Fog computing is a new systematic paradigm which provides low latency enabled cloud services to mobile and Internet of Things (IoT) networks by provisioning the computation capability within the radio access network (RAN) assignable to mobile end users. In this letter, an energy optimal offloading scheme based on a probabilistic priority model of cloud tasks is investigated over fog computing networks. The optimization problem jointly minimizes the energy consumption of user equipment (UE) and the fog server. Simulation results show that the proposed joint UE and fog server energy optimization (JUFO) scheme provides a better performance compared to the conventional offloading scheme, which operates strictly within the determined delay bound.
Bibliographical noteFunding Information:
Manuscript received March 2, 2019; accepted April 7, 2019. Date of publication April 16, 2019; date of current version August 21, 2019. This work was supported by the Ministry of Interior and Safety of Korean Government through the Disaster Prediction and Mitigation Technology Development Program under Grant MOIS-DP-2015-10. The associate editor coordinating the review of this paper and approving it for publication was X. Chu. (Corresponding author: Jong-Moon Chung.) J. Kim, W. Yoo, and J.-M. Chung are with the School of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, South Korea (e-mail: firstname.lastname@example.org; email@example.com; firstname.lastname@example.org).
© 2012 IEEE.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Electrical and Electronic Engineering