DocumentCode :
3397602
Title :
Reducing mobile device energy consumption with computation offloading
Author :
Hao Qian ; Andresen, Daniel
Author_Institution :
Dept. of Comput. & Inf. Sci., Kansas State Univ., Manhattan, KS, USA
fYear :
2015
fDate :
1-3 June 2015
Firstpage :
1
Lastpage :
8
Abstract :
The need for increased performance of mobile device directly conflicts with the desire for longer battery life. Offloading computation to multiple devices is an effective method to reduce energy consumption and enhance performance for mobile applications. Android provides mechanisms for creating mobile applications but lacks a native scheduling system for determining where code should be executed. This paper presents Jade, a system that adds sophisticated energy-aware computation offloading capabilities to Android apps. Jade monitors device and application status and automatically decides where code should be executed. Jade dynamically adjusts offloading strategy by adapting to workload variation, communication costs, and energy status in a distributed network of Android and non-Android devices. Jade minimizes the burden on developers to build applications with computation offloading ability by providing easy-to-use Jade API. Evaluation shows that Jade can effectively reduce up to 39% of average power consumption for mobile application while improving application performance.
Keywords :
Android (operating system); application program interfaces; mobile computing; power aware computing; scheduling; Android application; Android devices; Jade API; code offloading; communication costs; distributed network; energy-aware computation offloading strategy; mobile device energy consumption reduction; native scheduling system; nonAndroid devices; power consumption; workload variation; Energy consumption; Engines; Mobile applications; Mobile handsets; Programming; Runtime; Servers; code offload; distributed computing; energy management; mobile computing; scheduling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 2015 16th IEEE/ACIS International Conference on
Conference_Location :
Takamatsu
Type :
conf
DOI :
10.1109/SNPD.2015.7176219
Filename :
7176219
Link To Document :
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