Earticle

초록

영어

As more and more non-trivial applications have been deployed in cloud-based systems, the energy consumption of running these applications grow rapidly. Existing studies mainly focus on reducing the CPU-related energy consumption, while ignoring the data-accessing related energy costs. In the paper, we present a novel energy-efficient policy, which is aiming at reducing the data-accessing energy consumption of workflow applications that executed on cloud environments. The proposed policy uses a general energy model to describe the energy consumption of any given workflow. By this application-oriented energy model, a two-phase resource deploying algorithm is implemented, which is capable of generating task scheduling schemes with minimal data-accessing energy consumption. Massive experiments are conducted on a real-world cloud platform, and the results show that the proposed policy outperforms existing approaches in terms of energy efficiency and execution performance.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Problem Description and Formulation
 4. Scheduling Policy Implementation and Analysis
  4.1. Scheduling Model
  4.2. Implementation of Scheduling Algorithm
 5. Experiments and Performance Comparison
  5.1. Experimental Settings
  5.2. Comparison of Performance
 6. Conclusion
 References

키워드

저자

• Hong He [ Department of Computer and Communication, Hunan Institute of Engineering ]
• Dongbo Liu [ Department of Computer and Communication, Hunan Institute of Engineering ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Future Generation Communication and Networking

• 간기

  격월간

• pISSN

  2233-7857

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605