The reliability of data dissemination in vehicular ad hoc network (VANET) necessitates maximized cooperation between the vehicular nodes and the least degree of congestion. However, non‐line of sight (NLOS) nodes prevent the establishment and sustenance of connectivity between the vehicular nodes. In this paper, a hybrid seagull and thermal exchange optimization (TEO) algorithm‐based NLOS node detection technique is proposed for enhancing cooperative data dissemination in VANETs. It inherits three different versions of the proposed hybridized algorithm; three different approaches for localization of NLOS nodes depending upon its distance from the reference nodes are incorporated. It is considered as a reliable attempt in effective NLOS node localization as it is predominant in maintaining the balancing the degree of exploration and exploitation in the search process. In the first variant, the method of the roulette wheel is utilized for selecting one among the two optimization algorithm. In the second adoption, this hybridization algorithm combines TEO algorithm only after the iteration of SEOA algorithm. In the final adoption, the predominance of the seagull attack mode is enhanced by including the heat exchange formula of TEO algorithms for improving exploitation capability. The simulation experiments of the proposed HS‐TEO‐NLOS‐ND scheme conducted using EstiNet 8.1 exhibited its reliability in improving the emergency message delivery rate by 14.86%, a neighborhood awareness rate by 13%, and the channel utilization rate by 11.24%, compared to the benchmarked techniques under the evaluation done with different number of vehicular nodes and NLOS nodes in the network.

中文翻译：

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基于混合海鸥和热交换优化算法的NLOS节点检测技术可增强VAN​​ET数据分发下的可靠性

车载自组织网络（VANET）中数据分发的可靠性需要在车载节点之间实现最大程度的协作，并且拥塞程度最小。但是，非视线（NLOS）节点会阻止车辆节点之间的连接性的建立和维持。本文提出了一种基于混合海鸥和热交换优化（TEO）算法的NLOS节点检测技术，以增强VAN​​ET中的协作数据分发。它继承了所提出的混合算法的三个不同版本。结合了NLOS节点到参考节点的距离，三种不同的NLOS节点定位方法。它被认为是有效的NLOS节点定位的可靠尝试，因为它在保持搜索过程中探索和利用程度的平衡方面很重要。在第一种变型中，使用轮盘赌的方法从两个优化算法中选择一个。在第二种采用中，这种杂交算法仅在SEOA算法迭代之后才合并TEO算法。在最终采用中，通过包含TEO算法的热交换公式来提高开发能力，从而增强了海鸥攻击模式的优势。使用EstiNet 8.1进行的拟议的HS-TEO-NLOS-ND方案的仿真实验显示出其在将紧急消息传递率提高了14.86％，邻域感知率提高了13％，