Analysis and design of communication systems in today's dynamically changing environment face a lot of challenges. Networks can become overloaded at one moment and underutilized at the next. In a randomly changing environment, such as time-varying arrivals, variable bandwidth demands, data traffic integrated with streaming traffic, and burst traffic with correlated arrivals, performance and dimensioning issues become very complicated. Little research has been carried out on dimensioning a system in such an environment to meet quality of service requirement. In this dissertation, one of our contributions is providing efficient dimensioning algorithms in closed-form with a constant or near linear complexity. Analytical models and efficient dimensioning algorithms are then proposed for different Scenarios.
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Dr. Tian finished his PhD program from the department of Computer Science of North Carolina State University (NCSU) in Dec. of 2007, then continued a post-doc program with joint funding from oak ridge national lab and NCSU. His research interests include performance analysis and efficient dimensioning algorithms for different networks.
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