Unicasting of entertainment video is the primary reason why consumer data demand keeps growing. Edge computing and content delivery networks are one method for containing wide area network capacity demand.
So is multicasting.
In the days of broadcast TV and audio, essentially one copy of an item was sent out to all potential users at one time (one to all).
In other words, unicast delivery is demand sensitive, while multicasting is not. If N users request a particular file, unicast delivery must create N separate streams. A multicast system, in principle, creates just one stream.
As a simple example, a single unicast file requested by three users requires three separate streams. At bandwidth N, total consumed bandwidth is 3N.
When three users request a single file and multicasting is possible, one copy is launched to three addresses. Capacity consumed across the wide area network is just one stream. Total WAN bandwidth consumed is N.
If one video stream requires 4 Mbps, then a broadcast system consumes only 4 Mbps of total capacity. A unicast alternative requires 4 Mbos times N, in terms of bandwidth, where N is the number of users.
The network capability implications are enormous. As a one-to-one delivery mechanism, unicast networks require discrete network consumption for every identical file delivered to any number of end users who request it, whether demand is synchronous (all want the file at the same time) or asynchronous (at different times).
A multicast network operates more like a broadcast network, in the sense that all potential users of one piece of content, requesting it at the same time, are sent one copy, but addressed to all users requesting the file. Multicasting is a one to many delivery mechanism.
The point is that unicast content delivery is why consumer data demand keeps growing. As linear video consumption decreases, much more bandwidth is required to deliver content to the same number of active viewers.
As a practical matter, broadcasting and multicasting are functionally the same: all viewers who want to watch a particular event or item essentially receive the same copy. In the former case the selection is made by the user device and channel selection (device on or off; tuned to a particular channel or not).
In the latter case, copies are delivered to those user addresses who have requested delivery. The capacity implications are roughly the same, either way.
So content delivery networks and edge computing, storage and delivery are ways of containing unicast delivery costs. Signal compression, offline delivery and non-real-time delivery are methods for alleviating some of the peak capacity demand.
At the very least, serving up content closer to end users reduces capacity demands on core networks. Edge content delivery also improves latency performance.
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