Authors:
Adam Barker
1
and
Rajkumar Buyya
2
Affiliations:
1
University of St Andrews, United Kingdom
;
2
University of Melbourne, Australia
Keyword(s):
Service-oriented architectures, Optimisation, Scientific workflows, Data deluge.
Related
Ontology
Subjects/Areas/Topics:
Cloud Computing
;
Collaboration and e-Services
;
Communication and Software Technologies and Architectures
;
Data Engineering
;
e-Business
;
Enterprise Information Systems
;
Languages, Tools and Architectures
;
Mobile Software and Services
;
Model-Driven Software Development
;
Ontologies and the Semantic Web
;
Service Composition and Mashups
;
Service-Oriented Architectures
;
Services Science
;
Software Agents and Internet Computing
;
Software Engineering
;
Software Engineering Methods and Techniques
;
Technology Platforms
;
Telecommunications
;
Web Services
;
Wireless Information Networks and Systems
Abstract:
Service-oriented workflows in the scientific domain are commonly composed as Directed Acyclic Graphs (DAGs), formed from a collection of vertices and directed edges. When orchestrating service-oriented DAGs, intermediate data are typically routed through a single centralised engine, which results in unnecessary data transfer, increasing the execution time of a workflow and causing the engine to become a performance bottleneck. This paper introduces an architecture for deploying and executing a service-oriented DAG-based workflows across a peer-to-peer proxy network. A workflow is divided into a set of vertices, disseminated to a group of proxies and executed without centralised control over a peer-to-peer proxy network. Through a Web services implementation, we demonstrate across PlanetLab that by reducing intermediate data transfer and by sharing the workload between distributed proxies, end-to-end workflows are sped up. Furthermore, our architecture is non-intrusive: Web services o
wned and maintained by different institutions do not have to be altered prior to execution.
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