Reference : Profiling Performance of Application Partitioning for Wearable Devices in Mobile Clou...

	Document type :	Scientific journals : Article
	Discipline(s) :	Engineering, computing & technology : Computer science
	Focus Areas :	Security, Reliability and Trust
	To cite this reference:	http://hdl.handle.net/10993/42077

Title :	Profiling Performance of Application Partitioning for Wearable Devices in Mobile Cloud and Fog Computing
Language :	English
Author, co-author :	Fiandrino, Claudio [> IMDEA]
	Allio, Nicholas [Politechnico of Torino]
	Kliazovich, Dzmitry [Oply]
	Giaccone, Paolo [Politechgnico of Torino]
	Bouvry, Pascal [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Publication date :	2019
Journal title :	IEEE Access
Publisher :	Institute of Electrical and Electronics Engineers
Volume :	7
Pages :	12156-12166
Peer reviewed :	Yes
Audience :	International
ISSN :	2169-3536
City :	Piscataway
Country :	NJ
Keywords :	[en] Mobile cloud computing ; IoT ; wearable devices ; FoG computing
Abstract :	[en] Wearable devices have become essential in our daily activities. Due to battery constrains the use of computing, communication, and storage resources is limited. Mobile Cloud Computing (MCC) and the recently emerged Fog Computing (FC) paradigms unleash unprecedented opportunities to augment capabilities of wearables devices. Partitioning mobile applications and offloading computationally heavy tasks for execution to the cloud or edge of the network is the key. Offloading prolongs lifetime of the batteries and allows wearable devices to gain access to the rich and powerful set of computing and storage resources of the cloud/edge. In this paper, we experimentally evaluate and discuss rationale of application partitioning for MCC and FC. To experiment, we develop an Android-based application and benchmark energy and execution time performance of multiple partitioning scenarios. The results unveil architectural trade-offs that exist between the paradigms and devise guidelines for proper power management of service-centric Internet of Things (IoT) applications.
Permalink :	http://hdl.handle.net/10993/42077
DOI :	10.1109/ACCESS.2019.2892508

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