On-line machine covering

Yossi Azar, Leah Epstein

Research output: Contribution to journalArticlepeer-review

Abstract

We consider the problem of scheduling a sequence of jobs on m parallel identical machines so as to maximize the minimum load over the machines. This situation corresponds to a case that a system which consists of the m machines is alive (i.e. productive) only when all the machines are alive, and the system should be maintained alive as long as possible. It is well known that any on-line deterministic algorithm for identical machines has a competitive ratio of at least m and that greedy is an m competitive algorithm. In contrast we design an on-line randomized algorithm which is O(√m log m) competitive and a lower bound of Ω(√m) for any on-line randomized algorithm. In the case where the weights of the jobs are polynomially related we design an optimal O (log m) competitive randomized algorithm and a matching tight lower bound for any on-line randomized algorithm. In fact, if F is the ratio between the weights of largest job and the smallest job then our randomized algorithm is O(log F) competitive. A sub-problem that we solve which is interesting in its own right is the problem where the value of the optimal algorithm is known in advance. Here we show a deterministic (constant) 2-(1/m) competitive algorithm. We also show that our algorithm is optimal for two, three and four machines and that no on-line deterministic algorithm can achieve a better competitive ratio than 1·75 for m ≥ 4 machines.

Original languageEnglish
Pages (from-to)67-77
Number of pages11
JournalJournal of Scheduling
Volume1
Issue number2
DOIs
StatePublished - 1998
Externally publishedYes

Keywords

  • Competitive ratio
  • Load
  • Machine covering
  • On-line

ASJC Scopus subject areas

  • Software
  • Engineering (all)
  • Management Science and Operations Research
  • Artificial Intelligence

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