2019年编码设备买家指南
Software encoding, especially in the cloud, is all the rage these days. Not only has cloud-based encoding reached feature-set parity with older local (on-premises) hardware-based encoders, but the speed of data networks now enables uploading uncompressed or slightly compressed video files to cloud-based transcoders.
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Yet there are still very viable reasons to consider using hardware-based encoding, 我们将在本《百家乐软件》中介绍其中一些. 第一个, we’ll take into consideration the extremes of hardware-based encoding: ultra-portable and ultra-dense.
超便携编码:The ultra-portable encoding category contains two types of encoders: studio production and field production. 在这两个例子中, 编码器的外形尺寸非常小, whether it be a dedicated single-board computer (SBC) or a purpose-made encoder in a ruggedized casing.
超密度编码:超密集类别主要侧重于机架式编码, whether it be in a production environment (where the output of each camera is recorded simultaneously in a common codec, 格式, and 决议) or in a data center (where content is received as an IP stream and then re-encoded or repackaged for streaming delivery).
考虑到这些类别，有哪些因素 流媒体 readers should consider when comparing encoding appliances with each other or comparing them against software-based encoding solutions?
有限的带宽
One argument for cloud-based encoding is the ability to forego capital expenses (CapEx) and only use what computing is needed as part of ongoing operations (OpEx). But one of the last costly CapEx seems to be the most overlooked: equipment to meet bandwidth requirements.
在过去的几年里, when my lab has run comparison tests of cloud-versus-hardware encoding— centered on uploading a full-sized video asset for cloud-based encoding, versus simply transcoding the same asset on a local device—we’ve often run into the issue of customers having bandwidth that’s limited enough that it skews the results more toward the continued use of on-premises encoders than cloud-based transcoding.
While it might be easy to dismiss this by noting that theoretical bandwidth and actual bandwidth differ, too often we’ve found that our clients haven’t allocated the CapEx to keep the DSL router or cable modem up to modern specs.
有线电视提供商数据网络的最新进展, 包括扩大光纤到户的使用, mean that it’s now time to consider upgrading on-premises devices to meet the Data Over Cable Service Interface Specifications (DOCSIS) 3.1级连接. 而DOCSIS 3.0 specification has been around since 2006, it’s been only since 2016 that full-duplex DOCSIS 3.1 has enabled data rates higher than 1Gbps (gigabit per second) in both upstream and downstream configurations. 虽然1Gbps对于你当地的场地来说可能听起来有点夸张, the actual data rate is often 1/10 or less of the stated throughput, in no small part based on the way cable service providers use a shared network between units in multi-tenant office or housing complexes.
因为大多数有线电视供应商不提供DOCSIS 3.1 equipment, it falls to venue owners or content creators to upgrade their own on-premises hardware. But doing so may significantly change the dynamics around hardware encoding appliances for live events, including the ability to push out one or more ultra-high-definition (UHD) 4K signals.
对速度的需求
如果基于软件的编码速度不足以满足您的需求怎么办? An example of this from an ultra-dense encoding standpoint is the need to convert multiple UHD 4K signals into streaming 格式s with web-friendly data rates.
Using a standard laptop or even a robust desktop computer with a single software package provides a cost-effective solution. But that approach will take an inordinate amount of time to convert even just one UHD 4K signal to one streaming output of a particular data rate, 决议, 帧率, 颜色深度.
另一方面, 在软件中使用刀片计算当然是可行的, but the cost associated with populating the multi-blade server with processors, RAM, 存储, 软件可能会让人望而生畏. 然后是刀片服务器的外形因素, which necessitates finding a place to put the server in a data rack, 最好是在生产环境听不到的地方.
在中间地带存在什么替代方案? Haivision 宣布了一个这样的选择, KB Max, 在去年的全国广播协会(NAB)展会上. KB Max框的功能类似于非此即彼的解决方案, offering either localized transcoding “by encoding full adaptive-bitrate cascades in HEVC or H.264”，最多可同时进行四个1080p编码, or acting as a transmitter of “high-quality single bitrate streams up to 4K UHD to all major platforms for cloud transcoding.”
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