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.
Highlights
Mobile cloud computing (MCC) is one of the critical instances in cloud-based systems and key innovations in Internet of Things (IoT) networks [1] where mobile devices exploit external cloud resources to augment their computational capabilities, e.g., storage space, and optimize their local services [2,3,4]
The contributions of this study can be summarized as follows: (1) Based on our literature review, we focus on identifying the multi-criteria decision analysis (MCDA) methods most widely used in cloud offloading by selecting specific approaches in mobile cloud offloading that clearly utilize MCDA methods
The mobile cloud offloading papers used for this purpose were selected by searching academic databases and well-known publishers such as Sciencedirect, Google Scholar, ACM Digital Library, of MCDA methods in offloading by using two keywords which are: Certainty that describes MCDA methods using determined values of criteria to solve an MCDA issue, and uncertainty that describes the MCDA methods dealing with imprecise systems
Summary
Mobile cloud computing (MCC) is one of the critical instances in cloud-based systems and key innovations in Internet of Things (IoT) networks [1] where mobile devices exploit external cloud resources to augment their computational capabilities, e.g., storage space, and optimize their local services [2,3,4]. The main steps for the execution of an m-healthcare application are as follows: Generate large amounts of healthcare data which consumes resources of the mobile device, offload the application onto a cloud server, and send the result back to the mobile patient In this case, the m-healthcare application exploits the advantages of a cloud environment to make precise and real-time decisions. The main goal of MCDA methods is to solve complex problems by selecting, comparing, and ranking different attributes of multiple alternatives in a flexible manner This means that the MCDA techniques handle the diversity in MCC by managing different information from various environments, considering many factors that affect the selection process and deciding which service is the most suitable one for the end-user when making the final decision. How to offload: It introduces an offloading strategy that describes how the device should schedule code offloading operations
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