Revenue-sensitive scheduling of multi-application tasks in software-defined cloud

Haitao Yuan, Jing Bi, Mengchu Zhou

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

1 Scopus citations

Abstract

The development of cloud computing attracts a growing number of corporations to implement their applications in data centers. The increase in variety and amount of applications in data centers that support software-defined networking (SDN) protocols makes it a big challenge to maximize revenue for data center providers. However, current SDN controllers just consider latency optimization in network and do not consider latency in virtual machines (VMs), and therefore revenue loss may occur. Different from current studies, this work aims to maximize revenue of a software-defined cloud provider. A Revenue-sensitive Scheduling of Multi-application Tasks (RSMT) method is then proposed to increase the revenue of a cloud provider. It is realized by jointly determining optimal routing paths and VMs for multi-application tasks. Simulation based on real-life task data demonstrates that compared with several current algorithms, RSMT can produce the efficient schedules that increase the cloud provider's revenue and decrease round trip time of multi-application tasks.

Original languageEnglish (US)
Title of host publication2017 13th IEEE Conference on Automation Science and Engineering, CASE 2017
PublisherIEEE Computer Society
Pages1566-1571
Number of pages6
ISBN (Electronic)9781509067800
DOIs
StatePublished - Jul 1 2017
Event13th IEEE Conference on Automation Science and Engineering, CASE 2017 - Xi'an, China
Duration: Aug 20 2017Aug 23 2017

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2017-August
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Other

Other13th IEEE Conference on Automation Science and Engineering, CASE 2017
Country/TerritoryChina
CityXi'an
Period8/20/178/23/17

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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