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An Adaptive Approach Towards Computation Offloading for Mobile Cloud Computing

An Adaptive Approach Towards Computation Offloading for Mobile Cloud Computing

Archana Kero, Abhirup Khanna, Devendra Kumar, Amit Agarwal
Copyright: © 2019 |Volume: 14 |Issue: 2 |Pages: 22
ISSN: 1554-1045|EISSN: 1554-1053|EISBN13: 9781522564492|DOI: 10.4018/IJITWE.2019040104
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MLA

Kero, Archana, et al. "An Adaptive Approach Towards Computation Offloading for Mobile Cloud Computing." IJITWE vol.14, no.2 2019: pp.52-73. http://doi.org/10.4018/IJITWE.2019040104

APA

Kero, A., Khanna, A., Kumar, D., & Agarwal, A. (2019). An Adaptive Approach Towards Computation Offloading for Mobile Cloud Computing. International Journal of Information Technology and Web Engineering (IJITWE), 14(2), 52-73. http://doi.org/10.4018/IJITWE.2019040104

Chicago

Kero, Archana, et al. "An Adaptive Approach Towards Computation Offloading for Mobile Cloud Computing," International Journal of Information Technology and Web Engineering (IJITWE) 14, no.2: 52-73. http://doi.org/10.4018/IJITWE.2019040104

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Abstract

The widespread acceptability of mobile devices in present times have caused their applications to be increasingly rich in terms of the functionalities they provide to the end users. Such applications might be very prevalent among users but the execution results in dissipating many of the device end resources. Mobile cloud computing (MCC) has a solution to this problem by offloading certain parts of the application to cloud. At the first place, one might find computation offloading quite promising in terms of saving device end resources but eventually may result in being the other way around if performed in a static manner. Frequent changes in device end resources and computing environment variables may lead to a reduction in the efficiency of offloading techniques and even cause a drop in the quality of service for applications involving the use of real-time information. In order to overcome this problem, the authors propose an adaptive computation offloading framework for data stream applications wherein applications are partitioned dynamically followed by being offloaded depending upon the device end parameters, network conditions, and cloud resources. The article also talks about the proposed algorithm that depicts the workflow of the offloading model. The proposed model is simulated using the CloudSim simulator. In the end, the authors illustrate the working of the proposed system along with the simulated results.

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