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Multi-processor scheduling to minimize flow time with ε resource augmentation

机译:多处理器调度可通过ε资源增加来最大程度地减少流动时间

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We investigate the problem of online scheduling of jobs to minimize flow time and stretch on m identical machines. We consider the case where the algorithm is given either (1+ε)m machines or m machines of speed (1+ε), for arbitrarily small ε 0. We show that simple randomized and deterministic load balancing algorithms, coupled with simple single machine scheduling strategies such as SRPT (shortest remaining processing time) and SJF (shortest job first), are O(poly(1/ε))-competitive for both flow time and stretch. These are the first results which prove constant factor competitive ratios for flow time or stretch with arbitrarily small resource augmentation. Both the randomized and the deterministic load balancing algorithms are non-migratory and do immediate dispatch of jobs.The randomized algorithm just allocates each incoming job to a random machine. Hence this algorithm is non-clairvoyant, and coupled with SETF (shortest elapsed time first), yields the first non-clairvoyant algorithm which is constant competitive for minimizing flow time with arbitrarily small resource augmentation. The deterministic algorithm that we analyze is due to Avrahami and Azar. For this algorithm, we show O(1/ε)-competitiveness for total flow time and stretch, and also for their Lp norms, for any fixed p ≥ 1.
机译:我们调查作业的在线调度问题,以最大程度地减少流动时间并在m台相同的机器上进行拉伸。对于任意小的ε> 0,我们考虑给定算法为(1 +ε)m个机器或m个速度为(1 +ε)的机器的情况。我们证明了简单的随机确定性负载均衡算法,以及简单的单机负载均衡算法。机器调度策略,例如SRPT(最短剩余处理时间)和SJF(最短作业优先),在流动时间和拉伸方面都具有O(poly(1 /ε))竞争性。这些都是第一个结果,证明了对于流动时间或拉伸的恒定因子竞争比,并且具有任意小的资源增加。随机负载均衡算法和确定性负载均衡算法都是非迁移性的,可以立即分派作业。随机算法只是将每个传入的作业分配给随机机器。因此,该算法是非透视的,并且与SETF(最短的经过时间最短)结合,产生了第一个非透视的算法,该算法在以任意小的资源增加来最小化流时间方面一直具有竞争力。我们分析的确定性算法归功于Avrahami和Azar。对于此算法,对于任何固定p≥1,我们都显示了O(1 /ε)-竞争性的总流动时间和拉伸力,以及它们的L p 范数。

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