Paper Info
Title
ACS: an effective admission control scheme with deadlock resolutions for workflow scheduling in clouds.
Abstract
The Cloud with its abundant on-demand processor, storage, and bandwidth capacities and the elastic billing models has been emerging as a promising platform to scientific workflow computations. However, in reality, due to ineffective use of or practical constraints on the provisioned resources, the best-effort model to allocate as many as possible resources from Clouds is not always cost effective or feasible for cloud users to compute their workflow applications. To address this problem, in this paper, we study the effective use of a virtual cluster with a shared finite storage system to improve the performance of the workflow scheduling. Since the concurrent executions of multiple concurrent instances of the workflow are subject to the storage capacity constraints, deadlock resolution is our major concern in the performance optimization. To this end, we propose an effective admission control scheme (ACS) that integrates a set of deadlock resolution algorithms to admit workflow instances to the system based on the available storage capacities. With ACS, we can reduce the competitiveness on the finite storage and minimize the adverse impact of deadlock as well. We show the benefits of ACS via intensive simulation studies on the performance changes of a set of selected benchmark workflows. Our results demonstrate that the proposed ACS is a cost-effective way to fully utilize the provisioned storage resources for workflow scheduling in cloud virtual clusters.
Year
DOI
Venue
2015
10.1007/s00607-014-0409-6
Computing
Keywords
DocType
Volume
Workflow scheduling, Storage resource constraint, Deadlock resolution, Admission control, 68M20
Journal
97
Issue
ISSN
Citations 
4
1436-5057
2
PageRank 
References 
Authors
0.39
26
3
Name
Order
Citations
PageRank
Yang Wang1839.61
Menglan Hu211114.96
Kenneth B. Kent345854.42