Towards Energy Consumption Measurement in a Cloud Computing Wireless Testbed



The evolution of the Next Generation Networks, especially the wireless broadband access technologies such as Long Term Evolution (LTE) and Worldwide Interoperability for Microwave Access (WiMAX), have increased the number of all- IP networks across the world. The enhanced capabilities of these access networks has spearheaded the cloud computing paradigm, where the end-users aim at having the services accessible anytime and anywhere. The services availability is also related with the end-user device, where one of the major constraints is the battery lifetime. Therefore, it is necessary to assess and minimize the energy consumed by the end-user devices, given its significance for the user perceived quality of the cloud computing services. In this paper, an empirical methodology to measure network interfaces energy consumption is proposed. By employing this methodology, an experimental evaluation of energy consumption in three different cloud computing access scenarios (including WiMAX) were performed. The empirical results obtained show the impact of accurate network interface states management and application network level design in the energy consumption. Additionally, the achieved outcomes can be used in further software-based models to optimized energy consumption, and increase the Quality of Experience (QoE) perceived by the end- users.


Cloud Computing, Energy, Measurement, Testbed, Wireless, 4G networks


Energy efficiency

Related Project

WiMAX Pilot


IEEE First Symposium on Network Cloud Computing and Applications, IEEE NCCA 2011, Toulouse, France, November 2011

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Year 2013 : 1 citations

 K. Mohan Satya, Narayana Reddy , K. Sathi Reddy, "An Optimal Energy Efficient Video Distribution Over Cooperative Wireless Networks", International Journal Of Engineering And Computer Science, ISSN:2319-7242 Volume 2 Issue 8 August, 2013 Page No. 2393-2396

Year 2012 : 1 citations

 Saleh Abdallah-Saleh, Qi Wang, Christos Grecos, "Real-time video streaming in mobile cloud over heterogeneous wireless networks", Proc. SPIE 8437, Real-Time Image and Video Processing 2012, 84370S (June 1, 2012); doi:10.1117/12.924258;