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

By Xiaojie Wang, Zhaolong Ning, Lei Wang. IEEE Transactions on Industrial Informatics, 2018

346 citations recorded by the source corpus.

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.

Subfields: Automotive Engineering, Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/74e6710188e3deeee13304c10e2e93dc1e807998

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

  1. Kaoru Ota
  2. Mianxiong Dong
  3. Liangzhi Li

In Computer Networks and Communications

  1. Liangzhi Li
  2. Kaoru Ota
  3. Mianxiong Dong
  4. Huseyin Arslan
  5. Haji. M. Furqan
  6. Zhaolong Ning
  7. Jehad M. Hamamreh
  8. Dusist Niyato

In Information Systems

  1. Kaoru Ota
  2. Mianxiong Dong
  3. Liangzhi Li

Citations in the corpus