Abstract
Motivated by the organization of distributed service systems, we study models for throughput scheduling in a decentralized setting. In throughput scheduling, a set of jobs j with values w j , processing times p ij on machine i, release dates r j and deadlines d j , is to be processed non-preemptively on a set of unrelated machines. The goal is to maximize the total value of jobs scheduled within their time window [r j ,d j ]. While approximation algorithms with different performance guarantees exist for this and related models, we are interested in the situation where subsets of machines are governed by selfish players. We give a universal result that bounds the price of decentralization: Any local α-approximation algorithm, α ≥ 1, yields Nash equilibria that are at most a factor (α + 1) away from the global optimum, and this bound is tight. For identical machines, we improve this bound to \({\sqrt[\alpha]{e}}/{(\sqrt[\alpha]{e}-1)}\approx (\alpha+1/2)\), which is shown to be tight, too. The latter result is obtained by considering subgame perfect equilibria of a corresponding sequential game. We also address some variations of the problem.
Research supported by CTIT, Centre for Telematics and Information Technology, University of Twente, project “Mechanisms for Decentralized Service Systems”.
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de Jong, J., Uetz, M., Wombacher, A. (2013). Decentralized Throughput Scheduling. In: Spirakis, P.G., Serna, M. (eds) Algorithms and Complexity. CIAC 2013. Lecture Notes in Computer Science, vol 7878. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38233-8_12
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DOI: https://doi.org/10.1007/978-3-642-38233-8_12
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