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Fluid approximation for generalized Jackson network with vacations

Fluid approximation for generalized Jackson network with vacations
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摘要 Using a bounding technique, we prove that the fluid model of generalized Jackson network (GJN) with vacations is the same as a GJN without vacations, which means that vacation mechanism does not affect the dynamic performance of GJN under fluid approximation. Furthermore, in order to present the impact of vacation on the performance of GJN, we show that exponential rate of convergence for fluid approximation only holds for large N, which is different from a GJN without vacations. The results on fluid approximation and convergence fate are embodied by the queue length, workload, and busy time processes. Using a bounding technique, we prove that the fluid model of generalized Jackson network (GJN) with vacations is the same as a GJN without vacations, which means that vacation mechanism does not affect the dynamic performance of GJN under fluid approximation. Furthermore, in order to present the impact of vacation on the performance of GJN, we show that exponential rate of convergence for fluid approximation only holds for large N, which is different from a GJN without vacations. The results on fluid approximation and convergence fate are embodied by the queue length, workload, and busy time processes.
作者 Yongjiang GUO
机构地区 School of Science
出处 《Frontiers of Mathematics in China》 SCIE CSCD 2012年第3期459-485,共27页 中国高等学校学术文摘·数学(英文)
关键词 Generalized Jackson network (GJN) with vacations fluid approxi-mation exponential convergence rate Generalized Jackson network (GJN) with vacations, fluid approxi-mation, exponential convergence rate
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