Online Scheduling with Interval Conflicts

Magnús M. Halldórsson, Boaz Patt-Shamir, Dror Rawitz

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


In the problem of Scheduling with Interval Conflicts, there is a ground set of items indexed by integers, and the input is a collection of conflicts, each containing all the items whose index lies within some interval on the real line. Conflicts arrive in an online fashion. A scheduling algorithm must select, from each conflict, at most one survivor item, and the goal is to maximize the number (or weight) of items that survive all the conflicts they are involved in. We present a centralized deterministic online algorithm whose competitive ratio is O(lgσ), where σ is the size of the largest conflict. For the distributed setting, we present another deterministic algorithm whose competitive ratio is 2⌈lg σ⌉ in the special contiguous case, in which the item indices constitute a contiguous interval of integers. Our upper bounds are complemented by two lower bounds: one that shows that even in the contiguous case, all deterministic algorithms (centralized or distributed) have competitive ratio Ω(lgσ), and that in the non-contiguous case, no deterministic oblivious algorithm (i.e., a distributed algorithm that does not use communication) can have a bounded competitive ratio.

Original languageEnglish
Pages (from-to)300-317
Number of pages18
JournalTheory of Computing Systems
Issue number2
StatePublished - Aug 2013
Externally publishedYes

Bibliographical note

Funding Information:
An extended abstract was presented at the 28th International Symposium on Theoretical Aspects of Computer Science (STACS), 2011. M.M. Halldórsson supported in part by the Icelandic Research Fund (grant 90032021). B. Patt-Shamir and D. Rawitz research supported in part by the Next Generation Video (NeGeV) Consortium, Israel. B. Patt-Shamir supported in part by the Israel Science Foundation (grant 1372/09) and by a grant from Israel Ministry of Science and Technology.


  • Competitive analysis
  • Compound tasks
  • Distributed algorithms
  • Interval conflicts
  • Online scheduling
  • Online set packing


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