Scheduling jobs with unknown duration in clouds

Siva Theja Maguluri, Rayadurgam Srikant

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We consider a stochastic model of jobs arriving at a cloud data center. Each job requests a certain amount of CPU, memory, disk space, etc. Job sizes (durations) are also modeled as random variables, with possibly unbounded support. These jobs need to be scheduled non preemptively on servers. The jobs are first routed to one of the servers when they arrive and are queued at the servers. Each server then chooses a set of jobs from its queues so that it has enough resources to serve all of them simultaneously. This problem has been studied previously under the assumption that job sizes are known and upper bounded, and an algorithm was proposed which stabilizes traffic load in a diminished capacity region. Here, we present a load balancing and scheduling algorithm that is throughput optimal, without assuming that job sizes are known or are upper bounded.

Original languageEnglish (US)
Title of host publication2013 Proceedings IEEE INFOCOM 2013
Pages1887-1895
Number of pages9
DOIs
StatePublished - Sep 2 2013
Event32nd IEEE Conference on Computer Communications, IEEE INFOCOM 2013 - Turin, Italy
Duration: Apr 14 2013Apr 19 2013

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X

Other

Other32nd IEEE Conference on Computer Communications, IEEE INFOCOM 2013
CountryItaly
CityTurin
Period4/14/134/19/13

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering

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