Movement-based location update and selective paging for PCS networks
IEEE/ACM Transactions on Networking (TON)
Mobile users: to update or not to update?
Wireless Networks
Optimal location management for two-tier PCS networks
Computer Communications
A location-based mobility tracking scheme for PCS networks
Computer Communications
Improving the fault tolerance of GSM networks
IEEE Network: The Magazine of Global Internetworking
A Fault-Tolerant Scheme for Mobility Management in PCS Networks
Wireless Personal Communications: An International Journal
Bandwidth Sharing Schemes for Multimedia Traffic in the IEEE 802.11e Contention-Based WLANs
IEEE Transactions on Mobile Computing
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Mobility Databases, Home Location Register (HLR) and Visitor Location Register (VLR), are utilized to support mobility management for Mobile Stations (MSs) in Personal Communications Services (PCS) networks. If the location database fail, the subscribers' services will be seriously degraded due to the loss or corruption of location information. Previous work proposed demand re-registration with a p-persistent backoff strategy and a checkpoint method that demonstrates better performance than the periodic re-registration policy. In demand re-registration, after a VLR fails, it broadcasts a re-registration request to all MSs. Backoff strategies are needed since collisions may occur if all MSs try to re-register after receiving the request. Choosing a good backoff strategy for demand re-registration has several benefits that are our goals in this paper. A better strategy will save the re-registration traffic in terms of signaling cost. Moreover, a better strategy will allow an MS to re-register earlier to reduce the probability that a call termination with expensive paging operations happens earlier than location information recovery. In this paper, we propose and study seven backoff strategies for demand re-registration: one optimal p-persistent strategy, three dynamic p-persistent strategies, and three non-persistent strategies. Among these proposed strategies, the optimal p-persistent strategy is optimal in the sense of optimality among all the p-persistent strategies; the three dynamic p-persistent strategies improve p-persistent strategies by allowing the p-value to change with time; the three non-persistent strategies include a binary exponential backoff strategy, an exponential backoff strategy, and a non-exponential non-persistent backoff strategy; our studies show that they can be approximately equivalent to special dynamic p-persistent strategies. Our studies also show that one of the dynamic p-persistent backoff strategies is the best strategy among all the seven proposed strategies and our results indicate that with better backoff strategies, the performance of demand re-registration can be dramatically improved.