Papers › Non-Asymptotic Delay Bounds for Multi-Server Systems with Synchronization Constraints

Non-Asymptotic Delay Bounds for Multi-Server Systems with Synchronization Constraints

20 Oct 2016arXiv:1610.06309links table onlyarchive 2025-07-28

Markus Fidler, Brenton Walker, Yuming Jiang

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Multi-server systems have received increasing attention with important implementations such as Google MapReduce, Hadoop, and Spark. Common to these systems are a fork operation, where jobs are first divided into tasks that are processed in parallel, and a later join operation, where completed tasks wait until the results of all tasks of a job can be combined and the job leaves the system. The synchronization constraint of the join operation makes the analysis of fork-join systems challenging and few explicit results are known. In this work, we model fork-join systems using a max-plus server model that enables us to derive statistical bounds on waiting and sojourn times for general arrival and service time processes. We contribute end-to-end delay bounds for multi-stage fork-join networks that grow in 𝒪(h lnk) for h fork-join stages, each with k parallel servers. We perform a detailed comparison of different multi-server configurations and highlight their pros and cons. We also include an analysis of single-queue fork-join systems that are non-idling and achieve a fundamental performance gain, and compare these results to both simulation and a live Spark system.

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