Max-Min Fairness带宽分配算法

最近再写一个网络仿真器，里面参考了Max-MinFairness算法，这是一种比较理想、公平的带宽分配算法。其思路主要如下：首先是算法的准备，考察某一时刻的网络中所有的flow，由于每条flow都有其各个link，因此可以得到各个link上所有流经的flow，然后开始迭代，各个link都把capacity平均分给所有流经的flow，接着每条flow的速度就等于其最小link分配的带宽，然后每条link的剩余带宽就等于link的capacity减去所有流经的flow的速度的总和，再然后把link的剩余带宽作为capacity重新进行上面的迭代，直至所有flow在迭代中获得的带宽都小于一个阈值时，算法结束，带宽分配完成。

让我们来分析这个算法并考虑如何加速该算法的执行速度。首先，对于一些bottleneck的link，流经其的flow早早就不能分配带宽了，因此如果发现在某个迭代中某条link能够分配的带宽已经小于阈值，那么在下一轮迭代，所有流经其的flow都不再考察，即使某些flow并不是以该link为bottleneck，因此，算法结束的条件可以改为当所有flow都不再考察的时候。这样对不对呢，让我们分析一下。以该link为bottleneck的flow自然不用说了，所谓的bottleneck就是能够获取的带宽最小的link，那么最小的link已经不能分配带宽了，该flow自然不再考察。但不是以该link作为bottleneck的flow呢，它们有更小带宽的link，但是如果该link不是你的bottleneck，已经不能分配带宽了，那就刚不用说更小带宽的link了，所以这些flow也应该不再考察。好，算法的讲解和分析就到这儿了，下面就是算法的实现，笔者采用的Java语言。

public Map<Integer, List<TrafficState>> run() {
		Map<Integer, List<TrafficState>> resultMap = new HashMap<Integer, List<TrafficState>>();
		int current = 0;
		// PrintWriter resultWriter = new PrintWriter(resultFileName);
		while (current < runtime) {
			List<Integer> runningFlowList = new ArrayList<Integer>();
			// the first traverse,add the new flows and remove the shopped flow
			for (int i = 0; i < graph.traffics.size(); i++) {
				Traffic currentTraffic = graph.traffics.get(i);
				int starttime = currentTraffic.start;
				if (starttime <= current && !currentTraffic.isStopped) {
					List<Integer> linksList = currentTraffic.links;
					if (currentTraffic.totlesize == 0) {
						// start a new flow
						currentTraffic.totlesize = currentTraffic.flowsize;
						currentTraffic.leftsize = currentTraffic.totlesize;
						for (Integer linkno : linksList) {
							graph.links.get(linkno).trafficList
									.add(currentTraffic);
						}
					}
					// calculate the transfer bytes in a epoch
					currentTraffic.epochsize = currentTraffic.speed
							* ((float) period / 1000);
					currentTraffic.leftsize -= currentTraffic.epochsize;

					if (currentTraffic.leftsize <= 0
							|| currentTraffic.end == current) {
						// no more flowsize or time is up,stop it
						currentTraffic.isStopped = true;
						for (Integer linkno : linksList) {
							graph.links.get(linkno).trafficList
									.remove(currentTraffic);
						}
					} else
						runningFlowList.add(i);
				}
			}
			// print the measurement
			if (printTimeSet.contains(current)) {
				List<TrafficState> stateList = new ArrayList<TrafficState>();
				for (Traffic traffic : graph.traffics) {
					//not the stop flows and the start ones just now
					if (!traffic.isStopped && traffic.totlesize != 0
							&& traffic.speed != 0) {
						TrafficState state = new TrafficState();
						state.setBytes(traffic.epochsize);
						state.setDestination(traffic.destination);
						state.setSource(traffic.source);
						state.setThruput(traffic.speed);
						String pathString = traffic.source;
						int lastNode = Integer.parseInt(traffic.source);
						for (Integer linkno : traffic.links) {
							if (lastNode == graph.links.get(linkno).source) {
								pathString += ","
										+ graph.links.get(linkno).target;
								lastNode = graph.links.get(linkno).target;
							} else {
								pathString += ","
										+ graph.links.get(linkno).source;
								lastNode = graph.links.get(linkno).source;
							}
							// pathString += "," +
							// graph.links.get(linkno).target;
						}
						state.setPathString(pathString);
						state.setStarttime(traffic.start);
						state.setFlowsize(traffic.flowsize);
						state.setEndtime(traffic.end);
						stateList.add(state);
					}
				}
				resultMap.put(current, stateList);
			}
			// initialize all the links and traffics
			for (Link link : graph.links) {
				link.leftCapacity = link.capacity;
			}
			for (Traffic traffic : graph.traffics) {
				traffic.speed = 0;
			}
			Set<Integer> finishedTrafficSet = new HashSet<Integer>();
			// the second traverse,set the throughput of each flow in next
			// iteration
			while (finishedTrafficSet.size() < runningFlowList.size()) {
				for (int i = 0; i < runningFlowList.size(); i++) {
					if (!finishedTrafficSet.contains(runningFlowList.get(i))) {
						Traffic currentTraffic = graph.traffics
								.get(runningFlowList.get(i));
						currentTraffic.increSpeed = Float.MAX_VALUE;
						Link minLink = null;
						for (Integer linkno : currentTraffic.links) {
							Link currentLink = graph.links.get(linkno);
							int existFlowNum = 0;// the number of exist flows
							for (Traffic traffic : currentLink.trafficList) {
								if (traffic.increSpeed != 0
										|| traffic.speed == 0) {
									existFlowNum++;
								}
							}
							float currentLinkSpeed = (float) currentLink.leftCapacity
									/ (float) existFlowNum;
							if (currentLinkSpeed < currentTraffic.increSpeed) {
								currentTraffic.increSpeed = currentLinkSpeed;
								minLink = currentLink;
							}
						}
						if (currentTraffic.increSpeed > 5)
							currentTraffic.speed += currentTraffic.increSpeed;
						else {
							currentTraffic.increSpeed = 0;
							if (minLink != null) {
								for (Traffic traffic : minLink.trafficList) {
									traffic.increSpeed = 0;
									finishedTrafficSet.add(graph.traffics
											.indexOf(traffic));
								}
							} else
								finishedTrafficSet.add(runningFlowList.get(i));
						}
					}
				}
				// link left capacity decrease the traffic increase throughput
				for (Link link : graph.links) {
					for (Traffic traffic : link.trafficList) {
						link.leftCapacity -= traffic.increSpeed;
					}
				}
			}
			current += period;
		}
		// resultWriter.close();
		return resultMap;
	}

Max-Min Fairness带宽分配算法