Scheduling with Deadlines and Buffer Management with Processing Requirements

Yossi Azar*, Oren Gilon

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

We discuss the well known online job scheduling problem with release times and deadlines, alongside an extended model—buffer management for packets with processing requirements. For job scheduling, an Ω(logκloglogκ) lower bound on the competitive ratio of any randomized preemptive algorithm was shown by Canetti and Irani (Proceedings of the 27th annual ACM symposium on Theory of computing, ACM, pp 606–615, 1995), where κ is the the maximum job duration or the maximum job value (the minimum is assumed to be 1). The proof of this well-known result is fairly elaborate and involved. In contrast, we show a significantly improved lower bound of Ω(log κ) using a simple proof. Our result matches the easy upper bound and closes a gap which was supposedly open for 20 years. We also discuss the problem of handling a FIFO buffer of a limited capacity, where packets arrive over time and may be preempted. Most of the work in buffer management considers the case where each packet has unit processing requirement. We consider a model where packets require some number of processing cycles before they can be transmitted. We aim to maximize the value of transmitted packets. We show an Ω(logκloglogκ) lower bound on the competitive ratio of randomized algorithms in this setting. We also present bounds for several special cases. For packets with unit values we also show a φ≈ 1.618 lower bound on the competitive ratio of deterministic algorithms, and a 2-competitive algorithm. For the case of packets with constant densities we present a 4-competitive algorithm.

Original languageEnglish
Pages (from-to)1246-1262
Number of pages17
JournalAlgorithmica
Volume78
Issue number4
DOIs
StatePublished - 1 Aug 2017

Funding

FundersFunder number
Israel Science Foundation1506/16
Israeli Centers for Research Excellence4/11

    Keywords

    • Buffer management
    • Competitive analysis
    • Deadlines
    • Job scheduling
    • Online algorithms

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