Paper Info
Title
A Heuristic Task Scheduling Algorithm for Heterogeneous Virtual Clusters.
Abstract
Cloud computing provides on-demand computing and storage services with high performance and high scalability. However, the rising energy consumption of cloud data centers has become a prominent problem. In this paper, we first introduce an energy-aware framework for task scheduling in virtual clusters. The framework consists of a task resource requirements prediction module, an energy estimate module, and a scheduler with a task buffer. Secondly, based on this framework, we propose a virtual machine power efficiency-aware greedy scheduling algorithm (VPEGS). As a heuristic algorithm, VPEGS estimates task energy by considering factors including task resource demands, VM power efficiency, and server workload before scheduling tasks in a greedy manner. We simulated a heterogeneous VM cluster and conducted experiment to evaluate the effectiveness of VPEGS. Simulation results show that VPEGS effectively reduced total energy consumption by more than 20% without producing large scheduling overheads. With the similar heuristic ideology, it outperformed Min-Min and RASA with respect to energy saving by about 29% and 28%, respectively.
Year
DOI
Venue
2016
10.1155/2016/7040276
SCIENTIFIC PROGRAMMING
Field
DocType
Volume
Fixed-priority pre-emptive scheduling,Heuristic,Virtual machine,Fair-share scheduling,Scheduling (computing),Computer science,Heuristic (computer science),Parallel computing,Real-time computing,Energy consumption,Distributed computing,Cloud computing
Journal
2016
ISSN
Citations 
PageRank 
1058-9244
5
0.41
References 
Authors
15
3
Name
Order
Citations
PageRank
Weiwei Lin114312.22
Wentai Wu2343.77
James Z. Wang37526403.00