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EnergyBox: Disclosing the wireless transmission energy cost for mobile devices
Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, The Institute of Technology. (Real-Time Systems Laboratory)
Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, The Institute of Technology. (Real-Time Systems Laboratory)
Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, The Institute of Technology. (Real-Time Systems Laboratory)
2014 (English)In: Sustainable Computing: Informatics and Systems, ISSN 2210-5379, Vol. 4, no 2, 118-135 p.Article in journal (Refereed) Published
Abstract [en]

While evolving mobile technologies bring millions of users closer to the vision of information anywhere-anytime, device battery depletions still hamper the quality of experience to a great extent. The energy consumption of data transmission is highly dependent on the traffic pattern, and we argue that designing energy efficient data transmissions starts by energy awareness. Our work proposes EnergyBox, a parametrised tool that facilitates accurate and repeatable energy consumption studies for 3G and WiFi transmissions at the user end using real traffic data.

The tool takes as input the parameters of a network operator and the power draw for a given mobile device in the 3G and WiFi transmission states. It outputs an estimate of the consumed energy for a given packet trace, either synthetic or captured in a device using real applications. Using nine different applications with different data patterns the versatility and accuracy of the tool was evaluated. The evaluation was carried out for a modern and popular smartphone in the WiFi setting, a specific mobile broadband module for the 3G setting, and within the operating environment of a major mobile operator in Sweden. A comparison with real power traces indicates that EnergyBox is a valuable tool for repeatable and convenient studies. It exhibits an accuracy of 94–99% for 3G, and 95–99% for WiFi given the studied applications’ traces.

Next the tool was deployed in a use case where a location sharing application was ran on top of two alternative application layer protocols (HTTP and MQTT) and with two different data exchange formats (JSON and Base64). The illustrative use case helped to identify the appropriateness of the pull and push strategies in sharing location data, and the benefit of EnergyBox in characterising where the breaking point lies for preferring one or the other protocol, under which network load, or exchange data format.

Place, publisher, year, edition, pages
Elsevier, 2014. Vol. 4, no 2, 118-135 p.
Keyword [en]
Wireless transmission energy; Energy consumption; Trace-based simulation; 3G; 802.11; Location sharing
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:liu:diva-108229DOI: 10.1016/j.suscom.2014.03.008Scopus ID: 2-s2.0-84902535473OAI: oai:DiVA.org:liu-108229DiVA: diva2:729624
Available from: 2014-06-26 Created: 2014-06-26 Last updated: 2015-04-07Bibliographically approved

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Vergara Alonso, Ekhiotz JonNadjm-Tehrani, Simin

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