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Platform Support for Mobile Edge Computing

Authors: Jaehun Lee; Hochul Lee; Young Choon Lee; Hyuck Han; Sooyong Kang;

Platform Support for Mobile Edge Computing

Abstract

Computing resources including mobile devices at the edge of a network are increasingly connected and capable of collaboratively processing what's believed to be too complex to them. Collaboration possibilities with today's feature-rich mobile devices go far beyond simple media content sharing, traditional video conferencing and cloud-based software as a services. The realization of these possibilities for mobile edge computing (MEC) requires non-trivial amounts of efforts in enabling multi-device resource sharing. The current practice of mobile collaborative application development remains largely at the application level. In this paper, we present CollaboRoid, a platform-level solution that provides a set of system services for mobile collaboration. CollaboRoid's platform-level design significantly eases the development of mobile collaborative applications promoting MEC. In particular, it abstracts the sharing of not only hardware resources, but also software resources and multimedia contents between multiple heterogeneous mobile devices. We implement CollaboRoid in the application framework layer of the Android stack and evaluate it with several collaboration scenarios on Nexus 5 and 7 devices. Our experimental results show the feasibility of the platform-level collaboration using CollaboRoid in terms of the latency and energy consumption.

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    influence
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Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Average
Top 10%
Top 10%
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