Review of Potential Methods for Handover Decision in V2V VANET

Vehicular ad hoc network (VANET) enables the vehicles to communicate each other. This technology could lead the future of transportation system by enabling the safety application, traffic management, and passenger entertainment. However, due to the fast moving nodes and very dynamic environment, VANET has some challenges waiting to be solved. One of the problems is related with vehicle to vehicle (V2V) handover decision. In this paper, the problem related to V2V handover decision is investigated. Furthermore, several potential methods to solve the problem are presented. The implementations of those methods in VANET are surveyed to assess the potential. Finally, the advantages and disadvantages of each method related to the implementation for V2V handover decision are presented in discussion.

[1]  Mohammad Ali Jabraeil Jamali,et al.  A hybrid geographic-DTN routing protocol based on fuzzy logic in vehicular ad hoc networks , 2019, Peer-to-Peer Netw. Appl..

[2]  Yusheng Ji,et al.  Decentralized Trust Evaluation in Vehicular Internet of Things , 2019, IEEE Access.

[3]  Francesco Chiti,et al.  Context aware clustering in VANETs: A game theoretic perspective , 2015, 2015 IEEE International Conference on Communications (ICC).

[4]  Abdul Hanan Abdullah,et al.  BRAIN-F: Beacon Rate Adaption Based on Fuzzy Logic in Vehicular Ad Hoc Network , 2016, International Journal of Fuzzy Systems.

[5]  Rajesh Kumar,et al.  Efficient routing in Vehicular Ad-hoc Networks using firefly optimization , 2016, 2016 International Conference on Inventive Computation Technologies (ICICT).

[6]  Yan Zhang,et al.  A Reinforcement Learning-Based Data Storage Scheme for Vehicular Ad Hoc Networks , 2017, IEEE Transactions on Vehicular Technology.

[7]  Sushanta Karmakar,et al.  A game theory based multi layered intrusion detection framework for VANET , 2018, Future Gener. Comput. Syst..

[8]  Hongbo Zhu,et al.  FMCNN: A Factorization Machine Combined Neural Network for Driving Safety Prediction in Vehicular Communication , 2019, IEEE Access.

[9]  Jing Li,et al.  Improving positioning accuracy of vehicular navigation system during GPS outages utilizing ensemble learning algorithm , 2017, Inf. Fusion.

[10]  Xiao Li,et al.  Reinforcement Learning Based Mobility Adaptive Routing for Vehicular Ad-Hoc Networks , 2018, Wirel. Pers. Commun..

[11]  Abdellah Idrissi,et al.  A multi-objective optimization system for mobile gateways selection in vehicular Ad-Hoc networks , 2019, Comput. Electr. Eng..

[12]  Mario Gerla,et al.  Platoon-Based Driving Protocol Based on Game Theory for Multimedia Transmission over VANET , 2017, GLOBECOM 2017 - 2017 IEEE Global Communications Conference.

[13]  Franco Blanchini,et al.  The joint network/control design of platooning algorithms can enforce guaranteed safety constraints , 2019, Ad Hoc Networks.

[14]  Jia Yuan Yu,et al.  A Reinforcement Learning Technique for Optimizing Downlink Scheduling in an Energy-Limited Vehicular Network , 2017, IEEE Transactions on Vehicular Technology.

[15]  Farhan Aadil,et al.  Implementation of evolutionary algorithms in vehicular ad-hoc network for cluster optimization , 2017, 2017 Intelligent Systems Conference (IntelliSys).

[16]  Nikhil Kapade.  TLC: Trust Point Load Balancing Method using Coalitional Game Theory for message forwarding in VANET , 2014, 2014 IEEE Global Conference on Wireless Computing & Networking (GCWCN).

[17]  Mohamed Hamdi,et al.  A new security games based reaction algorithm against DOS attacks in VANETs , 2016, 2016 13th IEEE Annual Consumer Communications & Networking Conference (CCNC).

[18]  Selo Sulistyo,et al.  Distributed Channel and Power Level Selection in VANET Based on SINR using Game Model , 2017, Int. J. Commun. Networks Inf. Secur..

[19]  Seungmin Rho,et al.  A Novel White Space Optimization Scheme Using Memory Enabled Genetic Algorithm in Cognitive Vehicular Communication , 2017, Wirel. Pers. Commun..

[20]  Arun Prakash,et al.  Medium access control protocols for safety applications in Vehicular Ad-Hoc Network: A classification and comprehensive survey , 2015, Veh. Commun..

[21]  Jan Wantoro,et al.  M-AODV+: An extension of AODV+ routing protocol for supporting vehicle-to-vehicle communication in vehicular ad hoc networks , 2014, 2014 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT).

[22]  Imad Mahgoub,et al.  Fuzzy Logic-Based Broadcast in Vehicular Ad Hoc Networks , 2016, 2016 IEEE 84th Vehicular Technology Conference (VTC-Fall).

[23]  Naixue Xiong,et al.  A Game Theory Algorithm for Intra-Cluster Data Aggregation in a Vehicular Ad Hoc Network , 2016, Sensors.

[24]  Vahid Sattari-Naeini,et al.  Application of fuzzy logic for selecting the route in AODV routing protocol for vehicular ad hoc networks , 2015, 2015 23rd Iranian Conference on Electrical Engineering.

[25]  Selo Sulistyo,et al.  Performance study and optimization of multi-channel allocation in VANET under physical channel model , 2019, Wirel. Networks.

[26]  Santanu Phadikar,et al.  Multi-objective optimization technique for resource allocation and task scheduling in vehicular cloud architecture: A hybrid adaptive nature inspired approach , 2018, J. Netw. Comput. Appl..

[27]  Abdul Hanan Abdullah,et al.  A Secure Trust Model Based on Fuzzy Logic in Vehicular Ad Hoc Networks With Fog Computing , 2017, IEEE Access.

[28]  Eylem Ekici,et al.  Vehicular Networking: A Survey and Tutorial on Requirements, Architectures, Challenges, Standards and Solutions , 2011, IEEE Communications Surveys & Tutorials.

[29]  Hang Su,et al.  Clustering-Based Multichannel MAC Protocols for QoS Provisionings Over Vehicular Ad Hoc Networks , 2007, IEEE Transactions on Vehicular Technology.

[30]  Bin Ma,et al.  Speed-adaptive vertical handoff algorithm based on fuzzy logic in vehicular heterogeneous networks , 2012, 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery.

[31]  Zhu Qi,et al.  Game-based TDMA MAC protocol for vehicular network , 2017, Journal of Communications and Networks.

[32]  Sungwook Kim,et al.  QoS Sensitive VANET Control Scheme based on Feedback Game Model , 2015, KSII Trans. Internet Inf. Syst..

[33]  Selo Sulistyo,et al.  SINR and throughput improvement for VANET using fuzzy power control , 2018, Int. J. Commun. Syst..

[34]  Nikolaos D. Tselikas,et al.  A handoff algorithm for packet loss optimization in vehicular radio-over-fiber picocellular networks , 2014, 2014 International Conference on Connected Vehicles and Expo (ICCVE).

[35]  Manoj M. Dongre,et al.  Fuzzy logic based data dissemination in Vehicular Ad Hoc Networks , 2017, 2017 International conference of Electronics, Communication and Aerospace Technology (ICECA).

[36]  Xu Sun,et al.  A Security Aware Fuzzy Enhanced Reliable Ant Colony Optimization Routing in Vehicular Ad hoc Networks , 2018, 2018 IEEE Intelligent Vehicles Symposium (IV).

[37]  Xinyu Mao,et al.  An Unsupervised-Learning-Based Method for Multi-Hop Wireless Broadcast Relay Selection in Urban Vehicular Networks , 2017, 2017 IEEE 85th Vehicular Technology Conference (VTC Spring).

[38]  Jie Han,et al.  A social-aware routing protocol based on fuzzy logic in vehicular ad hoc networks , 2014, 2014 International Workshop on High Mobility Wireless Communications.

[39]  Samuel Pierre,et al.  Centralized and Localized Data Congestion Control Strategy for Vehicular Ad Hoc Networks Using a Machine Learning Clustering Algorithm , 2016, IEEE Transactions on Intelligent Transportation Systems.

[40]  Mario Gerla,et al.  A Game Theory Approach for Platoon-Based Driving for Multimedia Transmission in VANETs , 2018, Wirel. Commun. Mob. Comput..

[41]  Hyuk Lim,et al.  Prefetching-Based Data Dissemination in Vehicular Cloud Systems , 2016, IEEE Transactions on Vehicular Technology.

[42]  Sidi-Mohammed Senouci,et al.  A fuzzy logic-based communication medium selection for QoS preservation in vehicular networks , 2016, ICC.

[43]  Marjan Kuchaki Rafsanjani,et al.  F-Ant: an effective routing protocol for ant colony optimization based on fuzzy logic in vehicular ad hoc networks , 2018, Neural Computing and Applications.

[44]  Hussein Zedan,et al.  A comprehensive survey on vehicular Ad Hoc network , 2014, J. Netw. Comput. Appl..

[45]  Feng Wei,et al.  Improving security and stability of ad hoc on-demand distance vector with fuzzy neural network in vehicular ad hoc network , 2018, Int. J. Distributed Sens. Networks.

[46]  Mianxiong Dong,et al.  RSU placement optimization in vehicular participatory sensing networks , 2014, 2014 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[47]  Zheyi Chen,et al.  A Game Theory Based Approach for Power Efficient Vehicular Ad Hoc Networks , 2017, Wirel. Commun. Mob. Comput..

[48]  Osman Ghazali,et al.  Fuzzy Logic-based Intelligent Scheme for Enhancing QoS of Vertical Handover Decision in Vehicular Ad-hoc Networks , 2017 .

[49]  Shabnam Sharma,et al.  Nature inspired route optimization in vehicular adhoc network , 2016, 2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO).

[50]  Ahmad Mostafa,et al.  Connecting the Autonomous: A Distributed Game Theory Approach for VANET Connectivity , 2017, 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall).

[51]  Hongbo Zhu,et al.  Resource Management in Vehicular Ad Hoc Networks: Multi-parameter Fuzzy Optimization Scheme , 2017, IIKI.