characterizing energy per job in cloud applications

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ID: 130939
2016
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Abstract
Energy efficiency is a major research focus in sustainable development and is becoming even more critical in information technology (IT) with the introduction of new technologies, such as cloud computing and big data, that attract more business users and generate more data to be processed. While many proposals have been presented to optimize power consumption at a system level, the increasing heterogeneity of current workloads requires a finer analysis in the application level to enable adaptive behaviors and in order to reduce the global energy usage. In this work, we focus on batch applications running on virtual machines in the context of data centers. We analyze the application characteristics, model their energy consumption and quantify the energy per job. The analysis focuses on evaluating the efficiency of applications in terms of performance and energy consumed per job, in particular when shared resources are used and the hosts on which the virtual machines are running are heterogeneous in terms of energy profiles, with the aim of identifying the best combinations in the use of resources.
Reference Key
ho2016electronicscharacterizing Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Thi Thao Nguyen Ho;Marco Gribaudo;Barbara Pernici
Journal biology bulletin of the academy of sciences of the ussr
Year 2016
DOI
10.3390/electronics5040090
URL
http://www.mdpi.com/2079-9292/5/4/90
Keywords
energy efficiency cloud computing

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