Introduction
kcp-go is a Reliable-UDP library for golang.
This library is designed to provide smooth, resilient, ordered, error-checked and anonymous delivery of streams over UDP packets. It has been battle-tested with the open-source project kcptun. Millions of devices, ranging from low-end MIPS routers to high-end servers, have deployed kcp-go-powered programs in various applications, including online games, live broadcasting, file synchronization, and network acceleration.
Features
- Designed for latency-sensitive scenarios.
- Cache-friendly and memory-optimized design, offering extremely high performance core.
- Handles >5K concurrent connections on a single commodity server.
- Compatible with net.Conn and net.Listener, serving as a drop-in replacement for net.TCPConn.
- FEC (Forward Error Correction) support with Reed-Solomon Codes.
- Packet-level encryption support with AES, TEA, 3DES, Blowfish, Cast5, Salsa20, etc., in CFB mode, generating completely anonymous packets.
- Only a fixed number of goroutines are created for the entire server application, with costs in context switching between goroutines taken into consideration.
- Compatible with skywind3000's C version with various improvements.
- Platform-dependent optimizations: sendmmsg and recvmmsg exploited for Linux.
Documentation
For complete documentation, see the associated Godoc.
Specification
NONCE:
16bytes cryptographically secure random number, nonce changes for every packet.
CRC32:
CRC-32 checksum of data using the IEEE polynomial
FEC TYPE:
typeData = 0xF1
typeParity = 0xF2
FEC SEQID:
monotonically increasing in range: [0, (0xffffffff/shardSize) * shardSize - 1]
SIZE:
The size of KCP frame plus 2
KCP Header
+------------------+
| conv uint32 |
+------------------+
| cmd uint8 |
+------------------+
| frg uint8 |
+------------------+
| wnd uint16 |
+------------------+
| ts uint32 |
+------------------+
| sn uint32 |
+------------------+
| una uint32 |
+------------------+
| rto uint32 |
+------------------+
| xmit uint32 |
+------------------+
| resendts uint32 |
+------------------+
| fastack uint32 |
+------------------+
| acked uint32 |
+------------------+
| data []byte |
+------------------+Layer-Model of KCP-GO
+-----------------+
| SESSION |
+-----------------+
| KCP(ARQ) |
+-----------------+
| FEC(OPTIONAL) |
+-----------------+
| CRYPTO(OPTIONAL)|
+-----------------+
| UDP(PACKET) |
+-----------------+
| IP |
+-----------------+
| LINK |
+-----------------+
| PHY |
+-----------------+Looing for a C++ client?
- https://github.com/xtaci/libkcp -- FEC enhanced KCP session library for iOS/Android in C++
Examples
Benchmark
===
Model Name: MacBook Pro
Model Identifier: MacBookPro14,1
Processor Name: Intel Core i5
Processor Speed: 3.1 GHz
Number of Processors: 1
Total Number of Cores: 2
L2 Cache (per Core): 256 KB
L3 Cache: 4 MB
Memory: 8 GB
===
$ go test -v -run=^$ -bench .
beginning tests, encryption:salsa20, fec:10/3
goos: darwin
goarch: amd64
pkg: github.com/xtaci/kcp-go
BenchmarkSM4-4 50000 32180 ns/op 93.23 MB/s 0 B/op 0 allocs/op
BenchmarkAES128-4 500000 3285 ns/op 913.21 MB/s 0 B/op 0 allocs/op
BenchmarkAES192-4 300000 3623 ns/op 827.85 MB/s 0 B/op 0 allocs/op
BenchmarkAES256-4 300000 3874 ns/op 774.20 MB/s 0 B/op 0 allocs/op
BenchmarkTEA-4 100000 15384 ns/op 195.00 MB/s 0 B/op 0 allocs/op
BenchmarkXOR-4 20000000 89.9 ns/op 33372.00 MB/s 0 B/op 0 allocs/op
BenchmarkBlowfish-4 50000 26927 ns/op 111.41 MB/s 0 B/op 0 allocs/op
BenchmarkNone-4 30000000 45.7 ns/op 65597.94 MB/s 0 B/op 0 allocs/op
BenchmarkCast5-4 50000 34258 ns/op 87.57 MB/s 0 B/op 0 allocs/op
Benchmark3DES-4 10000 117149 ns/op 25.61 MB/s 0 B/op 0 allocs/op
BenchmarkTwofish-4 50000 33538 ns/op 89.45 MB/s 0 B/op 0 allocs/op
BenchmarkXTEA-4 30000 45666 ns/op 65.69 MB/s 0 B/op 0 allocs/op
BenchmarkSalsa20-4 500000 3308 ns/op 906.76 MB/s 0 B/op 0 allocs/op
BenchmarkCRC32-4 20000000 65.2 ns/op 15712.43 MB/s
BenchmarkCsprngSystem-4 1000000 1150 ns/op 13.91 MB/s
BenchmarkCsprngMD5-4 10000000 145 ns/op 110.26 MB/s
BenchmarkCsprngSHA1-4 10000000 158 ns/op 126.54 MB/s
BenchmarkCsprngNonceMD5-4 10000000 153 ns/op 104.22 MB/s
BenchmarkCsprngNonceAES128-4 100000000 19.1 ns/op 837.81 MB/s
BenchmarkFECDecode-4 1000000 1119 ns/op 1339.61 MB/s 1606 B/op 2 allocs/op
BenchmarkFECEncode-4 2000000 832 ns/op 1801.83 MB/s 17 B/op 0 allocs/op
BenchmarkFlush-4 5000000 272 ns/op 0 B/op 0 allocs/op
BenchmarkEchoSpeed4K-4 5000 259617 ns/op 15.78 MB/s 5451 B/op 149 allocs/op
BenchmarkEchoSpeed64K-4 1000 1706084 ns/op 38.41 MB/s 56002 B/op 1604 allocs/op
BenchmarkEchoSpeed512K-4 100 14345505 ns/op 36.55 MB/s 482597 B/op 13045 allocs/op
BenchmarkEchoSpeed1M-4 30 34859104 ns/op 30.08 MB/s 1143773 B/op 27186 allocs/op
BenchmarkSinkSpeed4K-4 50000 31369 ns/op 130.57 MB/s 1566 B/op 30 allocs/op
BenchmarkSinkSpeed64K-4 5000 329065 ns/op 199.16 MB/s 21529 B/op 453 allocs/op
BenchmarkSinkSpeed256K-4 500 2373354 ns/op 220.91 MB/s 166332 B/op 3554 allocs/op
BenchmarkSinkSpeed1M-4 300 5117927 ns/op 204.88 MB/s 310378 B/op 6988 allocs/op
PASS
ok github.com/xtaci/kcp-go 50.349s=== Raspberry Pi 4 ===
➜ kcp-go git:(master) cat /proc/cpuinfo
processor : 0
model name : ARMv7 Processor rev 3 (v7l)
BogoMIPS : 108.00
Features : half thumb fastmult vfp edsp neon vfpv3 tls vfpv4 idiva idivt vfpd32 lpae evtstrm crc32
CPU implementer : 0x41
CPU architecture: 7
CPU variant : 0x0
CPU part : 0xd08
CPU revision : 3
➜ kcp-go git:(master) go test -run=^$ -bench .
2020/01/05 19:25:13 beginning tests, encryption:salsa20, fec:10/3
goos: linux
goarch: arm
pkg: github.com/xtaci/kcp-go/v5
BenchmarkSM4-4 20000 86475 ns/op 34.69 MB/s 0 B/op 0 allocs/op
BenchmarkAES128-4 20000 62254 ns/op 48.19 MB/s 0 B/op 0 allocs/op
BenchmarkAES192-4 20000 71802 ns/op 41.78 MB/s 0 B/op 0 allocs/op
BenchmarkAES256-4 20000 80570 ns/op 37.23 MB/s 0 B/op 0 allocs/op
BenchmarkTEA-4 50000 37343 ns/op 80.34 MB/s 0 B/op 0 allocs/op
BenchmarkXOR-4 100000 22266 ns/op 134.73 MB/s 0 B/op 0 allocs/op
BenchmarkBlowfish-4 20000 66123 ns/op 45.37 MB/s 0 B/op 0 allocs/op
BenchmarkNone-4 3000000 518 ns/op 5786.77 MB/s 0 B/op 0 allocs/op
BenchmarkCast5-4 20000 76705 ns/op 39.11 MB/s 0 B/op 0 allocs/op
Benchmark3DES-4 5000 418868 ns/op 7.16 MB/s 0 B/op 0 allocs/op
BenchmarkTwofish-4 5000 326896 ns/op 9.18 MB/s 0 B/op 0 allocs/op
BenchmarkXTEA-4 10000 114418 ns/op 26.22 MB/s 0 B/op 0 allocs/op
BenchmarkSalsa20-4 50000 36736 ns/op 81.66 MB/s 0 B/op 0 allocs/op
BenchmarkCRC32-4 1000000 1735 ns/op 589.98 MB/s
BenchmarkCsprngSystem-4 1000000 2179 ns/op 7.34 MB/s
BenchmarkCsprngMD5-4 2000000 811 ns/op 19.71 MB/s
BenchmarkCsprngSHA1-4 2000000 862 ns/op 23.19 MB/s
BenchmarkCsprngNonceMD5-4 2000000 878 ns/op 18.22 MB/s
BenchmarkCsprngNonceAES128-4 5000000 326 ns/op 48.97 MB/s
BenchmarkFECDecode-4 200000 9081 ns/op 165.16 MB/s 140 B/op 1 allocs/op
BenchmarkFECEncode-4 100000 12039 ns/op 124.59 MB/s 11 B/op 0 allocs/op
BenchmarkFlush-4 100000 21704 ns/op 0 B/op 0 allocs/op
BenchmarkEchoSpeed4K-4 2000 981182 ns/op 4.17 MB/s 12384 B/op 424 allocs/op
BenchmarkEchoSpeed64K-4 100 10503324 ns/op 6.24 MB/s 123616 B/op 3779 allocs/op
BenchmarkEchoSpeed512K-4 20 138633802 ns/op 3.78 MB/s 1606584 B/op 29233 allocs/op
BenchmarkEchoSpeed1M-4 5 372903568 ns/op 2.81 MB/s 4080504 B/op 63600 allocs/op
BenchmarkSinkSpeed4K-4 10000 121239 ns/op 33.78 MB/s 4647 B/op 104 allocs/op
BenchmarkSinkSpeed64K-4 1000 1587906 ns/op 41.27 MB/s 50914 B/op 1115 allocs/op
BenchmarkSinkSpeed256K-4 100 16277830 ns/op 32.21 MB/s 453027 B/op 9296 allocs/op
BenchmarkSinkSpeed1M-4 100 31040703 ns/op 33.78 MB/s 898097 B/op 18932 allocs/op
PASS
ok github.com/xtaci/kcp-go/v5 64.151sTypical Flame Graph
Key Design Considerations
1. Slice vs. Container/List
kcp.flush() loops through the send queue for retransmission checking every 20 ms.
I wrote a benchmark comparing sequential loops through a slice and a container/list here:
BenchmarkLoopSlice-4 2000000000 0.39 ns/op
BenchmarkLoopList-4 100000000 54.6 ns/opThe list structure introduces heavy cache misses compared to the slice, which has better locality. For 5,000 connections with a 32-window size and a 20 ms interval, using a slice costs 6 μs (0.03% CPU) per kcp.flush(), while using a list costs 8.7 ms (43.5% CPU).
2. Timing Accuracy vs. Syscall clock_gettime
Timing is critical to the RTT estimator. Inaccurate timing leads to false retransmissions in KCP, but calling time.Now() costs 42 cycles (10.5 ns on a 4 GHz CPU, 15.6 ns on my MacBook Pro 2.7 GHz).
The benchmark for time.Now() is here:
BenchmarkNow-4 100000000 15.6 ns/opIn kcp-go, after each kcp.output() function call, the current clock time is updated upon return. For a single kcp.flush() operation, the current time is queried from the system once. For 5,000 connections, this costs 5000 * 15.6 ns = 78 μs (a fixed cost when no packet needs to be sent). For 10 MB/s data transfer with a 1400 MTU, kcp.output() is called around 7500 times, costing 117 μs for time.Now() every second.
3. Memory Management
Primary memory allocation is done from a global buffer pool, xmit.Buf. In kcp-go, when we need to allocate some bytes, we get them from that pool, which returns a fixed-capacity 1500 bytes (mtuLimit). The rx queue, tx queue, and fec queue all receive bytes from this pool and return them after use to prevent unnecessary zeroing of bytes. The pool mechanism maintains a high watermark for slice objects, allowing these in-flight objects to survive periodic garbage collection, while also being able to return memory to the runtime when idle.
4. Information Security
kcp-go is shipped with built-in packet encryption powered by various block encryption algorithms and works in Cipher Feedback Mode. For each packet to be sent, the encryption process starts by encrypting a nonce from the system entropy, ensuring that encryption of the same plaintext never results in the same ciphertext.
The contents of the packets are completely anonymous with encryption, including the headers (FEC, KCP), checksums, and contents. Note that no matter which encryption method you choose at the upper layer, if you disable encryption, the transmission will be insecure, as the header is plaintext and susceptible to tampering, such as jamming the sliding window size, round-trip time, FEC properties, and checksums. AES-128 is suggested for minimal encryption, as modern CPUs come with AES-NI instructions and perform better than salsa20 (check the table above).
Other possible attacks on kcp-go include:
- Traffic analysis: Data flow on specific websites may have patterns while exchanging data. This type of eavesdropping has been mitigated by adopting smux to mix data streams and introduce noise. A perfect solution has not yet appeared, but theoretically, shuffling/mixing messages on a larger scale network may mitigate this problem.
- Replay attack: Since asymmetrical encryption has not been introduced into kcp-go, capturing packets and replaying them on a different machine is possible. Note that hijacking the session and decrypting the contents is still impossible. Upper layers should use an asymmetrical encryption system to guarantee the authenticity of each message (to process each message exactly once), such as HTTPS/OpenSSL/LibreSSL. Signing requests with private keys can eliminate this type of attack.
Connection Termination
Control messages like SYN/FIN/RST in TCP are not defined in KCP. You need a keepalive/heartbeat mechanism at the application level. A real-world example is to use a multiplexing protocol over the session, such as smux (which has an embedded keepalive mechanism). See kcptun for an example.
FAQ
Q: I'm handling >5K connections on my server, and the CPU utilization is so high.
A: A standalone agent or gate server for running kcp-go is suggested, not only to reduce CPU utilization but also to improve the precision of RTT measurements (timing), which indirectly affects retransmission. Increasing the update interval with SetNoDelay, such as conn.SetNoDelay(1, 40, 1, 1), will dramatically reduce system load but may lower performance.
Q: When should I enable FEC?
A: Forward error correction is critical for long-distance transmission because packet loss incurs a huge time penalty. In the complex packet routing networks of the modern world, round-trip time-based loss checks are not always efficient. The significant deviation of RTT samples over long distances usually leads to a larger RTO value in typical RTT estimators, which slows down the transmission.
Q: Should I enable encryption?
A: Yes, for the security of the protocol, even if the upper layer has encryption.
Who is using this?
- https://github.com/xtaci/kcptun -- A Secure Tunnel Based On KCP over UDP.
- https://github.com/getlantern/lantern -- Lantern delivers fast access to the open Internet.
- https://github.com/smallnest/rpcx -- A RPC service framework based on net/rpc like alibaba Dubbo and weibo Motan.
- https://github.com/gonet2/agent -- A gateway for games with stream multiplexing.
- https://github.com/syncthing/syncthing -- Open Source Continuous File Synchronization.
Links
- https://github.com/xtaci/smux/ -- A Stream Multiplexing Library for golang with least memory
- https://github.com/xtaci/libkcp -- FEC enhanced KCP session library for iOS/Android in C++
- https://github.com/skywind3000/kcp -- A Fast and Reliable ARQ Protocol
- https://github.com/klauspost/reedsolomon -- Reed-Solomon Erasure Coding in Go