Network communication has become a part of everyday life, and the interconnection among devices and people will increase even more in the future. Nevertheless, prediction of Quality of Service parameters, particularly throughput, is quite a challenging task. In this survey, we provide an extensive insight into the literature on Transmission Control Protocol throughput prediction. The goal is to provide an overview of the used techniques and to elaborate on open aspects and white spots in this area. We assessed more than 35 approaches spanning from equation-based over various time smoothing to modern learning and location smoothing methods. In addition, different error functions for the evaluation of the approaches as well as publicly available recording tools and datasets are discussed. To conclude, we point out open challenges especially looking in the area of moving mobile network clients. The use of throughput prediction not only enables a more efficient use of the available bandwidth, the techniques shown in this work also result in more robust and stable communication.

中文翻译：

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有线和无线网络中客户端吞吐量预测算法综述

网络通信已成为日常生活的一部分，未来设备与人之间的互联互通将更加紧密。然而，服务质量参数的预测，特别是吞吐量，是一项相当具有挑战性的任务。在本次调查中，我们对有关传输控制协议吞吐量预测的文献提供了广泛的见解。目的是提供所用技术的概述，并详细说明该领域的开放方面和白点。我们评估了超过 35 种方法，从基于方程的各种时间平滑到现代学习和位置平滑方法。此外，还讨论了用于评估方法的不同误差函数以及公开可用的记录工具和数据集。总而言之，我们指出了开放的挑战，尤其是在移动移动网络客户端领域。吞吐量预测的使用不仅可以更有效地利用可用带宽，而且这项工作中显示的技术还可以实现更健壮和稳定的通信。