Proceedings ArticleDOI
Energy consumption in mobile phones: a measurement study and implications for network applications
Niranjan Balasubramanian,Aruna Balasubramanian,Arun Venkataramani +2 more
- pp 280-293
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TLDR
TailEnder is developed, a protocol that reduces energy consumption of common mobile applications and aggressively prefetches several times more data and improves user-specified response times while consuming less energy.Abstract:Â
In this paper, we present a measurement study of the energy consumption characteristics of three widespread mobile networking technologies: 3G, GSM, and WiFi. We find that 3G and GSM incur a high tail energy overhead because of lingering in high power states after completing a transfer. Based on these measurements, we develop a model for the energy consumed by network activity for each technology.Using this model, we develop TailEnder, a protocol that reduces energy consumption of common mobile applications. For applications that can tolerate a small delay such as e-mail, TailEnder schedules transfers so as to minimize the cumulative energy consumed meeting user-specified deadlines. We show that the TailEnder scheduling algorithm is within a factor 2x of the optimal and show that any online algorithm can at best be within a factor 1.62x of the optimal. For applications like web search that can benefit from prefetching, TailEnder aggressively prefetches several times more data and improves user-specified response times while consuming less energy. We evaluate the benefits of TailEnder for three different case study applications - email, news feeds, and web search - based on real user logs and show significant reduction in energy consumption in each case. Experiments conducted on the mobile phone show that TailEnder can download 60% more news feed updates and download search results for more than 50% of web queries, compared to using the default policy.read more
Citations
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Proceedings ArticleDOI
A close examination of performance and power characteristics of 4G LTE networks
TL;DR: This paper develops the first empirically derived comprehensive power model of a commercial LTE network with less than 6% error rate and state transitions matching the specifications, and identifies that the performance bottleneck for web-based applications lies less in the network, compared to the previous study in 3G.
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Diversity in smartphone usage
Hossein Falaki,Ratul Mahajan,Srikanth Kandula,Dimitrios Lymberopoulos,Ramesh Govindan,Deborah Estrin +5 more
TL;DR: A comprehensive study of smartphone use finds that qualitative similarities exist among users that facilitate the task of learning user behavior and demonstrates the value of adapting to user behavior in the context of a mechanism to predict future energy drain.
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Where is the energy spent inside my app?: fine grained energy accounting on smartphones with Eprof
TL;DR: Bundles are proposed, a new accounting presentation of app I/O energy, which helps the developer to quickly understand and optimize the energy drain of her app.
Journal ArticleDOI
Mobile data offloading: how much can WiFi deliver?
TL;DR: A trace-driven simulation using the acquired whole-day traces indicates that WiFi already offloads about 65% of the total mobile data traffic and saves 55% of battery power without using any delayed transmission.
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Mobile Data Offloading through Opportunistic Communications and Social Participation
TL;DR: This work proposes to exploit opportunistic communications to facilitate information dissemination in the emerging Mobile Social Networks (MoSoNets) and thus reduce the amount of mobile data traffic.
References
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Proceedings ArticleDOI
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Ahmad Rahmati,Lin Zhong +1 more
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Proceedings ArticleDOI
Wireless wakeups revisited: energy management for voip over wi-fi smartphones
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