It means if a system can only do X of something per second, then if you push the system past that, new arriving stuff has to wait on existing work in the queue, and things take longer than if the queue was empty. You can think of it like a traffic jam and it applies to most systems.
For example, our local radio station here in Cape Town loves to talk about "queuing traffic" when they do the 8am traffic report, and I always think of Little's law.
Bufferbloat is another example of queueing delay, e.g. where you fill the buffer of your network router say with a large Gmail attachment upload and spike the network ping times for everyone else sharing the same WiFi.
It means if a system can only do X of something per second, then if you push the system past that, new arriving stuff has to wait on existing work in the queue, and things take longer than if the queue was empty. You can think of it like a traffic jam and it applies to most systems.
For example, our local radio station here in Cape Town loves to talk about "queuing traffic" when they do the 8am traffic report, and I always think of Little's law.
Bufferbloat is another example of queueing delay, e.g. where you fill the buffer of your network router say with a large Gmail attachment upload and spike the network ping times for everyone else sharing the same WiFi.
Here is where I got the per-core bandwidth calculation from: https://www.eidos.ic.i.u-tokyo.ac.jp/~tau/lecture/parallel_d...