An Analysis of Location Management Cost by Predictive Location Update Policy in Mobile Cellular Networks

이동통신망에서 예측 위치 등록 정책을 통한 위치관리 비용 감소 효과 분석

  • Ko, Han-Seong (Industrial Engineering, Seoul National University) ;
  • Hong, Jung-Sik (Industrial and Information System Engineering, Seoul National University of Technology) ;
  • Chang, In-Kap (Industrial Engineering, Seoul National University) ;
  • Lie, Chang-Hoon (Industrial Engineering, Seoul National University)
  • 고한성 (서울대학교 산업공학과) ;
  • 홍정식 (서울산업대학교 산업정보시스템공학과) ;
  • 장인갑 (서울대학교 산업공학과) ;
  • 이창훈 (서울대학교 산업공학과)
  • Published : 2008.06.30

Abstract

MU's mobility patterns can be found from a movement history data. The prediction accuracy and model complexity depend on the degree of application of history data. The more data we use, the more accurate the prediction is. As a result, the location management cost is reduced, but complexity of the model increases. In this paper, we classify MU's mobility patterns into four types. For each type, we find the respective optimal number of application of history data, and predictive location area by using the simulation. The optimal numbers of four types are shown to be different. When we use more than three application of history data, the simulation time and data storage are shown to increase very steeply.

Keywords

References

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