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Conference Papers Year : 2018

A Self-adaptive Agent-based System for Cloud Platforms

Abstract

Cloud computing is a model for enabling on-demand network access to a shared pool of computing resources, that can be dynamically allocated and released with minimal effort. However, this task can be complex in highly dynamic environments with various resources to allocate for an increasing number of different users requirements. In this work, we propose a Cloud architecture based on a multi-agent system exhibiting a self-adaptive behavior to address the dynamic resource allocation. This self-adaptive system follows a MAPE-K approach to reason and act, according to QoS, Cloud service information, and propagated run-time information, to detect QoS degradation and make better resource allocation decisions. We validate our proposed Cloud architecture by simulation. Results show that it can properly allocate resources to reduce energy consumption, while satisfying the users demanded QoS.
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Dates and versions

hal-02437205 , version 1 (13-01-2020)

Identifiers

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Merzoug Soltane, Yudith Cardinale, Rafael Angarita, Philippe Roose, Philippe Rosse, et al.. A Self-adaptive Agent-based System for Cloud Platforms. International Conference on Pattern Analysis and Intelligent Systems (PAIS), Oct 2018, Tebessa, Algeria. pp.1-8, ⟨10.1109/PAIS.2018.8598507⟩. ⟨hal-02437205⟩
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