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Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2018 Vol.8(4): 367-371 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2018.8.4.713

A Cloud- Side Decision Offloading Scheme for Mobile Cloud Computing

Hamid Jadad, Abderezak Touzene, Khaled Day, and Nasser Alzeidir
Abstract—Mobile code offloading is one of the techniques that are used to migrate computation-intensive tasks of mobile applications from mobile devices to the cloud. Many offloading systems make online offloading decisions to ensure that offloading provides significant gain in battery saving and execution time. However, this offloading decision process produces a significant overhead when it is implemented in the mobile device. We call these approaches device-side approaches. In this paper, we propose a new offloading approach that shifts the offloading decision process components to the cloud. In other words, the offloading decision is made in the cloud and we call it cloud-side offloading approach. The evaluation results show that the new cloud—side’s approach saves around 20% of energy and execution time compared to the device-side approach.

Index Terms—Mobile cloud computing, offloading, cloud-side decision, execution time, energy saving.

Hamid Jadad, Abderezak Touzene, Khalid Day, Nasser Alziedi are with the Sultan Qaboos University, Muscat, Sultanate of Oman (e-mail: hamidjadad@gmail.com, {touzene, kday, alzidi}@squ.edu.om).

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Cite: Hamid Jadad, Abderezak Touzene, Khaled Day, and Nasser Alzeidir, "A Cloud- Side Decision Offloading Scheme for Mobile Cloud Computing," International Journal of Machine Learning and Computing vol. 8, no. 4, pp. 367-371, 2018.

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