A comparative study of DAG clustering

Hongliang Lu, Jiannong Cao, Shaohe Lv, Xiaodong Wang, Juan Liu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)

Abstract

Organizing tasks that are decomposed from workflows with directed acyclic graph (DAG) is a common practice. Assigning the tasks in DAG to physical computing nodes is a critical step for minimizing the total workflow processing time. However, scale and diversity of the DAG increase distinctly as the increment of the complexity of applications. Waiting time introduced by the dependencies between tasks affect the processing time of workflows severely. Cluster based task assignment is promising for reducing the waiting time introduced by dependencies. In which the key element is the cluster method that are taken to group the tasks. This paper comparatively studied the task assignment performance with different DAG clustering methods. The experiment results show that genetic based clustering method is better in reducing the make-span and enlarging the speedup for workflows.
Original languageEnglish
Title of host publicationInternational Conference on Information Society, i-Society 2015
PublisherIEEE
Pages84-89
Number of pages6
ISBN (Electronic)9781908320483
DOIs
Publication statusPublished - 28 Dec 2015
EventInternational Conference on Information Society, i-Society 2015 - London, United Kingdom
Duration: 9 Nov 201511 Nov 2015

Conference

ConferenceInternational Conference on Information Society, i-Society 2015
Country/TerritoryUnited Kingdom
CityLondon
Period9/11/1511/11/15

Keywords

  • cluster based task schedule
  • comaprative study
  • DAG clustering
  • task schedule

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Networks and Communications
  • Information Systems

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