Toward cloud-based vehicular networks with efficient resource management

By Rong Yu, Yan Zhang, Stein Gjessing, Wenlong Xia, Kun Yang. IEEE Network, 2013

407 citations recorded by the source corpus.

In the era of the Internet of Things, all components in intelligent transportation systems will be connected to improve transport safety, relieve traffic congestion, reduce air pollution, and enhance the comfort of driving. The vision of all vehicles connected poses a significant challenge to the collection and storage of large amounts of traffic-related data. In this article, we propose to integrate cloud computing into vehicular networks such that the vehicles can share computation resources, storage resources, and bandwidth resources. The proposed architecture includes a vehicular cloud, a roadside cloud, and a central cloud. Then we study cloud resource allocation and virtual machine migration for effective resource management in this cloud-based vehicular network. A game-theoretical approach is presented to optimally allocate cloud resources. Virtual machine migration due to vehicle mobility is solved based on a resource reservation scheme.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering, Information Systems

View Paper: https://www.semanticscholar.org/paper/db181966ea01d16530b1b452d44afdc051a7c9ba

How researchers see this paper

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

In Computer Networks and Communications

1. Jaime Lloret
2. A. Abdullah
3. Ke Zhang
4. Jiafu Wan

In Electrical and Electronic Engineering

1. Jaime Lloret
2. Laurence Tianruo Yang
3. A. Abdullah
4. Jiafu Wan

In Information Systems

1. Chin-Teng Lin
2. Mukesh Prasad
3. Laurence Tianruo Yang
4. Ke Zhang
5. Jiafu Wan

Citations in the corpus

• A Survey on Platoon-Based Vehicular Cyber-Physical Systems (2016, unknown): “Similar work was done in [50], wherein cloud computing was integrated into vehicular networks such that the vehicles can share computation resources, storage resources, and bandwidth resources.”
• On Multi-Access Edge Computing: A Survey of the Emerging 5G Network Edge Cloud Architecture and Orchestration (2017, unknown): “An architecture study for cloud connectivity among vehicles and towards edge-cloud platforms enabling a number of on-board services is presented in [66] considering also resource management and VM mobility.”
• Computation Offloading and Resource Allocation For Cloud Assisted Mobile Edge Computing in Vehicular Networks (2019, background): “evaluated the cloud resource allocation for an effective resource management [13].”
• Context-aware vehicular cyber-physical systems with cloud support: architecture, challenges, and solutions (2014, background): “In [4], the hierarchical cloud architecture for vehicular networks was proposed, and the proposed architecture included a vehicular cloud, a roadside cloud, and a central cloud.”
• Internet of Vehicles: Motivation, Layered Architecture, Network Model, Challenges, and Future Aspects (2016, methodology): “Intelligent computation in big traffic data using cloud computing for non-safety services and fog computing for safety services is the core of VCPS, and the same is supported in the layered architecture of IoV as artificial intelligence layer [87], [88].”