【标题】Artificial intelligence - Based video traffic policing for next generation networks
【参考中译】基于人工智能的下一代网络视频流量管制
【类型】 期刊
【关键词】 Video traffic; Traffic policing; Artificial intelligence; Neural networks; Performance evaluation; H.264; H.265
【参考中译】 视频流量；流量管制；人工智能；神经网络；性能评估；H.264；H.265
【作者】 Khandu Om; Randeep Singh; Snehdeep; Amandeep Kaur; Deepika; Anureet Kaur; Tanya McGill; Michael Dixon; Kok Wai Wong; Polychronis Koutsakis
【摘要】 The constant increase in users' bandwidth needs, through a large variety of multimedia applications, creates the need for highly effective network traffic control. This need is imperative in wireless networks, where the available bandwidth is limited, but is very important for wired networks as well. In this work we focus on the problem of policing video traffic from sources encoded with H.264 and H.265, given that these are the major state-of-the-art standards currently in the market. Building on work that has shown that classic traffic policing schemes can lead to unnecessarily strict policing for conforming video sources, we propose the use of Artificial Intelligence (AI) - based traffic policing schemes for video traffic. We conduct a performance evaluation of several AI - based schemes with the classic token bucket and we show that our proposed Frame Size Predictor and Policer scheme improve the performance of the classic token bucket by around 90% for conforming users, while providing only slightly worse policing results for non-conforming users.
【参考中译】 通过各种多媒体应用，用户带宽需求的不断增加，产生了对高效网络流量控制的需求。这一需求在可用带宽有限的无线网络中势在必行，但对于有线网络也非常重要。在这项工作中，鉴于H.264和H.265是目前市场上最先进的主要标准，我们将重点关注来自H.264和H.265编码源的视频流量的监管问题。基于经典流量管制方案可能导致对符合视频源的不必要的严格管制的工作，我们建议使用基于人工智能(AI)的视频流量管制方案。我们使用经典令牌桶对几种基于人工智能的方案进行了性能评估，结果表明，对于符合条件的用户，我们提出的帧大小预测器和策略器方案将传统令牌桶的性能提高了约90%，而对于不符合令牌桶的用户，仅提供了略差的监管结果。
【来源】 Simulation Modelling Practice and Theory 2022, vol.121
【入库时间】 2023/4/27
【标题】ARTIFICIAL INTELLIGENCE: HOPE, HYPE AND FOMO
【参考中译】人工智能：希望、炒作和FOMO
【作者】 Tim Foreman
【摘要】 Ten years ago when Omron received enquiries about AI-based projects, they were mainly driven by hype or FOMO. When customers were asked why they wanted to get into AI, the answer, more often than not, was either 'because my boss asked me to', 'because we have a lot of data' or 'because it seems like an interesting area'. None of these were particularly solid reasons and certainly did not justify the hefty investment that AI applications would have required at that time. That is changing, and hope, rather than hype or 'FOMO', is the driver. Customers do not ask whether Omron can help them with AI anymore. They ask whether Omron can help with predictive maintenance, quality control or process optimisation. They come to the company with a problem that they want help to solve. The adoption of AI is no longer a motive or an aim in itself. Instead, AI has become an 'enabler'.
【参考中译】 10年前，当欧姆龙收到关于基于人工智能的项目的询问时，他们主要是受到炒作或FOMO的推动。当客户被问及为什么想要进入人工智能领域时，他们的回答往往是，要么是因为我的老板让我这么做，要么是因为我们有大量的数据，或者是因为这似乎是一个有趣的领域。所有这些都不是特别可靠的理由，也肯定不能证明当时人工智能应用程序所需的巨额投资是合理的。这种情况正在改变，而希望，而不是炒作或‘’FOMO‘’，才是驱动因素。客户不会问欧姆龙是否还能在人工智能方面帮助他们。他们问欧姆龙是否可以在预测性维护、质量控制或流程优化方面提供帮助。他们带着一个他们想要帮助解决的问题来到公司。人工智能的采用本身不再是一个动机或目标。取而代之的是，人工智能已成为一种“推动者”。
【来源】 Instrumentation Monthly 2022, no.Oct.
【标题】Artificial intelligence: Hope, hype and FOMO
【摘要】 10 years ago, AI-based projects were mainly driven by hype or FOMO. Now, the adoption of AI is no longer a motive or an aim in itself. Instead, AI has become an 'enabler'. In the past, when asked why they wanted to get into AI, the answer from companies, more often than not, was either "because my boss asked me to", "because we have a lot of data", or "because it seems like an interesting area".
【参考中译】 10年前，基于AI的项目主要是由炒作或FOMO驱动的。现在，采用人工智能本身不再是一个动机或目标。取而代之的是，人工智能已成为一种“推动者”。过去，当被问及为什么要进入人工智能领域时，企业的回答往往是“因为我的老板让我这么做”，“因为我们有大量数据”，或者“因为这似乎是一个有趣的领域”。
【来源】 Panel building and system integration 2022, no.Nov.