{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T15:37:36Z","timestamp":1772465856855,"version":"3.50.1"},"reference-count":25,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JSAN"],"abstract":"<jats:p>Vehicle networking is a new paradigm in wireless technology that facilitates communication between vehicles in close proximity and in-vehicle internet access. This technology paves the way for a variety of safety, convenience and entertainment applications, including safety message exchange, real-time traffic information sharing and public internet access. The overall goal of vehicular networks is to create an efficient, safe and convenient environment for vehicles on the road. This paper presents a Sensitive Node Election (SNE) algorithm adapted to routing protocols in certain opportunistic network environments. The algorithm focuses on selecting the best agent for communication using an innovative approach for message forwarding. Quality of Service (QoS) metrics targeted for optimization include network end-to-end throughput and packet delivery, with the aim of improving the overall performance of the network. Our algorithm includes a stochastic rebroadcasting scheme that takes into account parameters, such as vehicle density, distance between vehicles and transmission distance, and adapts to various network conditions. Furthermore, the SNE algorithm uses a metric based on transmission distance and can dynamically adapt to application requirements, such as prioritization. It provides high throughput and minimizes delay. The results demonstrate the effectiveness of this approach in improving QoS in various vehicular ad hoc network (VANET) simulations and influencing the neural network ensemble (NNE Algorithm).<\/jats:p>","DOI":"10.3390\/jsan15020025","type":"journal-article","created":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T14:06:56Z","timestamp":1772460416000},"page":"25","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Vehicle Communications: Sensitive Node Election SNE Algorithm Achieves Optimized QoS"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2125-0343","authenticated-orcid":false,"given":"Ayoob","family":"Ayoob","sequence":"first","affiliation":[{"name":"Faculty of Computing, University of Malaysia Pahang Al-Sultan Abdullah, Pekan 26600, Malaysia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7388-4340","authenticated-orcid":false,"given":"Mohd Faizal Ab","family":"Razak","sequence":"additional","affiliation":[{"name":"Faculty of Computing, University of Malaysia Pahang Al-Sultan Abdullah, Pekan 26600, Malaysia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9951-8285","authenticated-orcid":false,"given":"Ghaith","family":"Khalil","sequence":"additional","affiliation":[{"name":"Faculty of Engineering and Information Technology, University of Melbourne, Parkville, VIC 3010, Australia"}]},{"given":"Muammer","family":"Aksoy","sequence":"additional","affiliation":[{"name":"Cyber Security Information & Telecommunication Public Company (ITPC), Iraqi Ministry of Communications, Baghdad 10001, Iraq"}]}],"member":"1968","published-online":{"date-parts":[[2026,3,1]]},"reference":[{"key":"ref_1","unstructured":"Chowdhury, M.A., and Sadek, A.W. 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