The development of intelligent traffic systems can benefit from the pervasiveness of IoT technologies. In recent years, increasing numbers of devices are connected to the IoT, and new kinds of heterogeneous data sources have been generated. This leads to traffic systems that exist in extended dimensions of data space. Although cloud computing can provide essential services that reduce the computational load on IoT devices, it has its limitations: high network bandwidth consumption, high latency, and high privacy risks. To alleviate these problems, edge computing has emerged to reduce the computational load for achieving TDaaS in a dynamic way. However, how to drive all edge servers' work and meet data service requirements is still a key issue. To address this challenge, this article proposes a novel three-level transparency-of-traffic-data service framework, that is, a KID-driven TEC computing paradigm. Its aim is to enable edge servers to cooperatively work with a cloud server. A case study is presented to demonstrate the feasibility of the proposed new computing paradigm with associated mechanisms. The performance of the proposed system is also compared to other methods.

中文翻译：

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KID 模型驱动的事物 - 交通数据即服务的边缘云计算范式


智能交通系统的发展可以受益于物联网技术的普及。近年来，越来越多的设备连接到物联网，并产生了新型异构数据源。这导致交通系统存在于数据空间的扩展维度中。虽然云计算可以提供减少物联网设备计算负载的基本服务，但它也有其局限性：高网络带宽消耗、高延迟和高隐私风险。为了缓解这些问题，边缘计算应运而生，以动态方式减少实现 TDaaS 的计算负载。然而，如何驱动所有边缘服务器工作并满足数据服务需求仍然是一个关键问题。为了应对这一挑战，本文提出了一种新颖的三级流量数据透明服务框架，即 KID 驱动的 TEC 计算范式。其目的是使边缘服务器能够与云服务器协同工作。提出了一个案例研究来证明所提出的新计算范式及其相关机制的可行性。所提出的系统的性能也与其他方法进行了比较。