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New hardness results for congestion minimization and machine scheduling

Published: 01 September 2006 Publication History

Abstract

We study the approximability of two natural NP-hard problems. The first problem is congestion minimization in directed networks. In this problem, we are given a directed graph and a set of source-sink pairs. The goal is to route all the pairs with minimum congestion on the network edges. The second problem is machine scheduling, where we are given a set of jobs, and for each job, there is a list of intervals on which it can be scheduled. The goal is to find the smallest number of machines on which all jobs can be scheduled such that no two jobs overlap in their execution on any machine. Both problems are known to be O(log n/log log n)-approximable via the randomized rounding technique of Raghavan and Thompson [1987]. However, until recently, only Max SNP hardness was known for each problem. We make progress in closing this gap by showing that both problems are Ω(log log n)-hard to approximate unless NP ⊆ DTIME(nO(log log log n)).

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Published In

cover image Journal of the ACM
Journal of the ACM  Volume 53, Issue 5
September 2006
173 pages
ISSN:0004-5411
EISSN:1557-735X
DOI:10.1145/1183907
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 01 September 2006
Published in JACM Volume 53, Issue 5

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Author Tags

  1. Hardness of approximation
  2. congestion minimization
  3. network routing
  4. resource minimization
  5. scheduling

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