Optimized communication in 5G-driven vehicular ad-hoc networks (VANETs)

University of Technology Sydney. Faculty of Engineering and Information Technology.Next generation Vehicular Ad-hoc Networks will be dominated by heterogeneous data and additional massive diffusion of Internet of Things (IoT) traffic. To meet these objectives, a radical rethink of current VANET architecture is essentially required by turning it into a more flexible and programmable fabric. This research endeavours to provide next generation 5G-driven VANET architecture, with solutions for efficient and optimized communication. This thesis first introduces an innovative 5G-driven VANET architecture to provide flexible network management, control and high resource utilization, leveraging the concepts of SDN, C-RAN and Fog Computing. A new Fog Computing (FC) framework (comprising of zones and clusters) is proposed at the edge of the network to support vehicles and end users with prompt responses, and to avoid frequent handovers between vehicles and RSUs. The key results are improved throughput, reduced transmission delay and minimized control overhead on the controller. Furthermore, a novel Evolutionary Game Theoretic (EGT) framework is presented to achieve stable and optimized clustering in the Fog Computing Framework. The solution of the game is presented to be an evolutionary equilibrium. The equilibrium point is also proven analytically and the existence of an evolutionary equilibrium is also verified using the Lyapunov function. The results are analysed for different number of clusters for different populations and speeds. An optimal cost is suggested that defines an optimum clustering thus reducing an overhead of frequent cluster reformation. In addition, this thesis provides a Hybrid-Fuzzy Logic guided Genetic Algorithm (H-FLGA) approach for the SDN controller, to support diversified quality of service (QoS) demands and dynamic resource requirements of mobile users in 5G-driven VANET architecture. The proposed Fuzzy Inference System (FIS) is used to optimize weights of multi-objectives, depending on the Type of Service (ToS) requirements of customers. The results proved that the proposed hybrid H-FLGA performs better than GA. The results improve spectral efficiency and optimizes connections while minimizing E2E delay and further facilitates the service providers to implement a more flexible customer-centric network infrastructure. Furthermore, an end-to-end (E2E) network slicing framework is proposed to support customized services by managing the cooperation of both the RAN and Core Network (CN), using SDN, NFV and Edge Computing technologies. A dynamic radio resource slice optimization scheme is proposed to slice the overall bandwidth resources for mission critical and non-mission critical demands. The results meet ultra reliability and E2E latency of mission-critical services

Optimization of vehicular networks in smart cities: from agile optimization to learnheuristics and simheuristics

Vehicular ad hoc networks (VANETs) are a fundamental component of intelligent transportation systems in smart cities. With the support of open and real-time data, these networks of inter-connected vehicles constitute an ‘Internet of vehicles’ with the potential to significantly enhance citizens’ mobility and last-mile delivery in urban, peri-urban, and metropolitan areas. However, the proper coordination and logistics of VANETs raise a number of optimization challenges that need to be solved. After reviewing the state of the art on the concepts of VANET optimization and open data in smart cities, this paper discusses some of the most relevant optimization challenges in this area. Since most of the optimization problems are related to the need for real-time solutions or to the consideration of uncertainty and dynamic environments, the paper also discusses how some VANET challenges can be addressed with the use of agile optimization algorithms and the combination of metaheuristics with simulation and machine learning methods. The paper also offers a numerical analysis that measures the impact of using these optimization techniques in some related problems. Our numerical analysis, based on real data from Open Data Barcelona, demonstrates that the constructive heuristic outperforms the random scenario in the CDP combined with vehicular networks, resulting in maximizing the minimum distance between facilities while meeting capacity requirements with the fewest facilities.Peer ReviewedPostprint (published version

Service Provisioning in Edge-Cloud Continuum Emerging Applications for Mobile Devices

Disruptive applications for mobile devices can be enhanced by Edge computing facilities. In this context, Edge Computing (EC) is a proposed architecture to meet the mobility requirements imposed by these applications in a wide range of domains, such as the Internet of Things, Immersive Media, and Connected and Autonomous Vehicles. EC architecture aims to introduce computing capabilities in the path between the user and the Cloud to execute tasks closer to where they are consumed, thus mitigating issues related to latency, context awareness, and mobility support. In this survey, we describe which are the leading technologies to support the deployment of EC infrastructure. Thereafter, we discuss the applications that can take advantage of EC and how they were proposed in the literature. Finally, after examining enabling technologies and related applications, we identify some open challenges to fully achieve the potential of EC, and also research opportunities on upcoming paradigms for service provisioning. This survey is a guide to comprehend the recent advances on the provisioning of mobile applications, as well as foresee the expected next stages of evolution for these applications

Clustering and 5G-enabled smart cities: a survey of clustering schemes in VANETs

This chapter highlights the importance of Vehicular Ad-hoc Networks (VANETs) in the context of the 5Genabled smarter cities and roads, a topic that attracts significant interest. In order for VANETs and its associated applications to become a reality, a very promising avenue is to bring together multiple wireless technologies in the architectural design. 5G is envisioned to have a heterogeneous network architecture. Clustering is employed in designing optimal VANET architectures that successfully use different technologies, therefore clustering has the potential to play an important role in the 5G-VANET enabled solutions. This chapter presents a survey of clustering approaches in the VANET research area. The survey provides a general classification of the clustering algorithms, presents some of the most advanced and latest algorithms in VANETs, and it is among the fewest works in the literature that reviews the performance assessment of clustering algorithms

Advancement in infotainment system in automotive sector with vehicular cloud network and current state of art

The automotive industry has been incorporating various technological advancement on top-end versions of the vehicle order to improvise the degree of comfortability as well as enhancing the safer driving system. Infotainment system is one such pivotal system which not only makes the vehicle smart but also offers abundance of information as well as entertainment to the driver and passenger. The capability to offer extensive relay of service through infotainment system is highly dependent on vehicular adhoc network as well as back end support of cloud environment. However, it is know that such legacy system of vehicular adhoc network is also characterized by various problems associated with channel capacity, latency, heterogeneous network processing, and many more. Therefore, this paper offers a comprehensive insight to the research work being carried out towards leveraging the infotainment system in order to obtain the true picture of strength, limitation, and open end problems associated with infotainment system

Off-Street Vehicular Fog for Catering Applications in 5G/B5G: A Trust-based Task Mapping Solution and Open Research Issues

One of the key enablers in serving the applications requiring stringent latency in 5G networks is fog computing as it is situated closer to the end users. With the technological advancement of vehicles’ on-board units, their computing capabilities are becoming robust, and considering the underutilization of the off-street vehicles, we envision that the off-street vehicles can be an enormously useful computational source for the fog computing. Additionally, clustering the vehicles would be advantageous in order to improve the service availability. As the vehicles become highly connected, trust is needed especially in distributed environments. However, vehicles are made from different manufacturers, and have different platforms, security mechanisms, and varying parking duration. These lead to the unpredictable behavior of the vehicles where quantifying trust value of vehicles would be difficult. A trust-based solution is necessary for task mapping as a task has a set of properties including expected time to complete, and trust requirements that need to be met. However, the existing metrics used for trust evaluation in the vehicular fog computing such as velocity and direction are not applicable in the off-street vehicle fog environments. In this paper, we propose a framework for quantifying the trust value of off-street vehicle fog computing facilities in 5G networks and forming logical clusters of vehicles based on the trust values. This allows tasks to be shared with multiple vehicles in the same cluster that meets the tasks’ trust requirements. Further, we propose a novel task mapping algorithm to increase the vehicle resource utilization and meet the desired trust requirements while maintaining imposed latency requirements of 5G applications. Results obtained using iFogSim simulator demonstrate that the proposed solution increases vehicle resource utilization and reduces task drop noticeably. This paper presents open research issues pertaining to the study to lead..