| Co-Investigator(Kenkyū-buntansha) |
FENG Wei Nagoya Institute of Technology, Assistant Professor, 工学部, 講師 (30252307)
OHI Fumio Nagoya Institute of Technology, Professor, 工学部, 教授 (60116001)
KOWADA Masashi Nagoya Institute of Technology, Professor, 文化情報学部, 教授 (80015875)
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| Research Abstract |
ATM(Asynchrpnous Transfer Mode) 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 ATM traffics in such network systems has very complicated properties -chaos, self-similarity, long-terms dependence and diverse quality of service (QoS) requirements. In general, 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. Determining the rare event probability becomes very important. As a powerful technique in estimating rare event probability, the large deviation theory and approach have received remarkable attention.
This study consider an ATM network consisting of two-parallel queue which is important in modeling a communication system with two different types of the traffic: real-time traffic(such as voice and video) and non-real-time traf」Lc(such as data). We analyzed the systems as polling models unde
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r the.various service schedules.
(I) The arrival processes are Poisson processes, and the service time distributions are exponential. (1) m servers serve the two queues according to an (M,N)-threshold service schedule under the (I) non-preemptive priority and (ii) preemptive priority. (2) Two servers serve the two queues according to (I) Threshould-based control service schedule and (ii) Hyteretic control service schedule. (3) Under the general service distribution, one server serves the two queues according to an (M,N)-threshold service schedule. We derived the generating functions of the stationary joint queue-length distributions, and obtain the packet loss probabilities.
(II) Using large deviation technique, we derive the upper and lower bounds of the packet loss probabilities for a discrete-time fluid polling system with Markov-modulated arrival processes and Bernoulli service schedule.
(III) Using the upper and lower bounds of the packet loss probabilities obtained in (II), we present an admission control algorithm for a polling system with general arival processes and multi-server. Less
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