物联网的流量分化

Thiago Garrett, S. Dustdar, L. C. E. Bona, E. P. Duarte
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引用次数: 5

摘要

在流量和市场份额方面,物联网(IoT)预计将在未来构成互联网的重要组成部分。要充分发挥其潜力,就必须有创新的解决方案来应对若干开放的挑战。在这种情况下,我们讨论网络中立性,它指出互联网上的所有流量必须被平等对待,即没有流量分化(TD)。不公平的流量管理可能导致非竞争市场,选择性地影响不同物联网应用的体验质量。这种情况可能会阻碍创新,威胁物联网的成功。因此,监测物联网上的输配电对于竞争更激烈的市场至关重要。在本文中,我们首先研究了TD对常见物联网流量模式(如定期更新和实时通知)的影响。我们给出了仿真结果,并讨论了哪些类型的物联网应用最受TD的影响。然后,我们讨论了在物联网上监控TD的解决方案。该解决方案利用物联网来解决TD检测的几个开放挑战。例如,大量的设备导致了进行td相关测量的高产环境。因此,该解决方案可以在众多物联网设备和应用程序通信时使用机器学习来持续监控TD。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Traffic Differentiation on Internet of Things
The Internet of Things (IoT) is expected to constitute a significant portion of the Internet in the future, both in terms of traffic, and market share. For it to achieve its full potential, innovative solutions are necessary to address several open challenges. In this context we discuss Network Neutrality, which states that all traffic in the Internet must be treated equally, i.e., without traffic differentiation (TD). Unfair traffic management may result in a non-competitive market, affecting selectively the quality of experience of different IoT applications. This scenario might hinder innovation, threatening IoT success. Monitoring TD on the IoT is thus important for a more competitive market. In this paper, we first study the impact of TD on common IoT traffic patterns, such as periodic updates and real-time notifications. We present simulation results, and discuss which types of IoT applications are most affected by TD. We then discuss a solution for monitoring TD on IoT. The solution takes advantage of the IoT to address several open challenges of TD detection. For instance, the large amount of devices results in a prolific environment for making TD-related measurements. The solution can thus employ machine learning for continuously monitoring TD as the numerous IoT devices and applications communicate.
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