Offloading in Internet of Vehicles: A Fog-Enabled Real-Time Traffic Management System

• Published in: IEEE transactions on industrial informatics Vol. 14; no. 10; pp. 4568 - 4578
• Main Authors: Wang, Xiaojie, Ning, Zhaolong, Wang, Lei
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01-10-2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Cloud computing; Computational modeling; Computing time; Edge computing; End users; Fog computing; Internet of vehicle; Internet of Vehicles; Nodes; offloading; Queues; Queuing theory; Real time; real-time processing; Real-time systems; Response time; Roads; Servers; Time factors; Traffic management; Vehicles
• ISSN: 1551-3203; 1941-0050
• DOI: 10.1109/TII.2018.2816590

Fog computing has been merged with Internet of Vehicle (IoV) systems to provide computational resources for end users, by which low latency can be guaranteed. In this paper, we put forward a feasible solution that enables offloading for real-time traffic management in fog-based IoV systems, aiming to minimize the average response time for events reported by vehicles. First, we construct a distributed city-wide traffic management system, in which vehicles close to road side units can be utilized as fog nodes. Then, we model parked and moving vehicle-based fog nodes according to a queueing theory, and draw the conclusion that moving vehicle-based fog nodes can be modeled as an M/M/1 queue. An approximate approach is developed to solve the offloading optimization problem by decomposing it into two subproblems and scheduling traffic flows among different fog nodes. Performance analyses based on a real-world taxi-trajectory datasets are conducted to illustrate the superiority of our method.