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Vehicular Edge Computing and Networking: A Survey

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TLDR
A comprehensive survey of state-of-the-art research on VEC can be found in this paper, where the authors provide an overview of VEC, including the introduction, architecture, key enablers, advantages, challenges as well as several attractive application scenarios.
Abstract
As one key enabler of Intelligent Transportation System (ITS), Vehicular Ad Hoc Network (VANET) has received remarkable interest from academia and industry. The emerging vehicular applications and the exponential growing data have naturally led to the increased needs of communication, computation and storage resources, and also to strict performance requirements on response time and network bandwidth. In order to deal with these challenges, Mobile Edge Computing (MEC) is regarded as a promising solution. MEC pushes powerful computational and storage capacities from the remote cloud to the edge of networks in close proximity of vehicular users, which enables low latency and reduced bandwidth consumption. Driven by the benefits of MEC, many efforts have been devoted to integrating vehicular networks into MEC, thereby forming a novel paradigm named as Vehicular Edge Computing (VEC). In this paper, we provide a comprehensive survey of state-of-art research on VEC. First of all, we provide an overview of VEC, including the introduction, architecture, key enablers, advantages, challenges as well as several attractive application scenarios. Then, we describe several typical research topics where VEC is applied. After that, we present a careful literature review on existing research work in VEC by classification. Finally, we identify open research issues and discuss future research directions.

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Citations
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Journal ArticleDOI

Cooperative Computation Offloading and Resource Allocation for Blockchain-Enabled Mobile-Edge Computing: A Deep Reinforcement Learning Approach

TL;DR: This article develops an asynchronous advantage actor–critic-based cooperation computation offloading and resource allocation algorithm to solve the MDP problem and designs a multiobjective function to maximize the computation rate of MEC systems and the transaction throughput of blockchain systems.
Journal ArticleDOI

Reliable Computation Offloading for Edge-Computing-Enabled Software-Defined IoV

TL;DR: Performance evaluation results validate that the proposed scheme is indeed capable of reducing the latency as well as improving the reliability of the EC-SDIoV.
Journal ArticleDOI

MEC-Assisted Immersive VR Video Streaming Over Terahertz Wireless Networks: A Deep Reinforcement Learning Approach

TL;DR: This article proposes to minimize the long-term energy consumption of a THz wireless access-based MEC system for high quality immersive VR video services support by jointly optimizing the viewport rendering offloading and downlink transmit power control policies and an asynchronous advantage actor–critic (A3C)-based joint optimization algorithm.
Journal ArticleDOI

Mobility-Aware Proactive Edge Caching for Connected Vehicles Using Federated Learning

TL;DR: Experimental results demonstrate that MPCF outperforms other baseline caching schemes in terms of the cache hit ratio in vehicular edge networks, and can greatly improve cache performance, effectively protect users’ privacy and significantly reduce communication costs.
Journal ArticleDOI

Blockchain-Enabled Secure Data Sharing Scheme in Mobile-Edge Computing: An Asynchronous Advantage Actor–Critic Learning Approach

TL;DR: In this article, a secure data sharing scheme in the blockchain-enabled mobile edge computing system using an asynchronous learning approach is presented, and an adaptive privacy-preserving mechanism according to available system resources and privacy demands of users is presented.
References
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Journal ArticleDOI

A Survey on Mobile Edge Computing: The Communication Perspective

TL;DR: A comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management is provided in this paper, where a set of issues, challenges, and future research directions for MEC are discussed.
Journal ArticleDOI

A survey of mobile cloud computing: architecture, applications, and approaches

TL;DR: A survey of MCC is given, which helps general readers have an overview of the MCC including the definition, architecture, and applications and the issues, existing solutions, and approaches are presented.
Journal ArticleDOI

A Survey of Software-Defined Networking: Past, Present, and Future of Programmable Networks

TL;DR: The SDN architecture and the OpenFlow standard in particular are presented, current alternatives for implementation and testing of SDN-based protocols and services are discussed, current and future SDN applications are examined, and promising research directions based on the SDN paradigm are explored.
Journal ArticleDOI

Mobile Edge Computing: A Survey

TL;DR: The definition of MEC, its advantages, architectures, and application areas are provided; where the security and privacy issues and related existing solutions are also discussed.
Journal ArticleDOI

Network Function Virtualization: State-of-the-Art and Research Challenges

TL;DR: In this article, the authors survey the state-of-the-art in NFV and identify promising research directions in this area, and also overview key NFV projects, standardization efforts, early implementations, use cases, and commercial products.
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