A Novel Device Based Edge-Cloud Architecture for Vehicular Edge Computing
Lecture Notes in Electrical Engineering, ISSN: 1876-1119, Vol: 1274 LNEE, Page: 1144-1155
2025
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Conference Paper Description
The rapid advancement of vehicular technology and the proliferation of connected vehicles have given rise to the demand for efficient and responsive computing solutions within the vehicular environment. Vehicular Edge Computing (VEC) emerges as a promising paradigm to meet these demands by leveraging the computational resources at the network edge. This paper presents an in-depth exploration of Vehicular Edge Computing Architecture (VECA), a novel framework designed to enhance the capabilities of connected vehicles through edge computing. VECA integrates edge computing nodes, vehicle-to-everything (V2X) communication technologies, and intelligent algorithms to create a dynamic and distributed computing environment within the vehicular network. This architecture addresses critical challenges related to latency, bandwidth, and scalability, enabling a wide range of applications, including real-time navigation, autonomous driving, traffic management, and infotainment services. Key components of VECA include edge servers strategically placed at roadside infrastructure and within vehicles, a robust communication infrastructure that supports low-latency data exchange, and machine learning algorithms for predictive analytics and decision-making. The architecture fosters efficient resource allocation, load balancing, and secure data management, ensuring optimal utilization of computational resources while preserving data privacy. This paper provides a comprehensive overview of VECA’s architecture, highlighting its technical specifications, benefits, and potential use cases. This research paper also discusses the integration of the novel Device Based Edge-Cloud Architecture into existing vehicular networks, along with challenges and future research directions. Through the adoption of this new architecture, connected vehicles can harness the power of edge computing to enhance safety, efficiency, and user experience, ushering in a new era of intelligent and responsive vehicular systems.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85208169277&origin=inward; http://dx.doi.org/10.1007/978-981-97-8043-3_175; https://link.springer.com/10.1007/978-981-97-8043-3_175; https://dx.doi.org/10.1007/978-981-97-8043-3_175; https://link.springer.com/chapter/10.1007/978-981-97-8043-3_175
Springer Science and Business Media LLC
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