Autonomic Management using Self-Stabilization for Hierarchical and Distributed Middleware
Abstract
Dynamic nature of distributed architecture is a major challenge to avail the benefits of distributed computing. An effective solution to deal with this dynamic nature is to implement a self-adaptive mechanism to sustain the distributed architecture. Self-adaptive systems can autonomously modify their behavior at run-time in response to changes in their environment. This capability may be included in the software systems at design time or later by external mechanisms. Our paper describes the self- adaptive algorithm that we developed for an existing middleware. Once the middleware is deployed, it can detect a set of events which indicate an unstable deployment state. When an event is detected, some instructions are executed to handle the event. We have designed a simulator to have a deeper insights of our proposed self-adaptive algorithm. Results of our simulated experiments validate the safe convergence of the algorithm.
Origin : Files produced by the author(s)
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