RMCC: A RESTful mobile cloud computing framework for exploiting adjacent service-based mobile cloudlets

Mobile devices, especially smartphones are increasingly gaining ground in several domains, particularly healthcare, telemonitoring, and education to perform Resource-intensive Mobile Applications (RiMA). However, constrained resources, especially CPU and battery hinder their successful adoption. Mob...

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Bibliographic Details
Main Authors: Abolfazli, S., Sanaei, Z., Gani, Abdullah, Xia, F., Lin, Wei-Ming
Format: Conference or Workshop Item
Language:English
Published: 2014
Subjects:
Online Access:http://eprints.um.edu.my/11349/1/RMCC_IEEE_CloudCom14.pdf
Description
Summary:Mobile devices, especially smartphones are increasingly gaining ground in several domains, particularly healthcare, telemonitoring, and education to perform Resource-intensive Mobile Applications (RiMA). However, constrained resources, especially CPU and battery hinder their successful adoption. Mobile Cloud Computing (MCC) aims to augment computational capabilities of resource-constraint mobile devices and conserve their native resources by remotely performing intensive tasks. In typical MCC solutions, intensive tasks are offloaded to distant VM-based cloud datacenters or cloudlets whose exploitation originates long WAN latency and/or virtualization overhead degrading RiMA execution efficiency. In this paper, a lightweight Resource-oriented MCC (RMCC) architecture is proposed that exploits resources of plethora of Adjacent Service-based Mobile Cloudlets (ASMobiC) as fine-grained mobile service providers. In RMCC, ASMobiCs host prefabricated RESTful services to be asynchronously called by mobile service consumers at runtime. RMCC is a RESTful cross-platform architecture functional on major mobile OSs (e.g., Android and iOS) and realizes utilization of the computing resources of off-the-shelve outdated or damaged-yet-functioning mobile devices towards green MCC. Results of benchmarking advocate significant mean time- and energy-saving of 87% and 71.45%, respectively when intensive tasks are executed in ASMobiCs.