mCloud: A Context-Aware Offloading Framework for Heterogeneous Mobile Cloud

Zhou, Bowen; Dastjerdi, Amir Vahid; Calheiros, Rodrigo N.; Srirama, Satish Narayana; Buyya, Rajkumar

doi:10.1109/tsc.2015.2511002

Cited by 121 publications

(78 citation statements)

References 26 publications

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“…The main features of TOPSIS are chosen as the alternatives that simultaneously have the shortest distance from the ideal solution and the farthest distance from the anti-ideal solution. On this basis, many decision making methods use or extend TOPSIS in order to determine the ideal solution such as [52,53,57]. Based on our survey, we found that the utilization of MCDA methods depends on the particular use at a particular step of the offloading process leading to considering a problem in part of the mobile cloud environment, such as [51], which focuses on the selection of an optimal wireless medium.…”

Section: Certainty In MCCmentioning

confidence: 99%

“…Accordingly, the authors have combined the Analytic Hierarchy Process (AHP) and fuzzy TOPSIS to make a decision to select a service from the candidate cloud services by considering the characteristics of the mobile cloud environment such as network bandwidth and the historical data based on mobile user experiences. Similarly, AHP and TOPSIS methods have been used in [52] to select a wireless medium based on the different context of the mobile devices. Moreover, this work has adopted a Min-Min heuristic to select an appropriate cloud platform among multiple types of mobile cloud resources (i.e., cloud, cloudlet, and mobile ad-hoc cloud) for offloading.…”

Section: Certainty In MCCmentioning

confidence: 99%

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Multi-Criteria Decision Analysis Methods in the Mobile Cloud Offloading Paradigm

Bangui

Bühnová

et al. 2017

JSAN

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Abstract:Mobile cloud computing (MCC) is becoming a popular mobile technology that aims to augment local resources of mobile devices, such as energy, computing, and storage, by using available cloud services and functionalities. The offloading process is one of the techniques used in MCC to enhance the capabilities of mobile devices by moving mobile data and computation-intensive operations to cloud platforms. Several techniques have been proposed to perform and improve the efficiency and effectiveness of the offloading process, such as multi-criteria decision analysis (MCDA). MCDA is a well-known concept that aims to select the best solution among several alternatives by evaluating multiple conflicting criteria, explicitly in decision making. However, as there are a variety of platforms and technologies in mobile cloud computing, it is still challenging for the offloading process to reach a satisfactory quality of service from the perspective of customers' computational service requests. Thus, in this paper, we conduct a literature review that leads to a better understanding of the usability of the MCDA methods in the offloading operation that is strongly reliant on the mobile environment, network operators, and cloud services. Furthermore, we discuss the challenges and opportunities of these MCDA techniques for offloading research in mobile cloud computing. Finally, we recommend a set of future research directions in MCDA used for the mobile cloud offloading process.

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Section: Certainty In MCCmentioning

confidence: 99%

Section: Certainty In MCCmentioning

confidence: 99%

Multi-Criteria Decision Analysis Methods in the Mobile Cloud Offloading Paradigm

Bangui

Bühnová

et al. 2017

JSAN

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“…Results show that the cost of execution time and energy are low using the decision with current context. Bowen Zhoun et al, [55] The objective of this paper is to provide computation offloading as a service to mobile devices. The application tracker, connectivity predictor and execution predictor are used as profilers.…”

Section: Related Workmentioning

confidence: 99%

Review on Compute Augmentation Techniques in Mobile Cloud Computing

Suganya¹,

Kannan²

2018

ijarcs

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“…These preceding works have assumed the case of augmentation of mobile devices through public cloud providers, which may not be true for some mobile users and mobile environments. (Zhou, Dastjerdi, Calheiros, Srirama, & Buyya, 2015) envisioned a mobile cloud environment that comprises multiple cloud resources, such as remote public clouds, cloudlet, and mobile ad-hoc cloud, to provide adaptive and context-aware mobile cloud services.…”

Section: A) MCCmentioning

confidence: 99%

Directory-based incentive management services for ad-hoc mobile clouds

Yousafzai

Chang

Gani

et al. 2016

International Journal of Information Management

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Mobile cloud computing is envisioned as a promising approach to augment the computational capabilities of mobile devices for emerging resource-intensive mobile applications. This augmentation is generally achieved through the capabilities of stationary resources in cloud data centers. However, these resources are mostly not free and sometimes not available. Mobile devices are becoming powerful day by day and can form a self-organizing mobile ad-hoc network of nearby devices and offer their resources as on-demand services to available nodes in the network. In the ad-hoc mobile cloud, devices can move after consuming or providing services to one another. During this process, the problem of incentives arises for a node to provide service to another device (or other devices) in the network, which ultimately decreases the motivation of the mobile device to form an ad-hoc mobile cloud. To solve this problem, we propose a directory-based architecture that keeps track of the retribution and reward valuations (in terms of energy saved and consumed) for devices even after they move from one ad-hoc environment to another. From simulation results, we infer that this framework increases the motivation for mobile devices to form a selforganizing proximate mobile cloud network and to share their resources in the network.

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mCloud: A Context-Aware Offloading Framework for Heterogeneous Mobile Cloud

Cited by 121 publications

References 26 publications

Multi-Criteria Decision Analysis Methods in the Mobile Cloud Offloading Paradigm

Multi-Criteria Decision Analysis Methods in the Mobile Cloud Offloading Paradigm

Review on Compute Augmentation Techniques in Mobile Cloud Computing

Directory-based incentive management services for ad-hoc mobile clouds

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