High mobility in ITS, especially V2V communication networks, allows increasing coverage and quick assistance to users and neighboring networks, but also degrades the performance of the entire system due to fluctuation in the wireless channel. How to obtain better QoS during multimedia transmission in V2V over future generation networks (i.e., edge computing platforms) is very challenging due to the high mobility of vehicles and heterogeneity of future IoT-based edge computing networks. In this context, this article contributes in three distinct ways: to develop a QoS-aware, green, sustainable, reliable, and available (QGSRA) algorithm to support multimedia transmission in V2V over future IoT-driven edge computing networks; to implement a novel QoS optimization strategy in V2V during multimedia transmission over IoT-based edge computing platforms; to propose QoS metrics such as greenness (i.e., energy efficiency), sustainability (i.e., less battery charge consumption), reliability (i.e., less packet loss ratio), and availability (i.e., more coverage) to analyze the performance of V2V networks. Finally, the proposed QGSRA algorithm has been validated through extensive real-time datasets of vehicles to demonstrate how it outperforms conventional techniques, making it a potential candidate for multimedia transmission in V2V over self-adaptive edge computing platforms.

中文翻译：

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物联网驱动的智能交通系统中的服务质量优化

ITS（尤其是V2V通信网络）中的高移动性允许增加覆盖范围并为用户和邻近网络提供快速帮助，但由于无线信道的波动，还会降低整个系统的性能。由于车辆的高移动性和未来基于物联网的边缘计算网络的异构性，如何在下一代网络（即边缘计算平台）上的V2V多媒体传输过程中获得更好的QoS非常具有挑战性。在这种情况下，本文以三种不同的方式做出了贡献：开发一种可感知QoS，绿色，可持续，可靠和可用（QGSRA）的算法，以支持未来IoT驱动的边缘计算网络在V2V中进行多媒体传输；在基于物联网的边缘计算平台上进行多媒体传输时，在V2V中实现一种新颖的QoS优化策略；提出QoS指标，例如绿色（即，能源效率），可持续性（即，较少的电池电量消耗），可靠性（即，较小的丢包率）和可用性（即，更大的覆盖范围）以分析V2V网络的性能。最后，通过广泛的车辆实时数据集对所提出的QGSRA算法进行了验证，以证明其性能优于传统技术，使其成为通过自适应边缘计算平台在V2V中进行多媒体传输的潜在候选者。