(1 + ε)-approximate sparse recovery
Eric Price, David P. Woodruff
FOCS 2011
Boxma and Groenendijk have shown that the workload in polling models decomposes into two independent variables. This paper demonstrates a different type of decomposition that has an explicit multi-dimensional form. This decomposition does not apply to all polling models, but does, for example, apply to models with constant switch-over times and either exhaustive or gated service disciplines. For such models, we show that the population of customers present in the system (represented by a vector indicating the number of customers at each queue) at key time points breaks into two independent subpopulations: (1) the population of customers present in the related model with zero switch-over times; (2) another population, which is particularly easy to analyze. This result has a number of theoretical and applied implications. © 1992 J.C. Baltzer AG, Scientific Publishing Company.
Eric Price, David P. Woodruff
FOCS 2011
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