Abstract
Measuring energy consumption is an essential step in the development of policies for the management of energy in every IT system. There is a wide range of methods using both hardware and software for measuring energy consumed by the system accurately. However, most of these methods measure energy consumed by a machine or a cluster of machines. In environments such as Cloud that an application can be built from components with comparable characteristics, measuring energy consumed by a single component can be extremely beneficial. For example, if we can measure energy consumed by different HTTP servers, then we can establish which one consumes less energy performing a given task. As a result, the Cloud provider can provide incentives, so that, application developers use the HTTP server that consume less energy. Indeed, considering size of the Cloud, even a small amount of saving per Virtual Machine can add up to a substantial saving. In this paper, we propose a technique to measure energy consumed by an application via measuring energy consumed by the individual processes of the application. We shall deal with applications that run in a virtualized environment such as Cloud. We present two implementations of our idea to demonstrate the feasibility of the approach. Firstly, a method of measurement with the help of Kernel-Based Virtual Machine running on a typical laptop is presented. Secondly, in a commercial Cloud such as Elastic host, we describe a method of measuring energy consumed by processes such as HTTP servers. This will allow commercial providers to identify which product consumes less energy on their platform.
Original language | English |
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Title of host publication | Proceedings - 4th IEEE International Conference on Big Data and Cloud Computing, BDCloud 2014 with the 7th IEEE International Conference on Social Computing and Networking, SocialCom 2014 and the 4th International Conference on Sustainable Computing and Communications, SustainCom 2014 |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Pages | 654-661 |
Number of pages | 8 |
ISBN (Print) | 9781479967193 |
DOIs | |
Publication status | Published - 5 Feb 2015 |
Event | 4th IEEE International Conference on Big Data and Cloud Computing, BDCloud 2014 - Sydney, Australia Duration: 3 Dec 2014 → 5 Dec 2014 |
Conference
Conference | 4th IEEE International Conference on Big Data and Cloud Computing, BDCloud 2014 |
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Country/Territory | Australia |
City | Sydney |
Period | 3/12/14 → 5/12/14 |
Keywords
- cloud
- energy
- virtual machine
ASJC Scopus subject areas
- Software
- Computer Networks and Communications