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حامی فایل دانلود مقاله A Study on Critical Analysis of Computational Offloading Frameworks for Mobile Cloud Computing انتشار 2015 دانلود با لینک مستقیم و پر سرعت .
Volume 47, January 2015, Pages 47–60
Muhammad Shiraz*, Mehdi Sookhak, Abdullah Gani, Syed Adeel Ali Shah
Abstract
Despite of substantial technological advancements in the recent years, Smart Mobile Devices (SMDs) are still low potential computing
devices. Therefore, Mobile Cloud Computing (MCC) deploys computational offloading for augmenting SMDs. The contemporary Computational
Offloading Frameworks (COFs) implement resources intensive procedures for computational offloading, which involve the overhead of
transmitting application binary code and deployment of distributed platform at runtime. As a result, energy consumption cost and turnaround
time of the mobile application and overhead of data transmission is increased. Nevertheless, the resources limited nature of SMDs requires
lightweight technique for leveraging the application processing services of computational clouds. This paper critically analyzes the resource
intensive nature of the latest existing computational offloading techniques for MCC and highlights technical issues in the establishment of
distributed application processing platform at runtime. A prototype application is evaluated with different computation intensities in the real
MCC environment. Analysis of the results shows that additional computing resources are utilized in the deployment of distributed application
processing platform at runtime such as: 31.6 % additional energy is consumed, 39% additional time is taken and 13241.2 KB data is transmitted
in offloading different computational intensive components of the prototype mobile application. Finally, we highlight technical issues in the
existing computational offloading techniques for MCC, which draw attention for the future research in computational offloading for MCC and
assist in developing lightweight procedures for computational offloading in MCC.
Keywords: Mobile Cloud Computing, Distributed Systems, Computational offloading, Resource Intensive,
Lightweight
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