A Taxonomy and Survey of Edge Cloud Computing for Intelligent Transportation Systems and Connected Vehicles

Abstract : Recent advances in smart connected vehicles and Intelligent Transportation Systems (ITS) are based upon the capture and processing of large amounts of sensor data. Modern vehicles contain many internal sensors to monitor a wide range of mechanical and electrical systems and the move to semi-autonomous vehicles adds outward looking sensors such as cameras, lidar, and radar. ITS is starting to connect existing sensors such as road cameras, traffic density sensors, traffic speed sensors, emergency vehicle, and public transport transponders. This disparate range of data is then processed to produce a fused situation awareness of the road network and used to provide real-time management, with much of the decision making automated. Road networks have quiet periods followed by peak traffic periods and cloud computing can provide a good solution for dealing with peaks by providing offloading of processing and scaling-up as required, but in some situations latency to traditional cloud data centres is too high or bandwidth is too constrained. Cloud computing at the edge of the network, close to the vehicle and ITS sensor, can provide a solution for latency and bandwidth constraints but the high mobility of vehicles and heterogeneity of infrastructure still needs to be addressed. This paper surveys the literature for cloud computing use with ITS and connected vehicles and provides taxonomies for that plus their use cases. We finish by identifying where further research is needed in order to enable vehicles and ITS to use edge cloud computing in a fully managed and automated way. We surveyed 496 papers covering a seven-year timespan with the first paper appearing in 2013 and ending at the conclusion of 2019.

 EXISTING SYSTEM :

 ? The work in gives a comprehensive overview of existing research developments in MEC along with advantages, architectures and applications. ? The existing research models in VEC, which are related to computation offloading, content caching, data management, flexible network management as well as security and privacy are summarized, respectively. ? Because of the self-interested characteristic, existing entities in the network are unwilling to contribute their available resources freely to others. ? In vehicular networks, especially urban vehicular environments, there exist many obstacles, e.g., trees, buildings, which may hinder the success of data transmission.

 DISADVANTAGE :

 ? This paper presents the current state of research in ITS and highlights security and privacy issues in current deployments. ? We examine ITS from a systemwide perspective and discuss long-term security and privacy issues that may arise as the field of ITS continues to grow. ? we provide a framework for classification of various security and privacy issues that exist currently in ITS, as well as those that may arise during the research and development of new ITS technologies. ? Understanding such complex dynamics and controlling emergent behaviors of ITS from a security standpoint is of paramount importance, since in such systems, local failures may give rise to cascades of failures, escalating the problem to the entire system.

 PROPOSED SYSTEM :

 • The work in targets the exploitation of ample computation resources on vehicles as well as the improvement of QoS by the proposed learning-based task replication scheme. • This proposed solution not only allows vehicles to select their preferable edge servers based on their requirements but also accounts for the mobility of vehicles. • In this proposed scheme, two metrics of Load Utilization Ratio (LUR) and Query to Connectivity Ratio (QCR) are designed to maintain the QoS. • A multicast data dissemination protocol is proposed in to reduce the energy consumption with the constraints of bandwidth and deadline.

 ADVANTAGE :

 ? Intelligent Transportation Systems (ITS) aim at integrating sensing, control, analysis, and communication technologies into travel infrastructure and transportation to improve mobility, comfort, safety, and efficiency. ? The ITS has the potential to create a more efficient, safer, and enjoyable experience for travelers all over the world. ? While these IoT devices are simple and serve their intended purpose in a very economical and efficient way, these devices struggle to implement basic security and privacy standards due to resource constraints. ? Managing these dynamic preferences in an efficient and transparent manner is critical to providing adaptive, resilient, and effective ITS solutions.