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Distributed Computing

, Volume 32, Issue 1, pp 27–40 | Cite as

Distributed approximation of k-service assignment

  • Magnús M. Halldórsson
  • Sven KöhlerEmail author
  • Dror Rawitz
Article
  • 387 Downloads

Abstract

We consider the k-Service Assignment problem (\(k\)-SA). The input consists of a network that contains servers and clients. Associated with each client is a demand and a profit. In addition, each client c has a service requirement Open image in new window , where \(\kappa (c)\) is a positive integer. A client c is satisfied only if its demand is handled by exactly \(\kappa (c)\) neighboring servers. The objective is to maximize the total profit of satisfied clients, while obeying the given capacity limits of the servers. We focus here on the more challenging case of hard constraints, where no profit is granted for partially satisfied clients. This models, e.g., when a client wants, for reasons of fault tolerance, a file to be stored at \(\kappa (c)\) or more nearby servers. Other motivations from the literature include resource allocation in 4G cellular networks and machine scheduling on related machines with assignment restrictions. In the r-restricted version of \(k\)-SA, no client requires more than an r-fraction of the capacity of any adjacent server. We present a (centralized) polynomial-time Open image in new window -approximation algorithm for r-restricted \(k\)-SA. A variant of this algorithm achieves an approximation ratio of Open image in new window when given a resource augmentation factor of \(1+r\). We use the latter result to present a Open image in new window -approximation algorithm for \(k\)-SA. In the distributed setting, we present: (i) a Open image in new window -approximation algorithm for r-restricted \(k\)-SA, (ii) a Open image in new window -approximation algorithm that uses a resource augmentation factor of \(1+r\) for r-restricted \(k\)-SA, both for any constant \(\varepsilon >0\), and (iii) an Open image in new window -approximation algorithm for \(k\)-SA (in expectation). The three distributed algorithms run in \(O(k^2 \varepsilon ^{-2} \log ^3 n)\) synchronous rounds (with high probability). In particular, this yields the first distributed Open image in new window -approximation of \(1\)-SA.

Notes

Acknowledgements

We thank Boaz Patt-Shamir for helpful discussions.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  1. 1.ICE-TCS, School of Computer ScienceReykjavik UniversityReykjavikIceland
  2. 2.Faculty of EngineeringUniversity of FreiburgFreiburg im BreisgauGermany
  3. 3.Faculty of EngineeringBar-Ilan UniversityRamat GanIsrael

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