A queueing-theoretic model for resource allocation in one-dimensional distributed analytics network?
ACM SIGMETRICS Performance Evaluation Review(2018)
摘要
We consider the problem of allocating requesters of analytic tasks to resources on servers. We assume both requesters and servers are placed in a one dimensional line: [0,1) according to two Poisson processes with each server having finite capacity. Requesters communicate with servers under a noninterference wireless protocol. We consider a "Move to Right" (MTR) request allocation strategy where each requester is allocated to the nearest available server to its right. We start our analysis from a single resource per request scenario where each requester demands a single computational resource. We map this scenario to an M/M/1 queue or a bulk service M/M/1 queue depending on the server capacity. We compare the performance of the MTR strategy with the globally optimal strategy taking "expected distance traveled by a request" (request distance) as performance metric. Next, we extend our analysis to two resources per request scenario. We show that the behavior of MTR can be transformed into an equivalent fork-join queue problem. Numerical results are presented to validate the claim.
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