The rapid advancement of the Internet of Things is expected to play a critical role in future intelligent transportation systems. This technology utilizes advanced information and communication technologies to enhance the operational capabilities of the vehicles and is often referred to as IoAV. More importantly, the increasing usage of sensors and other technologies generates vast amounts of data and information to be exchanged between AVs. Since the wireless connectivity between AVs is constantly expanding, the transmission of data is expected to pose several challenges to the conventional wireless networks, including resource utilization, network optimization, quality of service, and so on. To overcome these challenges, software-defined networking (SDN) has emerged as a powerful technology. This article presents a composite architecture named SD-IoAV for the integration of SDN with IoAV. This integration is not straightforward because SD-IoAV is geographically dispersed by nature. An efficient technique to manage the underlying communications is to deploy multiple SDN controllers across the widely dispersed SDN domains. This is referred to as the controller placement problem (CPP). Thus, the primary focus of this work is to explore CPP in the context of SD-IoAV as a special case of energy minimization and load balancing under latency restrictions. In this context, for large networks, the number of variables increases exponentially, which in turn escalates the complexity of the problem manifold. Hence, to deduce a near optimal solution for large networks, a heuristic approach based on the incremental expansion of candidate space is proposed. The simulation results have been carried out in MATLAB, and the obtained results show that the proposed scheme attains higher energy savings and better load capacity management compared to an existing technique, that is, improved performance by 18.73 and 9.42 percent, respectively.

中文翻译：

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基于SDN的自动驾驶汽车互联网：一种高效节能的控制器布局方法

物联网的快速发展有望在未来的智能交通系统中发挥关键作用。该技术利用先进的信息和通信技术来增强车辆的操作能力，通常被称为IoAV。更重要的是，传感器和其他技术的日益普及产生了大量的数据和信息，这些信息将在视音频之间进行交换。由于AV之间的无线连接性不断扩大，因此数据的传输有望给常规无线网络带来一些挑战，包括资源利用，网络优化，服务质量等。为了克服这些挑战，软件定义网络（SDN）已经成为一种强大的技术。本文介绍了一种用于将SDN与IoAV集成的名为SD-IoAV的复合体系结构。由于SD-IoAV本质上在地理位置上是分散的，因此这种集成并不简单。管理基础通信的有效技术是在广泛分布的SDN域中部署多个SDN控制器。这称为控制器放置问题（CPP）。因此，这项工作的主要重点是在SD-IoAV的背景下探索CPP，将其作为在等待时间限制下能量最小化和负载平衡的特例。在这种情况下，对于大型网络，变量的数量呈指数增长，这反过来又增加了问题流形的复杂性。因此，为了得出大型网络的最佳解决方案，提出了一种基于候选空间增量扩展的启发式方法。在MATLAB中进行了仿真，结果表明，与现有技术相比，该方案具有更高的节能性和更好的负载容量管理，性能分别提高了18.73％和9.42％。