How can you optimize IPTV content delivery for low-bandwidth networks?

As many readers may want more detail: MPEG-2, which is widely compatible but less efficient, is suitable for SD content but requires considerable bandwidth for HD. MPEG-4 (AVC/H.264) improves compression, supporting both SD and HD, but needs more processing power. H.264, is the most widely used in end devices today (2023). It balances quality and compatibility, efficiently streaming live and on-demand content but is less ideal for 4K resolutions. HEVC (H.265) excels in compressing 4K/8K content, significantly reducing bandwidth, but faces limited support on older devices and higher computational costs, especially if encoded in the cloud.

That is not good enough. If you need to go low , you have to know how much your signal was already damaged upstream and by what. If I take the example of a very well produced European football game that is delivered internationally the path of the signal is a 220MBs J2K from OB to commentary and graphics off site. a next one of the same from production to sat uplink with a 32Mbs H264 to finally go to the broadcasters and cable and IPTV platforms who will then do the job of squeezing even more . It will look mushy at best with a 10Mbs HEVC compression. now is you pick up the signal after the first hop and deliver directly into your network it will look better at 5MBs than the above version.

Choice of encoding format is only possible in greenfield projects. Newer encodings can be available at the transmitter site but the receiver might not be able to be retrofitted to accommodate them. When choice is completely free, the latest encoding format is always better than the preceding ones as it will save bandwidth for the same delivered quality.

I think when choosing the encoding format there are three factors that need to be equally evaluated. Codec, Bitrate and Quality. Looking at these as a whole. In a low-bandwidth application the bitrate is already a limited factor. So that leaves choosing the right codec that provides the quality expected by your target customer all while maximizing the number of customers. Depending on your application you may need to run several different combinations based on the end users devices.

For customers, it means the best streaming quality will be rendered regardless of fluctuations in bandwidth. For carriers, ABR reduces bandwidth costs and network congestion, as it optimises data usage based on real-time network conditions, enhancing overall service quality and customer satisfaction.

Adding AI (Artificial Intelligence) and ML (Machine Learning) and Just in Time encoding to the ABR technique further enhances the capacity to adapt in real time to the network conditions. Just in Time encoding will allow you to reduce storing requirements and AI/ML can help anticipate changes in network conditions.

This sentence is incorrect "which is a technique that adjusts the bitrate and resolution of the video stream according to the available bandwidth and device capabilities" The correct explanation is given below. The receiving device selects one of the available streams.

The question is how many different resolution and bitrate combinations do you want to provide. Having more combinations allows for the switching between them less noticeable but makes the implementation more complex. While a simplified implementation with less resolution makes the switching between resolutions more obvious. It would come down to the target audience and what they are willing to accept and maybe the content. A very popular sporting event might benefit from multiple resolutions but a less popular event/show can get away less resolution.

Getting the content (no matter what it is) as close to the subscriber as possible is always the best strategy, if economically viable.

Adding the right congestion control algorithms to your caches/edges on how fast to send packets from those caches/edges to the actual eyeballs. The longer and more network parts the route needs to travel from the cache/edge to the eyeball, and the less control you have over the network, the more important this gets and can have significant effects. Standard caches/edges will support TCP Cubic but there are free alternatives like commonly used BBR1 and BBR2 from Google or commercial alternatives like those of CompiraLabs that offer a dynamic ML-based version of PCC to get the best possible algorithm.

And why are managing these resources and strategies of such importance. Well because you want to make sure you enable monetization by providing a premium end user experience with ads or without ads. Remember is not how the solution behaves under optimum conditions, is how it behaves under real life constraints.. Also Ad insertion will benefit from an excellent experience derived from the AI/ML techniques to best manage ABR , catching in public and private CDNs . Imagine if you can properly predict expected network behavior during high demand live events and therefore ensure your OTT delivery is unlike any other ? Will this be a desired end user outcome ? What's important , resolution or. enablingbest possible experience through AI/ML use

Service delivery planning and control, in this case video delivery, is key to get the most of the service you have. All the pieces in the equation are expensive: coding of content, service headend, choice of networks to deliver, and terminal devices. You have to know where is the part of the service in which injecting effort (money) will make the most sense. Assuming that you do not own the network and you cannot improve the bandwidth, you can plan how you put your bits on the wire. A CDN that is video-aware will help, by means of congestion avoidance and use of modern ABR, typically using DASH and other features. But of course you will have to have a good pairing of encoding profile-max bandwidth available-terminal capabilities.

Be close to the content! IPTV’s traffic profile is similar to games, I mean, they're like real-time streaming and any loss/latency will have influence to UX. Therefore, in addition to having the 'boxes' of the main CDNs or OTTs and having a good routing policy, it’s important to establish a BGP peering directly to the Content Provider to avoid any issues on the Transit. Be close to the contente means having many BGP peerings established across the mais Internet Exchanges (IX’s) around the world. What if you’re a small ISP, can you peer with a remote contente? Yes! If you’re a small ISP and you’d like to improve your IX’s connections, you can order a connection (with a carrier) to remotely IX and start peering to other participants.

In addition to the above content aware streaming or audience aware encoding where the cdns feed the encoders with information on the processing needed for each streams by machine learning mimicking the statmux feature for OTT would significantly optmize bandwidth cost and efficiency..

Budget. I assume that there isn't a bottomless pit of money. You could design the ultimate system, but more than likely it is not very cost effective and expensive. Here are two determining factors for the budget. Location. Are you going to run the encoding on a cloud server, or are you going to build your own systems and infrastructure. Hardware. Will you use CPU, GPU or VPU (ASIC designed for video encoding).