Workflow as a Service in the Cloud: Architecture and Scheduling Algorithms
dc.contributor.author | Wang, Jianwu | |
dc.contributor.author | Korambath, Prakashan | |
dc.contributor.author | Altintas, Ilkay | |
dc.contributor.author | Davis, Jim | |
dc.contributor.author | Crawl, Daniel | |
dc.date.accessioned | 2024-02-12T21:40:30Z | |
dc.date.available | 2024-02-12T21:40:30Z | |
dc.date.issued | 2014-06-06 | |
dc.description.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. | |
dc.description.sponsorship | This work is supported by DOE grant DE-EE0005763 : “Industrial Scale Demonstration of Smart Manufacturing Achieving Transformational Energy Productivity Gains”, NSF grant DBI-1062565: Workflow as a Service in the Cloud J.Wang, P. Korambath, I. Altintas, J. Davis and D. Crawl “bioKepler: A Comprehensive Bioinformatics Scientific Workflow Module for Distributed Analysis of Large-Scale Biological Data”, and NSF grant 1331615: “WIFIRE: A Scalable Data-Driven Monitoring, Dynamic Prediction and Resilience Cyberinfrastructure for Wildfires ”. | |
dc.description.uri | https://www.sciencedirect.com/science/article/pii/S1877050914002269 | |
dc.format.extent | 11 pages | |
dc.genre | journal articles | |
dc.identifier.citation | 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. | |
dc.identifier.uri | https://doi.org/10.1016/j.procs.2014.05.049 | |
dc.identifier.uri | http://hdl.handle.net/11603/31605 | |
dc.language.iso | en_US | |
dc.publisher | Elsevier | |
dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
dc.relation.ispartof | UMBC Information Systems Department Collection | |
dc.relation.ispartof | UMBC Center for Accelerated Real Time Analysis | |
dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department | |
dc.relation.ispartof | UMBC Data Science | |
dc.relation.ispartof | UMBC Joint Center for Earth Systems Technology (JCET) | |
dc.relation.ispartof | UMBC Center for Real-time Distributed Sensing and Autonomy | |
dc.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. | |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Unported | en |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/ | |
dc.subject | UMBC Big Data Analytics Lab | |
dc.title | Workflow as a Service in the Cloud: Architecture and Scheduling Algorithms | |
dc.type | Text | |
dcterms.creator | https://orcid.org/0000-0002-9933-1170 |