B. Tsybakovand N. D. Georganas. Self-similar traffic and upper bounds to buffer overflow in an ATM queue. Performance Evaluation, 36(1):57--80, 1998.  Home/Search   Document Not in Database   Summary   Related Articles

....[22, 23] and is the topic of on going work. xii SELF SIMILAR NETWORK TRAFFIC: AN OVERVIEW 1.2. 3 Queueing analysis In the third category are works that provide mathematical models of long range dependent traffic with a view toward facilitating performance analysis in the queueing theory sense [2, 3, 17, 43, 49, 53, 66]. These works are important in that they establish basic performance boundaries by investigating queueing behavior with long range dependent input which exhibit performance characteristics fundamentally different from corresponding systems with Markovian input. In particular, the queue length ....

....has a slower than exponentially (or subexponentially) decreasing tail, in stark contrast with short range dependent input for which the decay is exponential. In fact, depending on the queueing model under consideration, long range dependent input can give rise to Weibullian [49] or polynomial [66] tail behavior of the underlying queue length distributions. The analysis of such non Markovian queueing systems is highly nontrivial and provides fundamental insight into the performance impact question. Of course, these works, in addition to providing valuable information into network ....

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B. Tsybakovand N. D. Georganas. Self-similar traffic and upper bounds to buffer overflow in an ATM queue. Performance Evaluation, 36(1):57--80, 1998.

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