Scheduling Real-Time Parallel Applications in Cloud to Minimize Energy Consumption

Biao Hu, Zhengcai Cao, Meng Chu Zhou

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Cloud computing has become an important paradigm in which scalable resources can be provided to users to remotely process their applications. In a cloud computing platform, energy consumption accounts for a significant cost portion. This work thus aims to present an energy-efficient scheduling algorithm for processing a user application with a real-time requirement. This problem is formulated as a non-linear mixed integer programming problem. We start with providing an optimal closed-form solution to its relaxation problem that aims to minimize the energy consumption without considering real-time requirements. To meet real-time requirements, we propose how to adjust task placement and resource allocation by making a good tradeoff between energy consumption and task execution time. Lastly, we propose to adjust the start time of task execution such that the application's completion time can be further shortened. Experimental results on two real-case benchmarks and extensive synthetic applications demonstrate that our proposed method finds a schedule that generally has 30% and 20% less energy consumption than E-HEFT and genetic algorithm, respectively. Besides, the proposed method has a higher rate to successfully find a feasible schedule than them, and its computation time is close to E-HEFT's, but far less than the genetic algorithm.

Original languageEnglish (US)
JournalIEEE Transactions on Cloud Computing
DOIs
StateAccepted/In press - Jan 1 2019

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications

Keywords

  • Energy consumption minimization
  • cloud computing
  • optimization methods
  • parallel application
  • real-time scheduling

Fingerprint Dive into the research topics of 'Scheduling Real-Time Parallel Applications in Cloud to Minimize Energy Consumption'. Together they form a unique fingerprint.

Cite this