Amirkabir University of Technology AUT Journal of Electrical Engineering 2588-2910 50 1 2018 06 01 Reduction of Energy Consumption in Mobile Cloud Computing by ‎Classification of Demands and Executing in Different Data Centers 59 66 2689 10.22060/eej.2017.13284.5150 EN H. Yeganeh Department of Electrical and Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran 0000-0002-6949-4622 A. Salahi Iran Telecommunication Research Center, Tehran, Iran 0000-0002-8486-8151 M. A Pourmina Department of Electrical and Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran Journal Article 2017 08 15 <strong> </strong>In recent years, mobile networks have faced with the increase of traffic demand. By emerging mobile applications and cloud computing, Mobile Cloud Computing (MCC) has been introduced. In this research, we focus on the 4th and 5th generation of mobile networks. Data Centers (DCs) are connected to each other by high-speed links in order to minimize delay and energy consumption. By considering a model of the geographical distribution of DCs which uses a wideband optical network, renewable energy and sharing resources for new generations of mobile networks, the real effect of issues on the consumed energy, cost, and profit in the mobile cloud computing are investigated. We derived a penalty function for cost and then by using Lyapunov optimization theorem; we designed an algorithm to minimize the average cost of energy consumption based on the online information in MCC. The time average cost is at most O(1/V) above the optimum target, while the average queue size is O(V). The parameter V can be tuned to make the time average cost as close to (or below) the optimum as desired. We designed three scenarios and two classes of applications to set up our simulation environment. The provided results illustrate the efficiency of our proposed scheme and validate the mathematical model. https://eej.aut.ac.ir/article_2689_577fd60255d4bb0f466464849ffe6d8e.pdf