Presently, smart city is designed to enhance the quality of life in city, fulfil the safety of the people, safe travelling, etc. Besides, big data has attracted significant attention among researchers in different fields as a large amount of data is being produced with diverse day-to-day applications. Besides, Vehicular adhoc network (VANET) is a kind of mobile adhoc network (MANET) that considers the vehicles as the nodes in a network. Since the VANET generates large amount of data, big data analytics can be used to gain meaningful understanding for improving the traffic management process such as planning, engineering, and operations. This paper designs a Big Data Analytics with Oppositional Moth Flame Optimization based Vehicular Routing Protocol for Future Smart Cities. The presented model maps the features of VANET with the attributes of the big data. In addition, oppositional moth flame optimization based vehicular routing (OMFOVR) technique is developed for VANET over the Hadoop Map Reduce standalone distributed framework. For validating the effectual performance of the proposed OMFOVR technique, a series of experiments were performed and the results are compared with the conventional NetBeans IDE platform. The experimental values showcased the betterment of the OMFOVR technique on the selection of routes over the compared methods.

中文翻译：

---

基于对立蛾火焰优化的未来智慧城市车辆路由协议的大数据分析

目前，智慧城市旨在提高城市生活质量，实现人们的安全，安全出行等。此外，随着大量数据的产生，大数据引起了不同领域的研究人员的广泛关注。各种日常应用。此外，车载自组织网络（VANET）是一种将车辆视为网络中节点的移动自组织网络（MANET）。由于 VANET 产生大量数据，大数据分析可用于获得有意义的理解，以改进交通管理流程，如规划、工程和运营。本文设计了一种基于对立飞蛾火焰优化的未来智能城市车辆路由协议的大数据分析。所提出的模型将 VANET 的特征与大数据的属性映射起来。此外，在 Hadoop Map Reduce 独立分布式框架上为 VANET 开发了基于对立飞蛾火焰优化的车辆路由 (OMFOVR) 技术。为了验证所提出的 OMFOVR 技术的有效性能，进行了一系列实验，并将结果与​​传统的 NetBeans IDE 平台进行了比较。实验值展示了 OMFOVR 技术在路线选择方面优于比较方法。进行了一系列实验，并将结果与​​传统的 NetBeans IDE 平台进行了比较。实验值展示了 OMFOVR 技术在路线选择方面优于比较方法。进行了一系列实验，并将结果与​​传统的 NetBeans IDE 平台进行了比较。实验值展示了 OMFOVR 技术在路线选择方面优于比较方法。