Title: A new energy-preserving cloud offloading algorithm for smart mobile devices

Authors: Samar A. Said; Sameh A. Salem; Samir G. Sayed

Addresses: Faculty of Engineering, Department of Electronics, Communications and Computer Engineering, Helwan University, Cairo, Egypt ' Faculty of Engineering, Department of Electronics, Communications and Computer Engineering, Helwan University, Cairo, Egypt ' Faculty of Engineering, Department of Electronics, Communications and Computer Engineering, Helwan University, Cairo, Egypt

Abstract: The advent of mobile devices becomes the way for various technological developments in mobile communication and information technology. However, mobile users expect to access computational intensive applications through resource constrained mobile devices. Consequently the growing demands for boosting the computations, storage and memory resources became essential for mobile devices. A new trend to incorporate mobile devices and cloud resources with the existence of the network connectivity is named as mobile cloud computing (MCC). MCC is the greatest solution to increase the application processing capabilities on mobile devices by migrating the application to the cloud servers with on demand and unlimited resources. This paper proposes a new energy-preserving cloud offloading algorithm. The proposed algorithm estimates the application computational time and uses multiple weighted parameters to give accurate offloading decisions. Simulation results on various applications clarify that the proposed algorithm is capable of estimating an application's computation time with high correlations compared with the real execution time. This improves the offloading decision which actually preserves the energy and reduces the execution time of mobile applications.

Keywords: mobile cloud; offloading decision; cloud computing; energy preserving.

DOI: 10.1504/IJHI.2019.099669

International Journal of Hybrid Intelligence, 2019 Vol.1 No.1, pp.5 - 22

Received: 06 Nov 2017
Accepted: 02 Feb 2018
Published online: 20 May 2019 *