Improved Approximations for Stochastic Loss Networks J. Anselmi INRIA and LIG Laboratory MontBonnot Saint-Martin, 38330, FR jonatha.anselmi@imag.fr Y. Lu, M. Sharma, M.S. Squillante Mathematical Sciences Department IBM Thomas J. Watson Research Center Yorktown Heights, NY 10598, USA {yingdong,mxsharma,mss}@us.ibm.com 1. INTRODUCTION Stochastic loss networks (SLNs) are often a very effective model for studying the random dynamics of systems requiring simultaneous resource possession. Given a loss network and a multi-class customer workload, the classical Erlang model renders the stationary probability that a customer will be lost due to insuf cient capacity for at least one required resource type. Unfortunately, the problem of evaluating the exact (multi-dimensional) Erlang formula is known to be P -complete in the network size [5], thus rendering the exact formula of limited use for many large networks in practice. The well-known Erlang xed-point approximation (EFPA) has been developed and extensively used and studied as a tractable alternative approach for calculating the stationary loss probabilities. The popularity of the EFPA can be attributed to the fact that, in addition to its favorable theoretical properties, the estimates provided by the method have been found to be remarkably accurate in some traditional application areas such as large communication
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Improved Approximations for Stochastic Loss Networks
Anselmi, J.; Lu, Y.; Sharma, M.; Squillante, M. S.
Follow ACM SIGMETRICS Performance Evaluation Review
, Volume 37 (2)
Association for Computing Machinery – Oct 16, 2009
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