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Profiling Performance of Application Partitioning for Wearable Devices in Mobile Cloud and Fog Computing

Fiandrino, Claudio and Allio, Nicholas and Kliazovich, Dzmitry and Giaccone, Paolo and Bouvry, Pascal (2019) Profiling Performance of Application Partitioning for Wearable Devices in Mobile Cloud and Fog Computing. [Journal Articles]

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Abstract

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.

Item Type: Journal Articles
Uncontrolled Keywords: Mobile cloud computing, fog computing, energy efficiency, IoT, wearable devices.
Subjects: UNSPECIFIED
Divisions: UNSPECIFIED
Depositing User: Claudio Fiandrino
Date Deposited: 05 Feb 2019 06:41
Last Modified: 05 Feb 2019 06:41
URI: http://eprints.networks.imdea.org/id/eprint/1949

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