JOURNAL ARTICLE

Developed Internet of Vehicles Architecture: Communication, Big Data and Route Determination Perspectives.

  • Published In: Journal of Circuits, Systems & Computers, 2025, v. 34, n. 3. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Alblehai, Fahad; Said, Omar 3 of 3

Abstract

Internet of vehicles (IoV) has become an important research topic due to its direct effect on intelligent transportation systems (ITS) development. There are many challenges in the IoV environment, such as communication, big data and best route assigning. In this paper, an effective IoV architecture is proposed. This architecture has four main objectives. The first objective is to utilize a powerful communication scheme in which three tiers of coverage tools — Internet, satellite, high-altitude platform (HAP) — are utilized. Therefore, the vehicles maintain a continuous connection to the IoV environment everywhere. The second objective is to apply filtering and prioritization mechanisms to reduce the detrimental effects of IoV big data. The third objective is to assign the best route for a vehicle after determining its real-time priority. The fourth objective is to analyze the IoV data. The proposed architecture performance is measured using a simulation environment that is created by the NS-3 package. The simulation results proved that the proposed IoV architecture has a positive impact on the IoV environment according to the performance metrics: energy, success rate of route assignment, filtering effect, data loss, delay, usage of coverage tools and throughput. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Circuits, Systems & Computers. 2025/02, Vol. 34, Issue 3, p1
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2025
  • ISSN:0218-1266
  • DOI:10.1142/S0218126625500781
  • Accession Number:183762428
  • Copyright Statement:Copyright of Journal of Circuits, Systems & Computers is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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