Cloud-Based Augmentation for Mobile Devices: Motivation, Taxonomies, and Open Challenges
By Saeid Abolfazli, Zohreh Sanaei, Ejaz Ahmed, Abdullah Bin Gani, Rajkumar Buyya. IEEE Communications Surveys and Tutorials, 2013
452 citations recorded by the source corpus.
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.
Subfields: Computer Networks and Communications, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/a9d3b9c1ba4158d19b4c5f573747ebb0da8d4298
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Citations in the corpus
- Joint Computation Offloading and Interference Management in Wireless Cellular Networks with Mobile Edge Computing (2017, background): “This has led to an exponential growth of demand in not only high data rate but also high computational capability in wireless cellular networks [2].”
- Heterogeneity in Mobile Cloud Computing: Taxonomy and Open Challenges (2014, background): “without commitment to complete assigned jobs (they can leave a task anytime at any stage of computing), whereas clouds provide paid services with assured availability, quality, and commitment according to the negotiated Service-Level Agreement (SLA) between cloud vendor and mobile client [16].”
- Energy Efficiency Tradeoff Mechanism Towards Wireless Green Communication: A Survey (2016, background): “although the effect is small [70], [111], [112].”
- Multiuser Joint Task Offloading and Resource Optimization in Proximate Clouds (2017, background): “Mobile cloud computing uses either distant or proximate clouds to enhance computing capabilities of mobile devices, to support mainly resource-intensive applications [17].”
- Big Data and cloud computing: innovation opportunities and challenges (2017, background): “For example, Abolfazli et al. (2014) surveyed the mobile augmentation domain and Soyata et al. (2012) proposed the MObile Cloud-based Hybrid Architecture (MOCHA) for mobile-cloud computing applications including object recognition in the battlefield.”
- A Secure Biometrics-Based Multi-Server Authentication Protocol Using Smart Cards (2015, background): “In the recent couple of decades, more and more transactions for the mobile devices have been implemented on the Internet or wireless networks due to the portability property of mobile devices, such as laptops, smart cards and smart phones [2].”
- Osmotic Computing: A New Paradigm for Edge/Cloud Integration (2016, background): “The related approach [24] of “mobile offloading” is centered on the need to off-load complex and long running tasks from mobile devices to Cloud-based datacenters.”