2015
DOI: 10.1016/j.tcs.2015.01.027
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Online parallel scheduling of non-uniform tasks: Trading failures for energy

Abstract: Abstract. Consider a system in which tasks of different execution times arrive continuously and have to be executed by a set of processors that are prone to crashes and restarts. In this paper we model and study the impact of parallelism and failures on the competitiveness of such an online system. In a fault-free environment, a simple Longest-in-System scheduling policy, enhanced by a redundancy-avoidance mechanism, guarantees optimality in a long-term execution. In the presence of failures though, scheduling… Show more

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Cited by 8 publications
(24 citation statements)
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References 39 publications
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“…See Figure 1 for a graph of our bounds. Note that we do not obtain tight bounds for s ∈ [2, 4), but we conjecture that using an appropriately adjusted non-local analysis of Theorem 4.1 (which shows 1-competitiveness for s = 4), it is possible to show that the algorithm is 4/s-competitive for s ∈ [2,4).…”
Section: Our Resultsmentioning
confidence: 86%
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“…See Figure 1 for a graph of our bounds. Note that we do not obtain tight bounds for s ∈ [2, 4), but we conjecture that using an appropriately adjusted non-local analysis of Theorem 4.1 (which shows 1-competitiveness for s = 4), it is possible to show that the algorithm is 4/s-competitive for s ∈ [2,4).…”
Section: Our Resultsmentioning
confidence: 86%
“…The model was introduced by Anta et al [1], who resolved it for two packet sizes: If γ > 1 denotes the ratio of the two sizes, then the optimum competitive ratio for deterministic algorithms is (γ + γ )/ γ , which is always in the range [2,3). This result was extended by Jurdzinski et al [10], who proved that the optimum ratio for the case of multiple (though fixed) packet sizes is given by the same formula for the two packet sizes which maximize it.…”
Section: Previous and Related Resultsmentioning
confidence: 99%
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