How can you maintain network performance with low-bandwidth clients?

If you difference (diff) a status message with the last message you sent before you compress it, you can save kb of data. Often you are sending most of the data without change, or just with small changes. If you get an error back you need to send a full message and then start diff-ing again after that. The other side just saves the last message you sent and applies the diff, making sure a checksum works for the message. If the checksum fails, ask for the full status. You can keep a mb sized file synchronized over a 9600 baud modem if all that is changing is a few sentences at a time. Like someone is typing.

Content Delivery Networks excel in caching and prefetching. Edge caching, coupled with data compression, is highly effective in low-bandwidth areas for streaming services. Time to Live (TTL) in HTTP defines data validity, demanding higher edge capacities for longer TTL. Cloud vendors use 'eventual consistency' to sync large data geographies, adaptable to low-bandwidth zones using refresh techniques. Prioritizing data becomes crucial. 'Network slicing,' common in 5G, isolates data transfer, ensuring minimal user impact. (My Original write up was more than 1000 words and has been condensed using AI content creator)

You want to make this a layer/library that wraps your function calls at the higher level so it doesn't make your code complicated. All the complexity is hidden in the cache/prefetch layer. And by doing it this way it makes it trivial to turn off caching for high speed low latency connections.

Die richtige Plazierung der Content Delivery Network Knoten/ Cluster ist hier in diesem Zusammenhang der entscheidende Erlfogsfaktor

There are also methods using epoll() and sendfile() that can allow a server program to handle 10K client connections on modest hardware. These don't have the overhead of select() style network functions and the kernel handles the actual data sending on the sendfile() calls, cutting your application out of the loop for sending data from the hard disk. Of course these much improved functions are only supported on modern "UNIX" style operating systems. You can use these servers for sending large files from disk for game/program updates or level loading. You can have a different group of servers that stores game status and shares the updates with many clients. The OS these servers use don't have to match the bulk file send servers.

Few other considerations in low bandwidth areas include creation of private network bubbles which allow creation of small local networks for carrying data over smaller lengths with central hub to perform processing at edge. This technique is especially useful in Defense Sector, Border Protection, Disaster Areas etc. Recent innovations in areas of 5G furthers this technique. During edge processing, a decision matrix needs to be developed which will allow carrying only meaningful and prioritized data over longer geographies over SATCOM. At edge processing, please consider removing digital exhaust out of the system. It has been seen that high % of the data generated at the edge is more for observability purposes than actual business data.