In multimedia cellular networks, when a Mobile Host requests multimedia services, it may experience hand-offs to several cells before the request is completely served. If a target cell cannot provide adequate bandwidt...In multimedia cellular networks, when a Mobile Host requests multimedia services, it may experience hand-offs to several cells before the request is completely served. If a target cell cannot provide adequate bandwidth for a service request, instead of directly dropping the request, the MH is put into the handoff queue and hopefully the requested bandwidth can be satisfied by later released bandwidth. Obviously, it is important to properly assign priorities for queued handoff of MHs based on their inborn dynamics to avoid unnecessary dropping. In this paper, we present a dynamic handoff priority adjustment scheme which applied a handoff queuing scheme to dynamically adjust handoff priority based on receiving signal strength, service class, and mobility of Mobile Hosts. In addition, idle bandwidth reserved by inactive MHs is reallocated to urgent handoff MHs to reduce the call dropping probability. The goal of the proposed dynamic handoff priority adjustment scheme is to further reduce call dropping probability while still maintaining high bandwidth utilization and acceptable call blocking probability on multimedia cellular networks.展开更多
This paper studies a queueing model with the finite buffer of capacity K in wireless cellular networks, which has two types of arriving calls--handoff and originating calls, both of which follow the Markov arriving pr...This paper studies a queueing model with the finite buffer of capacity K in wireless cellular networks, which has two types of arriving calls--handoff and originating calls, both of which follow the Markov arriving process with different rates. The channel holding times of the two types of calls follow different phase-type distributions. Firstly, the joint distribution of two queue lengths is derived, and then the dropping and blocking probabilities, the mean queue length and the mean waiting time from the joint distribution are gotten. Finally, numerical examples show the impact of different call arrival rates on the performance measures.展开更多
文摘In multimedia cellular networks, when a Mobile Host requests multimedia services, it may experience hand-offs to several cells before the request is completely served. If a target cell cannot provide adequate bandwidth for a service request, instead of directly dropping the request, the MH is put into the handoff queue and hopefully the requested bandwidth can be satisfied by later released bandwidth. Obviously, it is important to properly assign priorities for queued handoff of MHs based on their inborn dynamics to avoid unnecessary dropping. In this paper, we present a dynamic handoff priority adjustment scheme which applied a handoff queuing scheme to dynamically adjust handoff priority based on receiving signal strength, service class, and mobility of Mobile Hosts. In addition, idle bandwidth reserved by inactive MHs is reallocated to urgent handoff MHs to reduce the call dropping probability. The goal of the proposed dynamic handoff priority adjustment scheme is to further reduce call dropping probability while still maintaining high bandwidth utilization and acceptable call blocking probability on multimedia cellular networks.
基金supported by the Postgraduate Innovation Project of Jiangsu University (CX10B 003X)
文摘This paper studies a queueing model with the finite buffer of capacity K in wireless cellular networks, which has two types of arriving calls--handoff and originating calls, both of which follow the Markov arriving process with different rates. The channel holding times of the two types of calls follow different phase-type distributions. Firstly, the joint distribution of two queue lengths is derived, and then the dropping and blocking probabilities, the mean queue length and the mean waiting time from the joint distribution are gotten. Finally, numerical examples show the impact of different call arrival rates on the performance measures.
