Paper Info
Title
Reliability and energy efficient workflow scheduling in cloud environment
Abstract
Cloud data centers consume huge amounts of electrical energy which results in an increased operational cost, decreased system reliability and carbon dioxide footprints. Thus, it is highly important to develop scheduling strategy to reduce energy consumption. Dynamic voltage and frequency scaling (DVFS) has been recognized as an efficient technique for reducing energy consumption. However, there is negative impact of DVFS on the reliability of system as it increases the transient faults during the application execution. Hence, it is essential to address the issue of reliability for mission critical applications. Recent studies on workflow scheduling in distributed environment have not considered reliability while minimizing the energy consumption. In this paper, we propose a new scheduling algorithm called the reliability and energy efficient workflow scheduling algorithm which jointly optimizes lifetime reliability of application and energy consumption and guarantees the user specified QoS constraint. The proposed algorithm works in four phases: priority calculation, clustering of tasks, distribution of target time and assigning the cluster to processing element with appropriate voltage/frequency levels. The simulation results obtained by using randomly generated task graphs and Gaussian Elimination task graphs shows that the proposed approach is effective in joint optimization of lifetime reliability of system and energy consumption compared to existing algorithms.
Year
DOI
Venue
2019
10.1007/s10586-019-02911-7
Cluster Computing
Keywords
DocType
Volume
Workflow scheduling, Cloud environments, Reliability, Energy consumption
Journal
22
Issue
ISSN
Citations 
4
1386-7857
4
PageRank 
References 
Authors
0.41
35
3
Name
Order
Citations
PageRank
ritu garg164.50
Mamta Mittal2419.68
Le Hoang Son386164.51