A Hybrid-Fuzzy Logic Guided Genetic Algorithm (H-FLGA) Approach for Resource Optimization in 5G VANETs

To support diversified quality of service demands and dynamic resource requirements of users in 5G driven VANETs, network resources need flexible and scalable resource allocation strategies. Current heterogeneous vehicular networks are designed and deployed with a connection-centric mindset with fixed resource allocation to a cell regardless of traffic conditions, static coverage, and capacity. In this paper, we propose a hybrid-fuzzy logic guided genetic algorithm (H-FLGA) approach for the software defined networking controller, to solve a multi-objective resource optimization problem for 5G driven VANETs. Realizing the service oriented view, the proposed approach formulates five different scenarios of network resource optimization in 5G VANETs. Furthermore, the proposed fuzzy inference system is used to optimize weights of multi-objectives, depending on the type of service requirements of customers. The proposed approach shows the minimized value of multi-objective cost function when compared with the GA. The simulation results show the minimized value of end-to-end delay as compared to other schemes. The proposed approach will help the network service providers to implement a customer-centric network infrastructure, depending on dynamic customer needs of users.

[1]  Yusheng Ji,et al.  Joint MAC and Network Layer Control for VANET Broadcast Communications Considering End-to-End Latency , 2014, 2014 IEEE 28th International Conference on Advanced Information Networking and Applications.

[2]  Celimuge Wu,et al.  Flexible, Portable, and Practicable Solution for Routing in VANETs: A Fuzzy Constraint Q-Learning Approach , 2013, IEEE Transactions on Vehicular Technology.

[3]  Lin Zhang,et al.  Analyzing and relieving the impact of FCD traffic in LTE-VANET heterogeneous network , 2014, 2014 21st International Conference on Telecommunications (ICT).

[4]  Dusit Niyato,et al.  Applications, Architectures, and Protocol Design Issues for Mobile Social Networks: A Survey , 2011, Proceedings of the IEEE.

[5]  Dario Sabella,et al.  Mobile-Edge Computing Architecture: The role of MEC in the Internet of Things , 2016, IEEE Consumer Electronics Magazine.

[6]  Yonggang Wen,et al.  Cloud radio access network (C-RAN): a primer , 2015, IEEE Network.

[7]  Salah Eddine El Ayoubi,et al.  5G innovations for new business opportunities , 2017 .

[8]  Mianxiong Dong,et al.  Radio Access Network Virtualization for the Social Internet of Things , 2015, IEEE Cloud Computing.

[9]  Zaher Dawy,et al.  Traffic Offloading With Channel Allocation in Cache-Enabled Ultra-Dense Wireless Networks , 2018, IEEE Transactions on Vehicular Technology.

[10]  Jeffrey G. Andrews,et al.  What Will 5G Be? , 2014, IEEE Journal on Selected Areas in Communications.

[11]  Ning Lu,et al.  Soft-defined heterogeneous vehicular network: architecture and challenges , 2015, IEEE Network.

[12]  Fei Teng.  Resource Management in Next Generation Wireless Networks: Optimization and Games , 2016 .

[13]  Zhigang Cao,et al.  A utility-based network selection scheme for multiple services in heterogeneous networks , 2005, 2005 International Conference on Wireless Networks, Communications and Mobile Computing.

[14]  Wei Ni,et al.  5G next generation VANETs using SDN and fog computing framework , 2018, 2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC).

[15]  H. S. Al-Raweshidy,et al.  Quality of Service aware dynamic BBU-RRH mapping in Cloud Radio Access Network , 2015, 2015 International Conference on Emerging Technologies (ICET).

[16]  Qi Shi,et al.  Secure and Privacy-Aware Cloud-Assisted Video Reporting Service in 5G-Enabled Vehicular Networks , 2016, IEEE Transactions on Vehicular Technology.

[17]  Wei Ni,et al.  An Evolutionary Game Theoretic Approach for Stable and Optimized Clustering in VANETs , 2018, IEEE Transactions on Vehicular Technology.

[18]  Abdulmotaleb El-Saddik,et al.  Toward Social Internet of Vehicles: Concept, Architecture, and Applications , 2015, IEEE Access.

[19]  Daqiang Zhang,et al.  Cost-Efficient Heterogeneous Data Transmission in Software Defined Vehicular Networks , 2015, 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security, and 2015 IEEE 12th International Conference on Embedded Software and Systems.

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

[21]  Ilenia Tinnirello,et al.  A flexible and reconfigurable 5G networking architecture based on context and content information , 2017, 2017 European Conference on Networks and Communications (EuCNC).

[22]  Gang Feng,et al.  Resource Allocation in Software Defined Wireless Networks , 2017, IEEE Network.

[23]  Lajos Hanzo,et al.  User-Centric C-RAN Architecture for Ultra-Dense 5G Networks: Challenges and Methodologies , 2017, IEEE Communications Magazine.

[24]  Liviu Iftode,et al.  RoadSpeak: enabling voice chat on roadways using vehicular social networks , 2008, SocialNets '08.

[25]  Sungwook Kim.  News-vendor game-based resource allocation scheme for next-generation C-RAN systems , 2016, EURASIP J. Wirel. Commun. Netw..

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

[27]  Hassan Artail,et al.  Managing Social Networks in vehicular networks using trust rules , 2011, 2011 IEEE Symposium on Wireless Technology and Applications (ISWTA).

[28]  Oriol Sallent,et al.  Resource Auctioning Mechanisms in Heterogeneous Wireless Access Networks , 2006, 2006 IEEE 63rd Vehicular Technology Conference.

[29]  Branka Vucetic,et al.  Baseband Processing Units Virtualization for Cloud Radio Access Networks , 2015, IEEE Wireless Communications Letters.

[30]  Jie Zhang,et al.  Mobile-Edge Computation Offloading for Ultradense IoT Networks , 2018, IEEE Internet of Things Journal.

[31]  Derrick Wing Kwan Ng,et al.  Key technologies for 5G wireless systems , 2017 .

[32]  K. Dhanalakshmi.  A Fuzzy Multi-metric QoS-balancing Gateway Selection Algorithm in a Clustered VANET to LTE Advanced Hybrid Cellular Network , 2016 .

[33]  Enzo Baccarelli,et al.  Reliable Adaptive Resource Management for Cognitive Cloud Vehicular Networks , 2015, IEEE Transactions on Vehicular Technology.

[34]  Jiajia Liu,et al.  Collaborative Computation Offloading for Multiaccess Edge Computing Over Fiber–Wireless Networks , 2018, IEEE Transactions on Vehicular Technology.

[35]  Zhang Ning,et al.  Software defined Internet of vehicles: architecture, challenges and solutions , 2016 .

[36]  Jie Zhang,et al.  Computation Offloading for Multi-Access Mobile Edge Computing in Ultra-Dense Networks , 2018, IEEE Communications Magazine.

[37]  Antonios Argyriou,et al.  Video Delivery in Dense 5G Cellular Networks , 2017, IEEE Network.

[38]  Wenhui Zhang.  Bearer service allocation and pricing in heterogeneous wireless networks , 2005, IEEE International Conference on Communications, 2005. ICC 2005. 2005.