Application optimization in mobile cloud computing: Motivation, taxonomies, and open challenges

被引:111
作者
Ahmed, Ejaz [1 ]
Gani, Abdullah [1 ]
Sookhak, Mehdi [1 ]
Ab Hamid, Siti Hafizah [1 ]
Xia, Feng [2 ]
机构
[1] Univ Malaya, Fac Comp Sci & Informat Technol, Mobile Cloud Comp Res Lab, Kuala Lumpur, Malaysia
[2] Dalian Univ Technol, Sch Software, Mobile & Social Comp Lab, Dalian, Peoples R China
关键词
Mobile cloud computing; Cloud-based mobile applications; Application optimization; Cloud-based mobile application execution frameworks; FRAMEWORK; ART;
D O I
10.1016/j.jnca.2015.02.003
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In Mobile Cloud Computing (MCC), migrating an application processing to the cloud data centers enables the execution of resource-intensive applications on the mobile devices. However, the resource-intensive migration approaches and the intrinsic limitations of the wireless medium impede the applications from attaining optimal performance in the cloud. Hence, executing the application with low cost, minimal overhead, and non-obtrusive migration is a challenging research area. This paper presents the state-of-the-art mobile application execution frameworks and provides the readers a discussion on the optimization strategies that facilitate attaining the effective design, efficient deployment, and application migration with optimal performance in MCC. We highlight the significance of optimizing the application performance by providing real-life scenarios requiring the effective design, efficient deployment, and optimal application execution in MCC. The paper also presents cloud-based mobile application-related taxonomies. Moreover, we compare the application execution frameworks on the basis of significant optimization parameters that affect performance of the applications and mobile devices in MCC. We also discuss the future research directions for optimizing the application in MCC. Finally, we conclude the paper by highlighting the key contributions and possible research directions in cloud-based mobile application optimization. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:52 / 68
页数:17
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