A new location update strategy for cellular networks and its implementation using a genetic algorithm

A new location update strategy and its implementation using a genetic algorithm are proposed. Most of the practical cellular mobile systems partition a geographical region into location areas (LA) and users are made to update on entering a new LA. The main drawback of this scheme is that it does not consider the individual user mobility and call arrival patterns. Combining per-user mobility and call arrival patterns with the LAbased approach, an optimal update strategy is proposed for each user which determines whether or not to update in each LA. The update strategy minimizes the average location management cost derived from a user-specific mobility model and call generation pattern. The location management cost optimization problem is solved using a genetic algorithm. The results clearly demonstrate that for low user residing probability in LA’s, low call arrival rate and high update cost, skipping updation in several LA’s leads to minimization of the overall location management cost.

[1]  Kalyan Basu,et al.  Adaptive paging algorithms for cellular systems , 1995, 1995 IEEE 45th Vehicular Technology Conference. Countdown to the Wireless Twenty-First Century.

[2]  Xian Zhou,et al.  Locating Strategies for Personal Communication Networks: A Novel Tracking Strategy , 1997, IEEE J. Sel. Areas Commun..

[3]  Christopher Rose,et al.  Minimization of paging and registration costs through registration deadlines , 1995, Proceedings IEEE International Conference on Communications ICC '95.

[4]  Ian F. Akyildiz,et al.  Mobile user location update and paging under delay constraints , 1995, Wirel. Networks.

[5]  Roy D. Yates,et al.  Minimizing the average cost of paging under delay constraints , 1995, Wirel. Networks.

[6]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 2000, Springer Berlin Heidelberg.

[7]  P. Krishnan,et al.  Minimizing queuing delays and number of messages in mobile phone location , 1996, Mob. Networks Appl..

[8]  Dieter Plassmann.  Location management strategies for mobile cellular networks of 3rd generation , 1994, Proceedings of IEEE Vehicular Technology Conference (VTC).

[9]  Kenneth Steiglitz,et al.  Optimization of wireless resources for personal communications mobility tracking , 1994, Proceedings of INFOCOM '94 Conference on Computer Communications.

[10]  Mahmoud Naghshineh,et al.  Topology-based tracking strategies for personal communication networks , 1996, Mob. Networks Appl..

[11]  Sajal K. Das,et al.  Adaptive Location Prediction Strategies Based on a Hierarchical Network Model in a Cellular Mobile Environment , 1999, Comput. J..

[12]  Kenneth Steiglitz,et al.  Optimization of wireless resources for personal communications mobility tracking , 1995, TNET.

[13]  S. Subramanian,et al.  System partitioning in a cellular network , 1996, Proceedings of Vehicular Technology Conference - VTC.

[14]  David J. Goodman,et al.  Dynamic location area management and performance analysis , 1993, IEEE 43rd Vehicular Technology Conference.

[15]  Amotz Bar-Noy,et al.  Mobile users: To update or not to update? , 1995, Wirel. Networks.

[16]  Sheldon M. Ross,et al.  Introduction to Probability Models, Eighth Edition , 1972 .

[17]  Ivan Seskar,et al.  Rate of location area updates in cellular systems , 1992, [1992 Proceedings] Vehicular Technology Society 42nd VTS Conference - Frontiers of Technology.

[18]  Sheldon M. Ross,et al.  Introduction to probability models , 1975 .

[19]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1996, Springer Berlin Heidelberg.

[20]  Roy D. Yates,et al.  Analysis of a mobile-assisted adaptive location management strategy , 1996, Mob. Networks Appl..