Admission Control for ATM High-Speed Networks

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ATM(Asynchronous Transfer Mode) high-speed networks accommodate various types of traffic such as digitized voice, movie, encoded video and data, etc. Recently, it has been reported by many researchers that traffics in ATM high-speed networks have many complicated properties-self-similarity and long-terms dependence, etc. Furthermore, as the criterion for evaluating QoS(quality of service) of such ATM networks, the packet loss probabilities due to the buffer overflow are required to control below very small level, e.g., in the order of 10^<-9>. Thus, determining the rare event probability and performing the admission control become very important in order to provide the guarantee of QoS requirements for ATM high-speed networks.In the present study, we have considered ATM high-speed networks consisting of two-parallel queues, which are generally used in modeling communication systems with two different types of the traffics : real-time traffic(such as voice and video) and non-real-time t … More raffic(such as data). We analyzed the tail behavior of the systems under various arrival processes. Then, we derived the upper and lower bounds of the buffer overflow probabilities using the large deviations techniques, and provided the admission control algorithms. We also carried out the performance analysis for wireless mobile networks by using the finite buffer queueing models with the guard channels. Concretely, we have analyzed the following systems.(I)(1)the discrete-time polling system with two classes and a single server. The arrival processes are Markov-modulated processes and the service schedule is Bernoulli. (2)the discrete-time polling system with two classes and multiple servers. The arrival processes are general and the service schedule is Markovian. For those two polling systems, we derived the large deviations upper and lower bounds of the packet loss probabilities and presented the admission control algorithm.(II)For Markovian polling systems, we derived the large deviations upper and lower bounds of the packet loss probabilities, and applied the results to wireless mobile networks.(III)We modeled wireless mobile networks by using finite buffer queueing models, and derived the steady-state distributions using recursive algorithm approach. Less