Cloud-based augmentation for mobile devices: motivation, taxonomies, and open challenges
Recently, Cloud-based Mobile Augmentation (CMA) approaches have gained remarkable ground from academia and industry. CMA is the state-of-the-art mobile augmentation model that employs resource-rich clouds to increase, enhance, and optimize computing capabilities of mobile devices aiming at execution...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Institute of Electrical and Electronics Engineers (IEEE)
2013
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| Online Access: | http://eprints.um.edu.my/8295/1/Augmentation.pdf |
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| author | Abolfazli, Saeid Sanaei, Zohreh Ahmed, Ejaz Gani, Abdullah Buyya, Rajkumar |
| author_facet | Abolfazli, Saeid Sanaei, Zohreh Ahmed, Ejaz Gani, Abdullah Buyya, Rajkumar |
| author_sort | Abolfazli, Saeid |
| collection | UM |
| description | Recently, Cloud-based Mobile Augmentation (CMA) approaches have gained remarkable ground from academia and industry. CMA is the state-of-the-art mobile augmentation model that employs resource-rich clouds to increase, enhance, and optimize computing capabilities of mobile devices aiming at execution of resource-intensive mobile applications. Augmented mobile devices envision to perform extensive computations and to store big data beyond their intrinsic capabilities with least footprint and vulnerability. Researchers utilize varied cloud-based computing resources (e.g., distant clouds and nearby mobile nodes) to meet various computing requirements of mobile users. However, employing cloud-based computing resources is not a straightforward panacea. Comprehending critical factors (e.g., current state of mobile client and remote resources) that impact on augmentation process and optimum selection of cloud-based resource types are some challenges that hinder CMA adaptability. This paper comprehensively surveys the mobile augmentation domain and presents taxonomy of CMA approaches. The objectives of this study is to highlight the effects of remote resources on the quality and reliability of augmentation processes and discuss the challenges and opportunities of employing varied cloud-based resources in augmenting mobile devices. We present augmentation definition, motivation, and taxonomy of augmentation types, including traditional and cloud-based. We critically analyze the state-of-the-art CMA approaches and classify them into four groups of distant fixed, proximate fixed, proximate mobile, and hybrid to present a taxonomy. Vital decision making and performance limitation factors that influence on the adoption of CMA approaches are introduced and an exemplary decision making flowchart for future CMA approaches are presented. Impacts of CMA approaches on mobile computing is discussed and open challenges are presented as the future research directions. |
| first_indexed | 2024-03-06T05:20:58Z |
| format | Article |
| id | um.eprints-8295 |
| institution | Universiti Malaya |
| language | English |
| last_indexed | 2024-03-06T05:20:58Z |
| publishDate | 2013 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | um.eprints-82952018-10-12T02:18:30Z http://eprints.um.edu.my/8295/ Cloud-based augmentation for mobile devices: motivation, taxonomies, and open challenges Abolfazli, Saeid Sanaei, Zohreh Ahmed, Ejaz Gani, Abdullah Buyya, Rajkumar QA75 Electronic computers. Computer science Recently, Cloud-based Mobile Augmentation (CMA) approaches have gained remarkable ground from academia and industry. CMA is the state-of-the-art mobile augmentation model that employs resource-rich clouds to increase, enhance, and optimize computing capabilities of mobile devices aiming at execution of resource-intensive mobile applications. Augmented mobile devices envision to perform extensive computations and to store big data beyond their intrinsic capabilities with least footprint and vulnerability. Researchers utilize varied cloud-based computing resources (e.g., distant clouds and nearby mobile nodes) to meet various computing requirements of mobile users. However, employing cloud-based computing resources is not a straightforward panacea. Comprehending critical factors (e.g., current state of mobile client and remote resources) that impact on augmentation process and optimum selection of cloud-based resource types are some challenges that hinder CMA adaptability. This paper comprehensively surveys the mobile augmentation domain and presents taxonomy of CMA approaches. The objectives of this study is to highlight the effects of remote resources on the quality and reliability of augmentation processes and discuss the challenges and opportunities of employing varied cloud-based resources in augmenting mobile devices. We present augmentation definition, motivation, and taxonomy of augmentation types, including traditional and cloud-based. We critically analyze the state-of-the-art CMA approaches and classify them into four groups of distant fixed, proximate fixed, proximate mobile, and hybrid to present a taxonomy. Vital decision making and performance limitation factors that influence on the adoption of CMA approaches are introduced and an exemplary decision making flowchart for future CMA approaches are presented. Impacts of CMA approaches on mobile computing is discussed and open challenges are presented as the future research directions. Institute of Electrical and Electronics Engineers (IEEE) 2013-07-19 Article PeerReviewed application/pdf en http://eprints.um.edu.my/8295/1/Augmentation.pdf Abolfazli, Saeid and Sanaei, Zohreh and Ahmed, Ejaz and Gani, Abdullah and Buyya, Rajkumar (2013) Cloud-based augmentation for mobile devices: motivation, taxonomies, and open challenges. IEEE Communications Surveys & Tutorials, 99. pp. 1-32. ISSN 1553-877X, DOI https://doi.org/10.1109/SURV.2013.070813.00285 <https://doi.org/10.1109/SURV.2013.070813.00285>. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6563280&queryText%3Dcloud-based+augmentation 10.1109/SURV.2013.070813.00285 |
| spellingShingle | QA75 Electronic computers. Computer science Abolfazli, Saeid Sanaei, Zohreh Ahmed, Ejaz Gani, Abdullah Buyya, Rajkumar Cloud-based augmentation for mobile devices: motivation, taxonomies, and open challenges |
| title | Cloud-based augmentation for mobile devices: motivation, taxonomies, and open challenges |
| title_full | Cloud-based augmentation for mobile devices: motivation, taxonomies, and open challenges |
| title_fullStr | Cloud-based augmentation for mobile devices: motivation, taxonomies, and open challenges |
| title_full_unstemmed | Cloud-based augmentation for mobile devices: motivation, taxonomies, and open challenges |
| title_short | Cloud-based augmentation for mobile devices: motivation, taxonomies, and open challenges |
| title_sort | cloud based augmentation for mobile devices motivation taxonomies and open challenges |
| topic | QA75 Electronic computers. Computer science |
| url | http://eprints.um.edu.my/8295/1/Augmentation.pdf |
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