NDLI: User mobility-aware decision making for mobile computation offloading

Content Provider	IEEE Xplore Digital Library
Author	Kilho Lee Insik Shin
Copyright Year	2013
Description	Author affiliation: Dept. of Comput. Sci., KAIST, Daejeon, South Korea (Kilho Lee; Insik Shin)
Abstract	The last decade has seen a rapid growth in the use of mobile devices all over the world. With an increasing use of mobile devices, mobile applications are getting more diverse and complex, demanding more computational resources. However, mobile devices are typically resource-limited (i.e., a slower-speed CPU, a smaller memory) due to a variety of reasons. Mobile users will be capable of running applications with heavy computation if they can offload some of their computations to other places, such as desktop or server machines. However, mobile users are typically subject to dynamically changing network environments, particularly, due to user mobility. This makes it hard to make good offloading decisions in mobile environments. In general, user's mobility can provide some hints for upcoming changes to network environments. Motivated by this, we propose a mobility model of each individual user taking advantage of the regularity of his/her mobility pattern, and develop an offloading decision making technique based on the mobility model. We evaluate our technique through trace-based simulation with real log data traces from 14 Android users. Our evaluation result shows that the proposed technique can help mobile devices to boost its performance in terms of response time and energy consumption, when users are highly mobile.
Starting Page	116
Ending Page	119
File Size	504194
Page Count	4
File Format	PDF
ISBN	9781479907984
DOI	10.1109/CPSNA.2013.6614257
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-08-19
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	IEEE 802.11 Standards Computational modeling Decision making Mobile communication Mobile handsets Time factors Engines
Content Type	Text
Resource Type	Article

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