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ABSTRACT
We study the competitiveness of online deadline scheduling problems. It is assumed that jobs are non-preemptive and we want to maximize, in an online manner, the sum of the length of jobs completed before their deadlines. When there is a single machine, Goldwasser [4] showed that the optimal deterministic competitiveness of this problem is 2+1/k, where each job of length L can be delayed for at least k • L before it is started, while still meeting its deadline. We consider the case that k < 1 and present an O((log 1/k ))-competitive randomized algorithm not only for a single machine but also for m machines where m = 1,2,•••, O(( log 1/k )).Of particular interest is our technique: we mainly consider deterministic algorithms for multiple machines in order to improve the randomized competitiveness for a single (or more) machine. Though this approach is not completely new, it is rather complicated in our case to design a deterministic algorithm for multiple machines. Specifically, we present an [m+1+ m • (1/k)(1/m)]-competitive deterministic algorithm, where m (≥ 2) machines are available to both online algorithms and the adversary.Finally we also study a related problem and present an improved algorithm. REFERENCES
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"William A Fahle : Reviewer"
An algorithm for online scheduling across multiple connected machines is described in this paper. This algorithm maximizes the total job length of all jobs completed before their deadline, as opposed to some other metric, like maximizing the total
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