如何通过UDP协议传输网络大数据？方案分析与见解征询

Let’s break down the core tradeoffs first—they’re the heart of this problem:

• Repeated send() calls with MTU-sized packets

  • The upside: No IP fragmentation at all. Each packet fits neatly within the network’s MTU, so routers don’t waste cycles reassembling fragments.
  • The downside: Every single send() triggers a user-kernel context switch. For large datasets, this overhead piles up quickly and eats into performance.

• Sending large N*MTU packets in one send() call

  • The upside: Way fewer context switches (one call instead of N), which cuts down on the costly back-and-forth between user and kernel space.
  • The downside: Forces IP fragmentation. Every router along the path has to reassemble the entire packet before forwarding it, slowing end-to-end transmission. Plus, if even one fragment gets lost, the whole packet has to be retransmitted—riskier than sending intact MTU-sized packets.

After digging into these tradeoffs and doing some research, I think I’ve found a solid middle ground: using readv()/writev() with iovec structures to send MTU-sized packets. Here’s why this works:

• writev() lets you pull data from multiple non-contiguous user-space buffers and assemble them into a single MTU-sized packet in one system call. No need to copy data into a single buffer first—saves both time and memory.
• You still avoid IP fragmentation entirely (each packet stays MTU-sized), but you cut way down on context switches compared to repeated send() calls.
• On the receiving end, readv() pairs perfectly: it lets you split incoming MTU-sized packets into multiple buffers efficiently, keeping the whole pipeline streamlined.

I’d love to get deeper insights from the community here. Are there edge cases I’m overlooking? Scenarios where this approach underperforms, or better alternatives I haven’t considered? Let’s hash this out!

内容的提问来源于stack exchange，提问作者Ritesh