Movement-based location update and selective paging for PCS networks
IEEE/ACM Transactions on Networking (TON)
Reducing location update cost in a PCS network
IEEE/ACM Transactions on Networking (TON)
MobiCom '97 Proceedings of the 3rd annual ACM/IEEE international conference on Mobile computing and networking
Mobile users: to update or not to update?
Wireless Networks
Mobile user location update and paging under delay constraints
Wireless Networks
An activity-based mobility model and location management simulation framework
MSWiM '99 Proceedings of the 2nd ACM international workshop on Modeling, analysis and simulation of wireless and mobile systems
A selective location update strategy for PCS users
Wireless Networks
Efficient location area planning for cellular networks with hierarchical location databases
Computer Networks: The International Journal of Computer and Telecommunications Networking
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This paper introduces a dynamic location management algorithm with variable size location areas(LAs), which helps in reducing location update(LU) cost and hence total location management cost. Basically there are two types of location management strategies - Static and Dynamic. In the static strategy (used in GSM), LAs consist of static and arbitrarily defined collections of cells, which do not take into account individual subscriber's mobility pattern and hence these LAs remain same for all the subscribers. Since mobility pattern of an individualsubscriber may differ significantly, this approach is far from optimal. Proposed location management algorithm uses the mobility history of individual subscribers to dynamically form individualized LAs based on his previous movements from cell to cell. It defines the size ofLAs based on subscriber's speed and call arrival probability. An activity-based mobility model is developed to test the proposed algorithm and the performance of this algorithm is compared with other algorithms, like fixed location strategy, grid-based location management strategy and dynamic location management algorithm. Overall, the proposed algorithm incurred significantlylower location management cost, in terms of signalingmessages generated, as compared to all other algorithms.