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SPACE4CLOUD: a tool for system performance and costevaluation of cloud systems

Published: 22 April 2013 Publication History

Abstract

Cloud Computing is assuming a relevant role in the world of web applications and web services. Cloud technologies allow to build dynamic systems which are able to adapt their performance to workload fluctuations delegating to the Cloud Provider the intensive tasks of management and maintenance of the cloud infrastructure. Which is the best provider for our application? The application will guarantee the required service level objectives (SLOs)? Those are relevant issues that call for a tool able to carry on cost and performance analysis of the system before its actual development. In designing a software application to be executed in a cloud environment, the most relevant issues to be addressed are determining which cloud provider to use and verifying if the target system will present the required performance levels. The goal of this work is to provide a model-driven approach to performance and cost estimation of cloud and multi-cloud systems. We considered the IaaS (Infrastructure-as-a_Service) and PaaS (Platform-as-a-Service) levels.
The modelling of such systems has involved different abstraction levels, starting from the representation of cloud applications and ending with the modelling of the underlying insfrastructure/platform belonging to specific Cloud Providers. An initial prototype supporting our approach is also presented.

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cover image ACM Conferences
MultiCloud '13: Proceedings of the 2013 international workshop on Multi-cloud applications and federated clouds
April 2013
76 pages
ISBN:9781450320504
DOI:10.1145/2462326
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 22 April 2013

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Author Tags

  1. cloud computing
  2. model-driven software development
  3. performance prediction

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MultiCloud '13 Paper Acceptance Rate 9 of 18 submissions, 50%;
Overall Acceptance Rate 9 of 18 submissions, 50%

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