A new networking paradigm, Vehicular Edge Computing (VEC), has been introduced in recent years to the vehicular network to augment its computing capacity. The ultimate challenge to fulfill the requirements of both communication and computation is increasingly prominent, with the advent of ever-growing modern vehicular applications. With the breakthrough of VEC, service providers directly host services in close proximity to smart vehicles for reducing latency and improving quality of service (QoS). This paper illustrates the VEC architecture, coupled with the concept of the smart vehicle, its services, communication, and applications. Moreover, we categorized all the technical issues in the VEC architecture and reviewed all the relevant and latest solutions. We also shed some light and pinpoint future research challenges. This article not only enables naive readers to get a better understanding of this latest research field but also gives new directions in the field of VEC to the other researchers.

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A Survey on Vehicular Edge Computing: Architecture, Applications, Technical Issues, and Future Directions

A survey on context-aware vehicular network applications

It is difficult enough for drivers to handle distractions when they are in a familiar environment, but what happens when drivers are placed in a new environment? We explore drivers' behaviour when they encounter road signs from three countries. We conducted two eye-tracking studies with 50 participants. Participants spent increased time looking at unfamiliar road signs. Misinterpretation occurred due to the influence of previous experience and many drivers drove at reduced speeds throughout to compensate for the anticipated cognitive load.

An Eye-tracking Evaluation of Driver Distraction and Unfamiliar Road Signs

Wireless sensor networks are widely deployed and implicitly characterized by stringent energy and computation constraints. Sensor nodes are vulnerable to false positive and false negative attacks that inject false data through compromised nodes. Such attacks cause false alarms with energy drain and information loss. Although several en-route filtering schemes have been designed to detect the attacks, they focus on saving energy through early filtering or continuous delivery of data in accordance with verification records; they cannot exclude compromised nodes. In this paper, we propose a scheme that effectively identifies the compromised nodes and copes with new attacks using a context-aware architecture. In addition, the proposed scheme improves the security strength and energy efficiency of the network. Simulation results validate that the proposed scheme provides energy savings of up to 45 percent and allows fewer attack successes than the existing scheme.

Context-Aware Architecture for Probabilistic Voting-based Filtering Scheme in Sensor Networks

The vehicle-to-infrastructure (V2I) communication system allows the exchange of information between vehicles and road infrastructures. It aims to avoid or reduce vehicular accidents, increase mobility, and provide other road safety benefits. This paper aimed to review and analyze the literature on data exchanges in the V2I communication system. The factors considered to improve the understanding of various contextual aspects and the characteristics of the field were motivations, open challenges, and recommendations from other researchers. We systematically searched all articles on data exchanges in the V2I communication system from the three main databases, namely ScienceDirect, Web of Science, and IEEE Xplore, from 2008 to 2018. These indices were sufficiently extensive to encompass our field of literature. A total of 70 articles were selected based on our inclusion and exclusion criteria. Most studies (42/70) covered a developed V2I communication system, while numerous articles (22/70) focused on general research on the V2I communication system. The smallest portion of articles (6/70) comprised reviews and surveys. The V2I system plays a key role in vehicular ad hoc networks but is less implemented than vehicle-to-vehicle communication owing to its deployment costs and maintenance requirements. However, numerous studies have been conducted on the V2I communication system to promote its utility. Research areas on V2I communication classification vary but are all equally vital. We expect this systematic review to help emphasize current research opportunities and thus extend and create additional research fields.

Mapping and Deep Analysis of Vehicle-to-Infrastructure Communication Systems: Coherent Taxonomy, Datasets, Evaluation and Performance Measurements, Motivations, Open Challenges, Recommendations, and Methodological Aspects

Context-Aware Driver Assistance System

Recently, significant improvements have been made in the area of vehicular communication systems. Furthermore, vehicle-to-vehicle communication is considered a key concept for keeping roads safe. An efficient implementation of these systems is necessary to ensure the safety of driving situations and to reduce the collision rates. This paper proposes a Context-Aware Driver Assistance System that links drivers with the physical environment surrounding them using multiple types of sensors and traffic systems as well as considering the senior driver's difficulties and the system processing time. This is achieved by developing a warning system that assists drivers to avoid collisions and improve their response times. The proposed system architecture consists of a set of components to process the user's request such as parking assistance, and to provide responses and advices when needed. These components include communication, knowledge exchange, knowledge update, and context-history. Also, it includes other processes such as context-history manipulation, hazard detection, and hazard detection control. The main goal of the proposed system is to reduce the number of car accidents and improve driver's decisions. The NXT Robotic environment is used to demonstrate the feasibility of the proposed system.

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Integrated context-aware driver assistance system architecture

The extreme workloads on the fog layer caused a misalignment in some fog nodes that affect its efficiency and degenerate fog technology’s primary goal. Therefore, creating a balanced computing environment via the offloading process is the key. However, there are many obstacles to balance computing nodes in the fog environment, such as offloading strategy and its consequences due to the extreme offloading processes, and when need to offload and where. These obstacles are vital concerns among researchers. Thus, several studies have been conducted to enhance the fog system performance to increase the entire system’s throughput. This paper explores the recent articles to determine the possible research gaps and opportunities to implement an efficient solution for load balancing in fog environments after analyzing and assessing the existing solutions. While most of the proposed solutions involve short-term solution, this literature review reveals the need to find out a sustainable resolution for load balancing to avoid listed obstacles by using the offloading technique with maintaining the bandwidth of the network.

Wael Alghamdi

Papers

Context-Aware Driver Assistance System

Integrated context-aware driver assistance system architecture

Sustainability of Load Balancing Techniques in Fog Computing Environment: Review.

Improving Driver's Behavior Using Context-Aware Systems