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Book Sections Year : 2012

Self-management of applications and systems to optimize energy in data centers

Abstract

As a direct consequence of the increasing popularity of cloud computing solutions, data centers are amazingly growing and hence have to urgently face with the energy consumption issue. Available solutions are focused basically on the system layer, by leveraging virtualization technologies to improve energy efficiency. Another body of works relies on cloud computing models and virtualization techniques to scale up/down application based on their performance metrics. Although those proposals can reduce the energy footprint of applications and by transitivity of cloud infrastructures, they do not consider the internal characteristics of applications to finely define a trade-­‐off between applications Quality of Service and energy footprint. In this paper, we propose a self-­‐adaptation approach that considers both application internals and system to reduce the energy footprint in cloud infrastructure. Each application and the infrastructure are equipped with control loops, which allows them to autonomously optimize their executions. We implemented the control loops and simulated them in order to show their feasibility. In addition, we show how our solution fits in federated clouds through a motivating scenario. Finally, we provide some discussion about open issues on models and implementation of our proposal.
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Dates and versions

hal-00670033 , version 1 (14-02-2012)

Identifiers

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Frederico Alvares de Oliveira Jr., Adrien Lebre, Thomas Ledoux, Jean-Marc Menaud. Self-management of applications and systems to optimize energy in data centers. Ivona Brandic and Massimo Villari and Francesco Tusa. Achieving Federated and Self-Manageable Cloud Infrastructures: Theory and Practice, IGI Global, 2012, ⟨10.4018/978-1-4666-1631-8.ch019⟩. ⟨hal-00670033⟩
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