTC.2001.957245
  14. W. T. Poon and E. Chan, 'Traffic Management in Wireless ATM Network Using a Hierarchical Neural-Network Based Prediction Algorithm,' in Proc. ICSA 15th International Conference on Computers and their Applications, March, 2000
  15. R. Chellappa, A. Jennings and N. Shenoy, 'The Sectorized Mobility Prediction Algorithm for Wireless Networks,' ICT, pp.86-92, April, 2003
  16. R. Chellappa, A. Jennings and N. Shenoy, 'A Comparative Study of Mobility Prediction in Fixed Wireless Networks and Mobile Ad hoc Networks,' IEEE., 2003 https://doi.org/10.1109/ICC.2003.1204465
  17. 권세동, 박현민, '셀룰러 망에서 QoS 보장을 위한 사용자 이동성 예측 기법의 제안 및 성능 분석,' 한국통신학회 '03 추계종합학술발표회논문집, 한국통신학회, p.421, Dec., 2003
  18. 권세동, 박현민, '무선 네트워크에서 사용자 이동 패턴을 사용한 이동성 예측 기법.' 정보처리학회논문지C, 제11-C권 제2호, pp.193-202, Apr., 2004 https://doi.org/10.3745/KIPSTC.2004.11C.2.193
  19. 이종찬, 이문호, 문영성, 'PCS를 위한 이동체 위치 추정 기법,' 한국통신학회논문집, pp.2080-2089, Aug., 1998
  20. Q. A. Zeng and Dharma P. Agrawal, 'Handbook of Wireless and Mobile Computing,' John Wiley & Sons, Inc., 2002
  21. D. Collins and C. Smith, '3G Wireless Networks,' McGraw Hill, 2001
  22. A. J. Viterbi, 'CDMA : Principles of Spread Spectrum Communication, Reading, Mass,' Addison-Wesley, 1995
  23. S. Choi and K. G. Shin, 'Adaptive Bandwidth Reservation and Admission Control in QoS-Sensitive Cellular Networks,' IEEE Transactions on Parallel Distributed Systems, Vol.13, No.9, pp. 882-897, Sep., 2002 https://doi.org/10.1109/TPDS.2002.1036063