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Adaptare: Supporting automatic and dependable adaptation in dynamic environments

Published:30 July 2012Publication History
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Abstract

Distributed protocols executing in uncertain environments, like the Internet or ambient computing systems, should dynamically adapt to environment changes in order to preserve Quality of Service (QoS). In earlier work, it was shown that QoS adaptation should be dependable, if correctness of protocol properties is to be maintained. More recently, some ideas concerning specific strategies and methodologies for improving QoS adaptation have been proposed. In this article we describe Adaptare, a complete framework for dependable QoS adaptation. We assume that during its lifetime, a system alternates periods where its temporal behavior is well characterized, with transition periods during which a variation of the environment conditions occurs. Our method is based on the following: if the environment is generically characterized in analytical terms, and we can detect the alternation of these stable and transient phases, we can improve the effectiveness and dependability of QoS adaptation. To prove our point we provide detailed evaluation results of the proposed solutions. Our evaluation is based on synthetic data flows generated from probabilistic distributions, as well as on real data traces collected in various Internet-based environments. We compare our solution with other approaches and we show that Adaptare, albeit more complex, is very effective, allowing protocols to adapt to the available resources in a dependable way.

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            • Published in

              cover image ACM Transactions on Autonomous and Adaptive Systems
              ACM Transactions on Autonomous and Adaptive Systems  Volume 7, Issue 2
              July 2012
              275 pages
              ISSN:1556-4665
              EISSN:1556-4703
              DOI:10.1145/2240166
              Issue’s Table of Contents

              Copyright © 2012 ACM

              Publisher

              Association for Computing Machinery

              New York, NY, United States

              Publication History

              • Published: 30 July 2012
              • Accepted: 1 March 2011
              • Revised: 1 November 2010
              • Received: 1 March 2010
              Published in taas Volume 7, Issue 2

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