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整理SRv6Router代码，修bug，增加SRHInsert虚链路

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This commit is contained in:
KNEMC
2026-08-31 19:07:53 +08:00
parent 52f44335e4
commit 2c111770b3
17 changed files with 287 additions and 190 deletions
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src/org/kne/cloud/network/congestion/BBRCongestionAlgorithm.java
+15
View File
@@ -136,4 +136,19 @@ public class BBRCongestionAlgorithm implements CongestionAlgorithm ,DetnetConges
return "BBR";
}
@Override
public double getUpperDelayBound() {
return MAX_GAIN;
}
@Override
public double getLowerDelayBound() {
return MIN_GAIN;
}
@Override
public double getBurstLimit() {
return burstLimit;
}
}
src/org/kne/cloud/network/congestion/DCTCPCongestionAlgorithm.java
+1 -1
View File
@@ -88,7 +88,7 @@ public class DCTCPCongestionAlgorithm implements CongestionAlgorithm {
}
}else {
if(windowUsed*3L>=congressWindowSize) {
congressWindowSize+=4000;
congressWindowSize+=4096;
updateWindowSize();
}
}
src/org/kne/cloud/network/congestion/DetnetCongestionAlgorithm.java
+3
View File
@@ -4,4 +4,7 @@ public interface DetnetCongestionAlgorithm extends CongestionAlgorithm {
public void setUpperDelayBound(double upper);
public void setLowerDelayBound(double lower);
public void setBurstLimit(double limit);
public double getUpperDelayBound( );
public double getLowerDelayBound();
public double getBurstLimit();
}
src/org/kne/cloud/network/congestion/Vegas2CongestionAlgorithm.java
+37 -112
View File
@@ -2,6 +2,8 @@ package org.kne.cloud.network.congestion;
import java.util.function.Consumer;
import org.kne.cloud.network.monitor.DelaySampler;
public class Vegas2CongestionAlgorithm implements CongestionAlgorithm,DetnetCongestionAlgorithm {
// 可配置的时延膨胀比上下限 - Vegas2.0核心参数
@@ -17,6 +19,7 @@ public class Vegas2CongestionAlgorithm implements CongestionAlgorithm,DetnetCong
private Consumer<Long> windowControlConsumer;
private long MIN_RTTVAR = 30000000L;
private volatile long RTTCurr = 1000000000L; // RTT
private volatile long RTTMin = 1000000000L; // BaseRTT
private volatile long RTTVar = 1000000000L;
private volatile long RTTAvg = 1000000000L;
@@ -25,11 +28,6 @@ public class Vegas2CongestionAlgorithm implements CongestionAlgorithm,DetnetCong
private volatile long RTTCount = 0;
private volatile long RTO = 1000000000L;
private volatile long OWDTotal = 0;
private volatile long OWDCount = 0;
private volatile long OWDAvg2 = 1000000000L; // 当前平滑OWD
private volatile long OWDMin = 1000000000L; // BaseRTT
private volatile long window = MIN_WINDOW;
private volatile long window2 = MIN_WINDOW;
@@ -58,106 +56,14 @@ public class Vegas2CongestionAlgorithm implements CongestionAlgorithm,DetnetCong
@Override
public void putAck(long packetSize, long RTTns, long OWDup, boolean ecn) {
if(RTTns<0) {
throw new IllegalArgumentException("RTT:"+ RTTns+" is negative!");
}
// 处理ECN信号 - 将其视为强烈的拥塞信号
if (ecn) {
// 当收到ECN时，更激进地减少窗口
window2 = Math.max(0, window2 * 3 / 4);
if (windowControlConsumer != null) {
windowControlConsumer.accept(window2);
}
}
// 更新最小RTT（BaseRTT）
if (RTTns <= RTTMin) {
RTTMin = RTTns;
} else {
// 缓慢适应：当网络路径真正变化时，BaseRTT应能缓慢更新
// 这里使用极慢的衰减因子，只有在持续观测到更低RTT时才快速更新
RTTMin = (RTTMin * 999 + RTTns) / 1000;
}
// 更新最小OWD（BaseOWD）
if (OWDup <= OWDMin) {
OWDMin = OWDup;
} else {
// 缓慢适应：当网络路径真正变化时，BaseRTT应能缓慢更新
// 这里使用极慢的衰减因子，只有在持续观测到更低RTT时才快速更新
OWDMin = (OWDMin * 999 + OWDup) / 1000;
}
// 更新平滑RTT估计
RTTVar = (RTTVar * 3 + Math.abs(RTTAvg - RTTns)) / 4;
RTTAvg = (RTTAvg * 7 + RTTns) / 8;
RTO = RTTAvg + Math.max(MIN_RTTVAR, RTTVar * 4);
RTTTotal += RTTns;
RTTCount++;
OWDTotal += OWDup;
OWDCount++;
long curr = System.nanoTime();
// 每个RTT周期调整一次窗口（使用当前估计的RTT）
if (curr - RTTstartTime > Math.max(BIAS, 2*RTTMin)) {
long RTTCountx=RTTCount;
if (RTTCountx > 0) {
long currentRTT = RTTTotal / RTTCountx;
//RTTAvg2 = (RTTAvg2 * 3 + currentRTT) / 4; // 平滑当前RTT
RTTAvg2=currentRTT;
RTTTotal = 0;
RTTCount = 0;
}
long OWDCountx=OWDCount;
if (OWDCountx > 0) {
long currentOWD = OWDTotal / OWDCountx;
OWDAvg2=currentOWD;
OWDTotal = 0;
OWDCount = 0;
}
// ================== Vegas2.0核心逻辑 ==================
// 1. 计算时延膨胀比
double delayRatio = (double) OWDAvg2 / (double) Math.max(BIAS, OWDMin);
//System.out.println(delayRatio+" "+RTTAvg2/1000000.0+" "+RTTMin/1000000.0);
// 2. 基于比值的窗口调整（取代原来的基于差值的调整）
if (delayRatio > delayUpperBound) {
// 时延过高：减小窗口，减少幅度与超标程度成正比
window2 -= 4096;
} else if (delayRatio < delayLowerBound) {
// 时延过低：增大窗口，增加幅度与低于目标程度成正比
window2 += 4096;
} else {
}
// ===================================================
updateWindowSize();
RTTstartTime = curr;
}
}
private DelaySampler dsp=new DelaySampler();
@Override
public void putAck(long packetSize, long RTTns, boolean ecn) {
if(RTTns<0) {
throw new IllegalArgumentException("RTT:"+ RTTns+" is negative!");
}
this.RTTCurr=RTTns;
// 处理ECN信号 - 将其视为强烈的拥塞信号
if (ecn) {
// 当收到ECN时，更激进地减少窗口
@@ -167,14 +73,7 @@ public class Vegas2CongestionAlgorithm implements CongestionAlgorithm,DetnetCong
}
}
// 更新最小RTT（BaseRTT）
if (RTTns <= RTTMin) {
RTTMin = RTTns;
} else {
// 缓慢适应：当网络路径真正变化时，BaseRTT应能缓慢更新
// 这里使用极慢的衰减因子，只有在持续观测到更低RTT时才快速更新
RTTMin = (RTTMin * 999 + RTTns) / 1000;
}
dsp.recordDelay(RTTns);
// 更新平滑RTT估计
@@ -190,6 +89,15 @@ public class Vegas2CongestionAlgorithm implements CongestionAlgorithm,DetnetCong
long curr = System.nanoTime();
// 每个RTT周期调整一次窗口（使用当前估计的RTT）
if (curr - RTTstartTime > Math.max(BIAS, 2*RTTMin)) {
dsp.update();
long rmin=dsp.getMinDelayNanos();
if(rmin<=RTTMin) {
RTTMin=rmin;
}else {
RTTMin=Math.min(rmin, RTTMin+1000);
}
long RTTCountx=RTTCount;
if (RTTCountx > 0) {
long currentRTT = RTTTotal / RTTCountx;
@@ -206,12 +114,12 @@ public class Vegas2CongestionAlgorithm implements CongestionAlgorithm,DetnetCong
// 2. 基于比值的窗口调整（取代原来的基于差值的调整）
if (delayRatio > delayUpperBound) {
// 时延过高：减小窗口，减少幅度与超标程度成正比
window2 -= 4096;
window2 =window2-4096;
} else if (delayRatio < delayLowerBound) {
// 时延过低：增大窗口，增加幅度与低于目标程度成正比
window2 += 4096;
window2 =window2+4096;
} else {
//window2=window2+4096
}
// ===================================================
@@ -271,10 +179,12 @@ public class Vegas2CongestionAlgorithm implements CongestionAlgorithm,DetnetCong
public long getBaseRTT() {
return RTTMin;
}
public long getCurrentRTT() {
public long getAvgRTT() {
return RTTAvg2;
}
public long getCurrentRTT() {
return RTTCurr;
}
@Override
public void setUpperDelayBound(double upper) {
@@ -295,4 +205,19 @@ public class Vegas2CongestionAlgorithm implements CongestionAlgorithm,DetnetCong
return "Vegas2";
}
@Override
public double getUpperDelayBound() {
return delayUpperBound;
}
@Override
public double getLowerDelayBound() {
return delayLowerBound;
}
@Override
public double getBurstLimit() {
return burstLimit;
}
}