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Caching to Reduce Mobile App Energy Consumption

Published:09 September 2017Publication History
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Abstract

Mobile applications consume device energy for their operations, and the fast rate of battery depletion on mobile devices poses a major usability hurdle. After the display, data communication is the second-biggest consumer of mobile device energy. At the same time, software applications that run on mobile devices represent a fast-growing product segment. Typically, these applications serve as front-end display mechanisms, which fetch data from remote servers and display the information to the user in an appropriate format—incurring significant data communication overheads in the process. In this work, we propose methods to reduce energy overheads in mobile devices due to data communication by leveraging data caching technology. A review of existing caching mechanisms revealed that they are primarily designed for optimizing response time performance and cannot be easily ported to mobile devices for energy savings. Further, architectural differences between traditional client-server and mobile communications infrastructures make the use of existing caching technologies unsuitable in mobile devices. In this article, we propose a set of two new caching approaches specifically designed with the constraints of mobile devices in mind: (a) a response caching approach and (b) an object caching approach. Our experiments show that, even for a small cache size of 250MB, object caching can reduce energy consumption on average by 45% compared to the no-cache case, and response caching can reduce energy consumption by 20% compared to the no-cache case. The benefits increase with larger cache sizes. These results demonstrate the efficacy of our proposed method and raise the possibility of significantly extending mobile device battery life.

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        • Published in

          cover image ACM Transactions on the Web
          ACM Transactions on the Web  Volume 12, Issue 1
          February 2018
          169 pages
          ISSN:1559-1131
          EISSN:1559-114X
          DOI:10.1145/3133955
          Issue’s Table of Contents

          Copyright © 2017 ACM

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 9 September 2017
          • Revised: 1 July 2017
          • Accepted: 1 July 2017
          • Received: 1 March 2016
          Published in tweb Volume 12, Issue 1

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