QoS现状2017

2016年，OTT供应商开始意识到OTT消费者一直在说的话:质量是获得和留住客户的关键, 从订阅者到内容所有者.

A case in point was the very public feedback after the launch of DirecTV Now.

AT&作为一种OTT服务，它将有线和广播电视频道捆绑在一起，这在纸面上听起来很棒, 尤其是当&T提供了优惠的入门费用，并赠送了一台新的Apple TV，让消费者可以开始观看他们订阅的数十个实时线性OTT频道中的一个. But the experience for consumers, judging by hundreds of complaints posted on AT&T, DirecTV, and other user forums, was anything but great.

根据恩里克·罗德里格斯的说法&T娱乐的首席技术官, 2016年早些时候对Quickplay的收购具有战略意义，因为双方都拥有基于AT的OTT交付技术&T’s infrastructure and also for allowing the rollout to meet expectations.

“当然存在问题,罗德里格斯说, in an interview with FierceCable at the 2017 CES show in January. “The problems were not as big as I expected. I’m so proud of the quality we delivered.”

订阅者似乎无动于衷, 甚至一个月后的CES, 而Sling等竞争对手正利用这种不满情绪，驱使心怀不满的DirecTV Now用户尝试Sling更成熟的在线直播捆绑服务.

为什么QoS?

在流媒体行业中，一个架构合理的QoS方法应该产生高质量的体验，这是毋庸置疑的. In fact, it’s one of the industry’s primary mantras.

There are many ways to improve a delivery network’s QoS, 哪一个, 反过来, benefits an end user’s quality of experience (QoE).

Most of these approaches are outside the control of the content owner, and many are also outside the reach of the content publishing solution (e.g., last mile, multiple devices on a home network, etc.). 几, 虽然, can be directly influenced by the choice of protocols, 编解码器, 甚至分段或块大小.

We covered some of those choices in a recent 流媒体 article called “延迟糟透了!” 该研究着眼于小分割尺寸和较新的交互式视频协议，如WebRTC. 本文为理解延迟如何影响最终用户的总体QoE提供了很好的基础.

从结尾开始

OK, now that we’ve determined just how broad a reach QoS can have, with complex networking and technology challenges impacting an end user’s QoE, what happened in 2016 that changed the QoS conversation?

QoS实现中一个重要的增长领域是通过使用度量工具来理解消费者的消费.

In both kindergarten and Alice in Wonderland, you were told to start at the beginning and persevere until you reach the end. 但在QoE的世界里, 事实证明，您需要从最后开始正确地跟踪从媒体服务器或选择的在线视频平台(OVP)提供内容后可能出现的问题.

In other words, as Jiddu Krishnamurti observed in 唯一的革命, “结束就是开始, and the beginning is the first step, 第一步是唯一的一步.”

让我们从最远的终端用户消费点开始:你向观众流出的内容最终被播放的设备.

Measuring Analysis With Practical QoS Impact

无论您是内容所有者, 内容发布者, 或者是负责向最终用户交付流媒体内容的基础设施的网络工程师, 实时分析的出现, based on data gathered from real users, is a step in the right direction that gained traction in 2016.

To understand the world of analytics—especially real-time analytics, 哪些可以用来将名义上良好的最终用户体验转变为高质量的用户体验——我们首先需要了解行业处理最终用户度量的方式.

度量最终用户QoE的主要方法被称为真实用户度量，或简称RUM.

A number of companies in the industry provide RUM tools. 流媒体的 Dan Rayburn provided an overview of a number of these companies in a September 2016 博客，包括QoE检查表.

Another area to focus on is the dashboard itself. After all, it’s hard to take action with just data. NeuLion, 例如, 推出了OTT仪表板, 它将QoS监控(直播和VOD内容)与观看和设备类型的地理集群热图结合在一起. NeuLion says its dashboard updates “every 30 seconds with views broken down by device, 比特率, “位置”作为一种确保内容正确传递到热图中确定的区域的方法.

这个团队工作中的好人 (NPAW)利用Youbora的大数据分析，为广播公司优化了多cdn方案. NPAW声称其解决方案提供了“实时的视频体验信息”, with granular data specific to individual end users,” meaning it is measuring at both the CDN and end customer points of the delivery pipeline.

NPAW和 Ooyala, an OVP with its own analytics package, 将他们的解决方案整合为OVP/CDN负载平衡以及Ooyala的受众参与工具的分析和指标. This trend will probably continue into 2017, ovp要么创建自己的实时分析和负载平衡，要么与QoS公司合作，帮助实时调整流量塑造需求.

2016年初，由 Conviva against NPAW accused the latter of infringing on multiple U.S. 康维娃持有的专利. “Conviva花了十年时间投资和开发屡获殊荣的视频监控和优化解决方案, and holds several foundational patents protecting its technology,” said Conviva CEO Hui Zhang in March 2016. “We believe innovation and diversity provides for a stronger ecosystem. 然而, we cannot stand by and watch Conviva’s IP be intentionally and flagrantly exploited, and we will defend our intellectual property rights through every means available to us.”

原因尚不清楚, the lawsuit was dropped in September 2016, 在指定的法官听取了围绕三项专利的案件的口头辩论后两天,874,725; 9,100,288; 9,246,965.

Are Real-Time Analytics Really Real Time?

我们都认识到，在有机增长的视频点播(VOD)市场上，分析可以为构建基础设施带来好处. But what about the real-time impact during a live-streaming event, beyond just the post-game analysis that’s beneficial in beefing up overall infrastructure?

一些公司，如 Cedexis, center solutions on multi-CDN strategies for delivering video in real time. The aptly named Cedexis Buffer Killer can be used, 据公司介绍, with “a combination of CDNs with cloud origins, as a strategy of choice to improve end user experience while controlling costs.”

对于Conviva, with its Precision performance mapping, QoS还意味着不仅要满足最终用户的QoE期望，还要满足内容发布者对多个cdn的各种流量和资金承诺.

这些分析产品之间的关键区别之一是数据点的数量, but pay attention to the type of data points each company specializes in. Some may be more generic HTTP delivery, while others may offer granularity for specific streaming protocols.

同样地, 仅仅拥有最多的数据测量点并不意味着可以实现可操作的QoS. 请公司举例说明他们的服务是如何处理各种网络环境的，并举例说明你所在行业中规模类似的公司.

So how quickly can decisions be made on based on RUM data?

Cedexis says that the decision-making process sweet spot is 7–15 seconds. This timeframe—well within the bounds of a typical live stream, 通常在到达最终用户的设备时延迟15-30秒——包括从数十万个RUM数据中收集数据的时间, 甚至几百万, 终端用户设备.

这是关键, 因为业务逻辑需要足够健壮，不仅可以处理企业可能面临的流媒体视频问题，还可以处理特定于行业的规则，以便在监管框架内保护组织.

“数据从用户发送到完全投入并指导决策在7到15秒内完成,西蒙·琼斯说, Cedexis的流媒体布道者, 它的Openmix产品是一个提供决策能力的全局服务器负载平衡器(GSLB).

Jones说，Cedexis Live服务甚至可以绘制“非常小的故障”热图，然后通过Openmix决策引擎同时反映出来. Decisioning also has a predictive element, 据琼斯说, so problems are very quickly recognized and actionable.

未来的趋势是什么? “Predictive” is a term to watch in 2017.

“If there is a goal in terms of accelerating impact, 我认为，公平地说，我们正在努力实现越来越预测性的交通管理,琼斯说。.

Wi-Fi网络的QoS

With a significant amount of OTT consumption occurring on portable devices, what is being done to address QoS for Wi-Fi devices in the home, 在零售场所, 或者在餐馆?

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