Workflow as a Service in the Cloud: Architecture and Scheduling Algorithms

Thumbnail Image

Files

1-s2.0-S1877050914002269-main.pdf (888.81 KB)

Links to Files

https://www.sciencedirect.com/science/article/pii/S1877050914002269

Permanent Link

https://doi.org/10.1016/j.procs.2014.05.049
 http://hdl.handle.net/11603/31605

Collections

UMBC Information Systems Department
UMBC Center for Accelerated Real Time Analysis
UMBC Center for Real-time Distributed Sensing and Autonomy
UMBC Computer Science and Electrical Engineering Department
UMBC Data Science
UMBC Joint Center for Earth Systems Technology (JCET)

Author/Creator

Author/Creator ORCID

https://orcid.org/0000-0002-9933-1170

Date

2014-06-06

Type of Work

journal articles
Text

Department

Program

Citation of Original Publication

Wang, Jianwu, Prakashan Korambath, Ilkay Altintas, Jim Davis, and Daniel Crawl. “Workflow as a Service in the Cloud: Architecture and Scheduling Algorithms.” Procedia Computer Science, 2014 International Conference on Computational Science, 29 (January 1, 2014): 546–56. https://doi.org/10.1016/j.procs.2014.05.049.

Rights

This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
Attribution-NonCommercial-NoDerivs 3.0 Unported

Subjects

UMBC Big Data Analytics Lab

Abstract

With more and more workflow systems adopting cloud as their e xecution environment, it becomes increasingly challenging on how to effic iently manage various workflows, v irtual machines (VMs) and workflow e xecution on VM instances. To make the system scalable and easy-to-extend, we design a Workflow as a Service (WFaaS) a rchitecture with independent services. A core part of the architecture is how to efficiently respond continuous workflo w requests from users and schedule their e xecutions in the c loud. Based on diffe rent targets, we p ropose four heuristic workflo w scheduling a lgorith ms for the WFaaS architecture, and analy ze the differences and best usages of the algorith ms in terms of performance, cost and the price/performance ratio via experimental studies.