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Yushan Li and Satoshi Fujita
This paper proposes a novel event-driven architecture for enhancing edge-based vehicular systems within smart transportation. Leveraging the inherent real-time, scalable, and fault-tolerant nature of the Elixir language, we present an innovative architec...
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Qi Deng and Feng Zeng
In big cities, there are more and more parking lots and charging piles for electric vehicles, and the resources of parking and charging vehicles can be aggregated to provide strong computing power for vehicular edge computing (VEC). In this paper, we pro...
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Ali Pashazadeh, Giovanni Nardini and Giovanni Stea
In recent years, the need for computation-intensive applications in mobile networks requiring more storage, powerful processors, and real-time responses has risen substantially. Vehicular networks play an important role in this ecosystem, as they must su...
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Hongli Zhang and Ying Li
Computation-intensive vehicle tasks sharply increase with the rapid growth of intelligent vehicles. The technology of Mobile Edge Computing (MEC) has the possibility of assisting vehicles with computation offloading. To solve the problem of computation r...
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Prachi V. Wadatkar, Rosario G. Garroppo and Gianfranco Nencioni
Fifth-generation (5G) mobile networks fulfill the demands of critical applications, such as Ultra-Reliable Low-Latency Communication (URLLC), particularly in the automotive industry. Vehicular communication requires low latency and high computational cap...
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Yousef-Awwad Daraghmi, Mamoun Abu Helou, Eman-Yasser Daraghmi and Waheeb Abu-ulbeh
The violation traffic laws by driving at high speeds, the overloading of passengers, and the unfastening of seatbelts are of high risk and can be fatal in the event of any accident. Several systems have been proposed to improve passenger safety, and the ...
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Tianyu Bai, Song Fu and Qing Yang
With the wider adoption of edge computing services, intelligent edge devices, and high-speed V2X communication, compute-intensive tasks for autonomous vehicles, such as object detection using camera, LiDAR, and/or radar data, can be partially offloaded t...
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Xianhao Shen, Zhaozhan Chang, Xiaolan Xie and Shaohua Niu
To reduce computing delay and energy consumption in the Vehicular networks, the total cost of task offloading, namely delay and energy consumption, is studied. A task offloading model combining local vehicle computing, MEC (Mobile Edge Computing) server ...
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Salahadin Seid Musa, Marco Zennaro, Mulugeta Libsie and Ermanno Pietrosemoli
Recently the Internet of Vehicles (IoV) has become a promising research area in the field of the Internet of Things (IoT), which enables vehicles to communicate and exchange real-time information with each other, as well as with infrastructure, people, a...
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Muhammad Firdaus and Kyung-Hyune Rhee
The conventional architecture of vehicular ad hoc networks (VANETs) with a centralized approach has difficulty overcoming the increasing complexity of intelligent transportation system (ITS) applications as well as challenges in providing large amounts o...
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