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ACM Meas. Anal. Comput. Syst."],"published-print":{"date-parts":[[2017,6,13]]},"abstract":"<jats:p>Modeling the energy consumption of applications on mobile devices is an important topic that has received much attention in recent years. However, there has been very little research on modeling the energy consumption of the mobile Web. This is primarily due to the short-lived yet complex page load process that makes it infeasible to rely on coarse-grained resource monitoring for accurate power estimation.<\/jats:p>\n          <jats:p>We present RECON, a modeling approach that accurately estimates the energy consumption of any Web page load and deconstructs it into the energy contributions of individual page load activities. Our key intuition is to leverage low-level application semantics in addition to coarse-grained resource utilizations for modeling the page load energy consumption. By exploiting fine-grained information about the individual activities that make up the page load, RECON enables fast and accurate energy estimations without requiring complex models. Experiments across 80 Web pages and under four different optimizations show that RECON can estimate the energy consumption for a Web page load with an average error of less than 7%. Importantly, RECON helps to analyze and explain the energy effects of an optimization on the individual components of Web page loads.<\/jats:p>","DOI":"10.1145\/3084443","type":"journal-article","created":{"date-parts":[[2018,3,23]],"date-time":"2018-03-23T18:28:08Z","timestamp":1521829688000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":16,"title":["Deconstructing the Energy Consumption of the Mobile Page Load"],"prefix":"10.1145","volume":"1","author":[{"given":"Yi","family":"Cao","sequence":"first","affiliation":[{"name":"Stony Brook University, Stony Brook, NY, USA"}]},{"given":"Javad","family":"Nejati","sequence":"additional","affiliation":[{"name":"Stony Brook University, Stony Brook, NY, USA"}]},{"given":"Muhammad","family":"Wajahat","sequence":"additional","affiliation":[{"name":"Stony Brook University, Stony Brook, NY, USA"}]},{"given":"Aruna","family":"Balasubramanian","sequence":"additional","affiliation":[{"name":"Stony Brook University, Stony Brook, NY, USA"}]},{"given":"Anshul","family":"Gandhi","sequence":"additional","affiliation":[{"name":"Stony Brook University, Stony Brook, NY, USA"}]}],"member":"320","published-online":{"date-parts":[[2017,6,13]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"2011. 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Calabash. http:\/\/calaba.sh. (2017).  2017. Calabash. http:\/\/calaba.sh. (2017)."},{"key":"e_1_2_1_11_1","unstructured":"2017. Chrome Developer Tools. https:\/\/developers.google.com\/web\/tools\/chrome-devtools\/?hl=en. (2017).  2017. Chrome Developer Tools. https:\/\/developers.google.com\/web\/tools\/chrome-devtools\/?hl=en. (2017)."},{"key":"e_1_2_1_12_1","unstructured":"2017. Code and relevant scripts for RECON. https:\/\/github.com\/davycao\/Deconstructing-Mobipower. (2017).  2017. Code and relevant scripts for RECON. https:\/\/github.com\/davycao\/Deconstructing-Mobipower. (2017)."},{"key":"e_1_2_1_13_1","unstructured":"2017. Google Pagespeed Insights. https:\/\/developers.google.com\/speed\/pagespeed\/insights. (2017).  2017. Google Pagespeed Insights. https:\/\/developers.google.com\/speed\/pagespeed\/insights. (2017)."},{"key":"e_1_2_1_14_1","unstructured":"2017. mod_pagespeed. http:\/\/www.modpagespeed.com\/. (2017).  2017. mod_pagespeed. http:\/\/www.modpagespeed.com\/. 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