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Better Bounds for Online Load Balancing on Unrelated Machines

Overview This paper studies the problem of scheduling permanent jobs on un-related machines when the objective is to minimize the Lp norm of the machine loads. The problem is known as load balancing under the Lp norm. It presents an improved upper bound for the greedy algorithm through simple analysis; this bound is also shown to be best possible within the class of deterministic online algorithms for the problem. The paper also address the question whether randomization helps on-line load balancing under Lp norms on unrelated machines; this is a challenging question which is open for more than a decade even for the L2 norm.

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Publisher
University of Patras
File Format
PDF
Date Published
Jul 10, 2008
Format
White Papers
Topics
Diagnostics and Analysis, Load Balancing

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