Online algorithms for maximizing weighted throughput of unit jobs with temperature constraints

We consider a temperature-aware online deadline scheduling model. The objective is to schedule a number of unit jobs, with release dates, deadlines, weights and heat contributions, to maximize the weighted throughput subject to a temperature threshold. We first give an optimally competitive randomiz...

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Bibliographic Details
Published inJournal of combinatorial optimization Vol. 26; no. 2; pp. 237 - 250
Main Authors Birks, Martin, Cole, Daniel, Fung, Stanley P. Y., Xue, Huichao
Format Journal Article
LanguageEnglish
Published Boston Springer US 01.08.2013
Subjects
Combinatorics
Convex and Discrete Geometry
Mathematical Modeling and Industrial Mathematics
Mathematics
Mathematics and Statistics
Operations Research/Decision Theory
Optimization
Theory of Computation
Resource augmentation
Online algorithms
Temperature
Scheduling
Competitive analysis
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Summary:We consider a temperature-aware online deadline scheduling model. The objective is to schedule a number of unit jobs, with release dates, deadlines, weights and heat contributions, to maximize the weighted throughput subject to a temperature threshold. We first give an optimally competitive randomized algorithm. Then we give a constant competitive randomized algorithm that allows a tradeoff between the maximum heat contribution of jobs and the competitiveness. Finally we consider the multiple processor case and give several tight upper and lower bounds.
ISSN:1382-6905
1573-2886
DOI:10.1007/s10878-012-9543-2