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

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08616760.pdf (5.205Mb)
Identificadores
URI: http://hdl.handle.net/20.500.12761/675
ISSN: 2169-3536
DOI: DOI: 10.1109/ACCESS.2019.2892508
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Autor(es)
Fiandrino, Claudio; Allio, Nicholas; Kliazovich, Dzmitry; Giaccone, Paolo; Bouvry, Pascal
Fecha
2019-01-17
Resumen
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.
Compartir
Ficheros
08616760.pdf (5.205Mb)
Identificadores
URI: http://hdl.handle.net/20.500.12761/675
ISSN: 2169-3536
DOI: DOI: 10.1109/ACCESS.2019.2892508
Metadatos
Mostrar el registro completo del ítem

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