On Throughput in Stochastic Linear Loss Networks Petar MomË ilovi´ c c Dept. of Elect. Eng. and Comp. Sci. University of Michigan Ann Arbor, MI 48105 Mark S. Squillante Mathematical Sciences Department IBM T.J. Watson Research Center Yorktown Heights, NY 10598 petar@eecs.umich.edu mss@watson.ibm.com 1. INTRODUCTION Performance scalability is one of the central problems in designing large-scale systems as well as emerging applications. It is therefore of critical importance to understand fundamental properties of various performance characteristics as the size of the multi-node system grows while the local resources of each node remain xed. In particular, there is a strong need for developing a precise mathematical foundation for investigating performance scalability, which is even more apparent since building experimental large-scale systems and conducting experimental studies on such systems is very expensive or practically infeasible. A theoretical approach has a unique advantage for providing insights into the performance scaling properties of large systems with limited local resources. In this paper we investigate fundamental properties of various performance characteristics in stochastic linear loss networks and the asymptotic scaling of these properties as the size of the network grows. Within the context of this class of stochastic tandem networks, an expression for
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On throughput in stochastic linear loss networks
Momčilović, Petar; Squillante, Mark S.
Follow ACM SIGMETRICS Performance Evaluation Review
, Volume 36 (2)
Association for Computing Machinery – Aug 31, 2008
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