Abstract—Concurrent processing of sophisticated tasks on mobile devices could consume a lot of energy and processing time because of their limited resources. In order to offload mobile devices, some tasks are uploaded to the cloud server for execution. However, it is very difficult to choose which tasks to upload to the cloud because it needs to ensure two requirements: Optimizing energy costs and optimizing execution time costs. In this paper, we introduce a method to offload mobile devices when it processes multiple tasks concurrently. By applying the proposed energy automata from previous studies, our method allows for the identification of factors influencing the energy consumption and execution time of tasks, while also proposing an objective function and algorithms to make the offloading decision. When we applied the proposed method to an actual image processing application to process 1000 photos on a mobile device, it could save a maximum of 24.1% of energy, 37.6% of processing time, and an average of 18% of energy, 21% of processing time compared to non-offloading.
Index Terms—Android, computation offloading, mobile cloud computing, power model
Anh-Tu Bui and Van-Viet Nguyen are with University of Engineering and Technology, Hanoi, Vietnam and Thai Nguyen University of Information and Communication Technology, Thai Nguyen, Vietnam.
Ninh-Thuan Truong is with University of Engineering and Technology, Hanoi, Vietnam.
*Correspondence: batu@ictu.edu.vn (A.T.B.)
Cite: Anh-Tu Bui*, Van-Viet Nguyen, and Ninh-Thuan Truong, "Time-and-Energy Consumption Offloading for Mobile Devices in Mobile Cloud Computing," International Journal of Future Computer and Communication vol. 12, no. 3, pp. 63-69, 2023.
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