A Model to Guide Dynamic Adaptation Planning in Self-Adaptive Systems

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Abstract

Self-adaptive enterprise applications have the ability to continuously reconfigure themselves according to changes in their execution contexts or user requirements. The infrastructure managing such systems is based on IBM's MAPE-K reference model: a Monitor and an Analyzer to sense and interpret context data, a Planner and an Executor to create and apply structural adaptation plans, and a Knowledge manager to share relevant information. In this paper we present a formal model, built on the principles of constraint satisfaction, to address dynamic adaptation planning for self-adaptive enterprise applications. We formalize, modify and extend the approach presented in [H. Arboleda, J. F. Díaz, V. Vargas, and J.-C. Royer, "Automated reasoning for derivation of modeldriven spls," in SPLC'10 MAPLE'10, 2010, pp. 181-188] for working with self-adaptation infrastructures in order to provide automated reasoning on the dynamic creation of structural adaptation plans. We use a running example to demonstrate the applicability of such model, even in situations where complex interactions arise between context elements and the target self-adaptive enterprise application.

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APA

Paz, A., & Arboleda, H. (2016). A Model to Guide Dynamic Adaptation Planning in Self-Adaptive Systems. In Electronic Notes in Theoretical Computer Science (Vol. 321, pp. 67–88). Elsevier B.V. https://doi.org/10.1016/j.entcs.2016.02.005

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