Authors:
Moreno Marzolla
1
and
Raffaela Mirandola
2
Affiliations:
1
Università di Bologna, Italy
;
2
Politecnico di Milano, Italy
Keyword(s):
Cloud Computing, Workflow Engine, Self-management, SLA Management.
Related
Ontology
Subjects/Areas/Topics:
Cloud Application Scalability and Availability
;
Cloud Applications Performance and Monitoring
;
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
;
Platforms and Applications
;
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:
The Cloud Computing paradigm is providing system architects with a new powerful tool for building scalable
applications. Clouds allow allocation of resources on a ”pay-as-you-go” model, so that additional resources
can be requested during peak loads and released after that. In this paper we describe SAVER (qoS-Aware
workflows oVER the Cloud), a QoS-aware algorithm for executing workflows involving Web Services hosted
in a Cloud environment. SAVER allows execution of arbitrary workflows subject to response time constraints.
SAVER uses a simple Queueing Network (QN) model to identify the optimal resource allocation; specifically,
the QN model is used to identify bottlenecks, and predict the system performance as Cloud resources are
allocated or released. Our approach has been validated through numerical simulations, whose results are
reported in this paper.