A Survey on Computation Offloading for Vehicular Edge Computing

Vehicular Edge Computing (VEC) is a promising new paradigm that has received a lot of attention recently. Computation Offloading (CO) can migrate computing tasks to the network edge of VEC, which is critical for mobile applications that are sensitive to computation power. However, the dynamicity and randomness of Internet of Vehicles (IoV) lead to new features and challenges in vehicular computation offloading. Therefore, we focus on the CO in VEC. This paper depicts a broad methodical literature analysis of CO scheme and CO methods in VEC domains and divides the current works of CO into various categories. The methodical analysis of this research will help researchers to find the important characteristics of CO and select the most appropriate algorithm for computing tasks. Challenges and research directions have also been suggested in this paper.

[1]  Lei Shu,et al.  Parked Vehicle Edge Computing: Exploiting Opportunistic Resources for Distributed Mobile Applications , 2018, IEEE Access.

[2]  Laurence T. Yang,et al.  Defending ON–OFF Attacks Using Light Probing Messages in Smart Sensors for Industrial Communication Systems , 2018, IEEE Transactions on Industrial Informatics.

[3]  Weisong Shi,et al.  Edge Computing: Vision and Challenges , 2016, IEEE Internet of Things Journal.

[4]  Qi Zhang,et al.  Offloading Schemes in Mobile Edge Computing for Ultra-Reliable Low Latency Communications , 2018, IEEE Access.

[5]  Min Chen,et al.  Task Offloading for Mobile Edge Computing in Software Defined Ultra-Dense Network , 2018, IEEE Journal on Selected Areas in Communications.

[6]  Gaofeng Nie,et al.  Energy-Saving Offloading by Jointly Allocating Radio and Computational Resources for Mobile Edge Computing , 2017, IEEE Access.

[7]  Jingyu Wang,et al.  Knowledge-Driven Service Offloading Decision for Vehicular Edge Computing: A Deep Reinforcement Learning Approach , 2019, IEEE Transactions on Vehicular Technology.

[8]  Zhou Su,et al.  Computation Offloading Scheme to Improve QoE in Vehicular Networks with Mobile Edge Computing , 2018, 2018 10th International Conference on Wireless Communications and Signal Processing (WCSP).

[9]  Jie Zhang,et al.  FiWi-Enhanced Vehicular Edge Computing Networks: Collaborative Task Offloading , 2019, IEEE Vehicular Technology Magazine.

[10]  Huaiyu Dai,et al.  A Truthful Reverse-Auction Mechanism for Computation Offloading in Cloud-Enabled Vehicular Network , 2019, IEEE Internet of Things Journal.

[11]  Soumaya Cherkaoui,et al.  A Game Theory Based Efficient Computation Offloading in an UAV Network , 2019, IEEE Transactions on Vehicular Technology.

[12]  Hong Ji,et al.  Federated Offloading Scheme to Minimize Latency in MEC-Enabled Vehicular Networks , 2018, 2018 IEEE Globecom Workshops (GC Wkshps).

[13]  Ke Zhang,et al.  Computation Offloading and Resource Allocation For Cloud Assisted Mobile Edge Computing in Vehicular Networks , 2019, IEEE Transactions on Vehicular Technology.

[14]  Lili Du,et al.  Information Dissemination Delay in Vehicle-to-Vehicle Communication Networks in a Traffic Stream , 2015, IEEE Transactions on Intelligent Transportation Systems.

[15]  Xiongwen Zhao,et al.  Task Offloading for Vehicular Fog Computing under Information Uncertainty: A Matching-Learning Approach , 2019, 2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC).

[16]  Tony Q. S. Quek,et al.  Computation Offloading for Mobile Edge Computing Enabled Vehicular Networks , 2019, IEEE Access.

[17]  Yan Zhang,et al.  Optimal delay constrained offloading for vehicular edge computing networks , 2017, 2017 IEEE International Conference on Communications (ICC).

[18]  Xin Liu,et al.  Adaptive Learning-Based Task Offloading for Vehicular Edge Computing Systems , 2019, IEEE Transactions on Vehicular Technology.

[19]  Yan Zhang,et al.  Energy-efficient workload offloading and power control in vehicular edge computing , 2018, 2018 IEEE Wireless Communications and Networking Conference Workshops (WCNCW).

[20]  Yusheng Ji,et al.  Mobile edge computing based VM migration for QoS improvement , 2017, 2017 IEEE 6th Global Conference on Consumer Electronics (GCCE).

[21]  Hong Ji,et al.  Dynamic Offloading Scheduling Scheme for MEC-enabled Vehicular Networks , 2018, 2018 IEEE/CIC International Conference on Communications in China (ICCC Workshops).

[22]  Pengju Liu,et al.  Matching-Based Task Offloading for Vehicular Edge Computing , 2019, IEEE Access.

[23]  Du Xu,et al.  Joint Load Balancing and Offloading in Vehicular Edge Computing and Networks , 2019, IEEE Internet of Things Journal.

[24]  Zhenyu Zhou,et al.  Energy-Efficient Edge Computing Service Provisioning for Vehicular Networks: A Consensus ADMM Approach , 2019, IEEE Transactions on Vehicular Technology.

[25]  Chao Yang,et al.  Efficient Mobility-Aware Task Offloading for Vehicular Edge Computing Networks , 2019, IEEE Access.

[26]  Xinping Guan,et al.  A Contract-Stackelberg Offloading Incentive Mechanism for Vehicular Parked-Edge Computing Networks , 2019, 2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring).

[27]  Xin Liu,et al.  Adaptive Exploration-Exploitation Tradeoff for Opportunistic Bandits , 2017, ICML.

[28]  Xin Li,et al.  Vehicular Edge Cloud Computing: Depressurize the Intelligent Vehicles Onboard Computational Power , 2018, 2018 21st International Conference on Intelligent Transportation Systems (ITSC).

[29]  Shahid Mumtaz,et al.  Social Big-Data-Based Content Dissemination in Internet of Vehicles , 2018, IEEE Transactions on Industrial Informatics.

[30]  Jie Huang,et al.  A Computation Offloading Algorithm Based on Game Theory for Vehicular Edge Networks , 2018, 2018 IEEE International Conference on Communications (ICC).

[31]  Ke Zhang,et al.  Delay constrained offloading for Mobile Edge Computing in cloud-enabled vehicular networks , 2016, 2016 8th International Workshop on Resilient Networks Design and Modeling (RNDM).

[32]  Xiang Zhang,et al.  Opportunistic WiFi Offloading in Vehicular Environment: A Game-Theory Approach , 2016, IEEE Transactions on Intelligent Transportation Systems.

[33]  Zdenek Becvar,et al.  Mobile Edge Computing: A Survey on Architecture and Computation Offloading , 2017, IEEE Communications Surveys & Tutorials.

[34]  Ke Zhang,et al.  Mobile-Edge Computing for Vehicular Networks: A Promising Network Paradigm with Predictive Off-Loading , 2017, IEEE Veh. Technol. Mag..

[35]  Elisabeth Uhlemann Initial Steps Toward a Cellular Vehicle-to-Everything Standard [Connected Vehicles] , 2017, IEEE Vehicular Technology Magazine.

[36]  Huan Zhou,et al.  V2V Data Offloading for Cellular Network Based on the Software Defined Network (SDN) Inside Mobile Edge Computing (MEC) Architecture , 2018, IEEE Access.

[37]  Zhisheng Niu,et al.  Task Replication for Vehicular Edge Computing: A Combinatorial Multi-Armed Bandit Based Approach , 2018, 2018 IEEE Global Communications Conference (GLOBECOM).

[38]  Xiuhua Li,et al.  Data Offloading Techniques Through Vehicular Ad Hoc Networks: A Survey , 2018, IEEE Access.

[39]  Chung-Ming Huang,et al.  The Mobile Edge Computing (MEC)-Based VANET Data Offloading Using the Staying-Time-Oriented k-Hop Away Offloading Agent , 2019, 2019 International Conference on Information Networking (ICOIN).

[40]  Yue Wang,et al.  Cooperative Task Offloading in Three-Tier Mobile Computing Networks: An ADMM Framework , 2019, IEEE Transactions on Vehicular Technology.

[41]  Zhisheng Niu,et al.  Exploiting Moving Intelligence: Delay-Optimized Computation Offloading in Vehicular Fog Networks , 2019, IEEE Communications Magazine.

[42]  Longjiang Li,et al.  Compound Model of Task Arrivals and Load-Aware Offloading for Vehicular Mobile Edge Computing Networks , 2019, IEEE Access.

[43]  Sangheon Pack,et al.  Optimal Task Offloading and Resource Allocation in Software-Defined Vehicular Edge Computing , 2018, 2018 International Conference on Information and Communication Technology Convergence (ICTC).

[44]  Xuemin Shen,et al.  Reinforcement Learning Based Computation Migration for Vehicular Cloud Computing , 2018, 2018 IEEE Global Communications Conference (GLOBECOM).