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Dataflow modelling in distributed diagnostic processing systems: a closed queuing network model with single servers

Abstract : In this paper, a closed queuing network model with single servers has been proposed to model dataflow in distributed diagnosticprocessing systems. Multi-threading is useful in reducing the latency by switching among a set of threads in order to improve the processor utilization. Two sets of processors, synchronization and execution processors exist. Synchronization processors handle load/store operations and execution processors handle arithmetic/logic and control operations. A closed queuing network model is suitable for large number of job arrivals. The normalization constant is derived using a recursive algorithm for the given model. Performance measures such as average response times and average system throughput are derived and plotted against the total number of processors in the closed queuing network model. Other important performance measures like processor utilizations, average queue lengths, average waiting times and relative utilizations are also derived.
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https://hal.univ-lorraine.fr/hal-03045168
Contributor : Kondo Adjallah <>
Submitted on : Monday, December 7, 2020 - 9:46:09 PM
Last modification on : Friday, December 25, 2020 - 6:10:02 PM

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  • HAL Id : hal-03045168, version 1

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Vidhyacharan Bhaskar, Kondo Hloindo Adjallah, Laurie Joiner. Dataflow modelling in distributed diagnostic processing systems: a closed queuing network model with single servers. International Journal of Pure and Applied Mathematics, Academic Publishing Ltd, 2005, 19 (2), pp.137-155. ⟨hal-03045168⟩

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