负载均衡5中算法是如何实现的？

负载均衡算法是现代计算技术中的关键部分，用于在多个服务器或资源之间分配请求，以提高系统的性能和稳定性，以下是五种常见的负载均衡算法及其实现：

随机算法（Random）

随机算法通过系统随机函数，根据后台服务器的地址随机选取其中一台服务器进行访问，随着调用量的增加，最终的访问趋于平均，达到均衡的目的。

import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Random;
public class RandomLoadBalancer {
    private final Map<String, Integer> serverWeights = new HashMap<>();
    private final List<String> servers = new ArrayList<>();
    public RandomLoadBalancer() {
        // 初始化服务器权重
        serverWeights.put("192.168.13.1", 1);
        serverWeights.put("192.168.13.2", 2);
        serverWeights.put("192.168.13.3", 4);
    }
    public String getServer() {
        List<String> weightedServers = new ArrayList<>(serverWeights.keySet());
        int totalWeight = weightedServers.stream().mapToInt(server -> serverWeights.get(server)).sum();
        Random random = new Random();
        int index = random.nextInt(totalWeight);
        int sum = 0;
        for (String server : weightedServers) {
            sum += serverWeights.get(server);
            if (index < sum) {
                return server;
            }
        }
        return null; // 应该不会到这里
    }
    public static void main(String[] args) {
        RandomLoadBalancer balancer = new RandomLoadBalancer();
        for (int i = 0; i < 10; i++) {
            String server = balancer.getServer();
            System.out.println("Selected server: " + server);
        }
    }
}

轮询算法（Round Robin）

轮询算法按照顺序循环将请求分配到每台服务器上，简单易实现，适用于服务器性能相近的情况。

import java.util.*;
public class RoundRobinLoadBalancer {
    private final List<String> servers = new ArrayList<>();
    private int currentIndex = 0;
    public RoundRobinLoadBalancer() {
        // 初始化服务器列表
        servers.add("192.168.13.1");
        servers.add("192.168.13.2");
        servers.add("192.168.13.3");
    }
    public String getNextServer() {
        String server = servers.get(currentIndex);
        currentIndex = (currentIndex + 1) % servers.size();
        return server;
    }
    public static void main(String[] args) {
        RoundRobinLoadBalancer balancer = new RoundRobinLoadBalancer();
        for (int i = 0; i < 10; i++) {
            String server = balancer.getNextServer();
            System.out.println("Selected server: " + server);
        }
    }
}

加权轮询算法（Weighted Round Robin）

加权轮询算法在轮询的基础上引入权重，使得高性能服务器可以承担更多请求。

import java.util.*;
public class WeightedRoundRobinLoadBalancer {
    private final List<Node> nodes = new ArrayList<>();
    private int currentIndex = -1;
    private int currentWeight = 0;
    private int totalWeight = 0;
    static class Node {
        String address;
        int weight;
        int effectiveWeight;
        int currentWeight;
        Node(String address, int weight) {
            this.address = address;
            this.weight = weight;
            this.effectiveWeight = weight;
            this.currentWeight = 0;
        }
    }
    public WeightedRoundRobinLoadBalancer(Map<String, Integer> weights) {
        for (Map.Entry<String, Integer> entry : weights.entrySet()) {
            nodes.add(new Node(entry.getKey(), entry.getValue()));
            totalWeight += entry.getValue();
        }
    }
    public String getServer() {
        while (true) {
            currentIndex = (currentIndex + 1) % nodes.size();
            Node node = nodes.get(currentIndex);
            node.currentWeight += node.effectiveWeight;
            if (node.currentWeight > totalWeight) {
                node.currentWeight -= totalWeight;
                totalWeight = nodes.stream().mapToInt(n -> n.effectiveWeight).sum();
                return node.address;
            }
        }
    }
    public static void main(String[] args) {
        Map<String, Integer> weights = new HashMap<>();
        weights.put("192.168.13.1", 5);
        weights.put("192.168.13.2", 1);
        weights.put("192.168.13.3", 1);
        WeightedRoundRobinLoadBalancer balancer = new WeightedRoundRobinLoadBalancer(weights);
        for (int i = 0; i < 10; i++) {
            String server = balancer.getServer();
            System.out.println("Selected server: " + server);
        }
    }
}

IP-Hash算法（IP_HASH）

IP-Hash算法通过对用户请求的IP地址进行哈希运算，将请求分配到固定的服务器上，保证同一用户请求总是由同一台服务器处理。

import java.util.*;
import java.net.*;
import java.security.MessageDigest;
import java.security.NoSuchAlgorithmException;
import java.math.BigInteger;
public class IpHASHLoadBalancer {
    private final Map<String, String> serverMap = new HashMap<>();
    private final List<String> servers = new ArrayList<>();
    public IpHASHLoadBalancer() {
        // 初始化服务器列表和映射关系
        servers.add("192.168.13.1");
        servers.add("192.168.13.2");
        servers.add("192.168.13.3");
        for (String server : servers) {
            serverMap.put(hashIP(server), server);
        }
    }
    public String hashIP(String ip) {
        try {
            MessageDigest md = MessageDigest.getInstance("MD5");
            BigInteger hash = new BigInteger(1, md.digest(ip.getBytes()));
            return String.valueOf(hash);
        } catch (NoSuchAlgorithmException e) {
            throw new RuntimeException(e);
        }
    }
    public String getServer(String clientIp) {
        String hashedIp = hashIP(clientIp);
        return serverMap.getOrDefault(hashedIp, null); // 默认返回null，表示没有找到对应的服务器
    }
    public static void main(String[] args) throws UnknownHostException {
        IpHASHLoadBalancer balancer = new IpHASHLoadBalancer();
        String clientIp = InetAddress.getLocalHost().getHostAddress(); // 模拟客户端IP地址
        for (int i = 0; i < 10; i++) {
            String server = balancer.getServer(clientIp);
            System.out.println("Selected server for client IP " + clientIp + ": " + server);
        }
    }
}

最小连接数算法（Least Connections）

最小连接数算法将新的请求发送到当前连接数最少的服务器，动态调整以适应实际负载。

import java.util.*;
import java.util.concurrent.atomic.AtomicInteger;
public class LeastConnectionsLoadBalancer {
    private final List<String> servers = new ArrayList<>();
    private final Map<String, AtomicInteger> connectionCounts = new ConcurrentHashMap<>();
    private final Object lock = new Object(); // 锁对象，用于确保线程安全
    public LeastConnectionsLoadBalancer() {
        // 初始化服务器列表和连接计数器
        servers.add("192.168.13.1");
        servers.add("192.168.13.2");
        servers.add("192.168.13.3");
        for (String server : servers) {
            connectionCounts.put(server, new AtomicInteger(0));
        }
    }
    public String getServer() {
        synchronized (lock) { // 确保线程安全
            String selectedServer = null;
            int minConnections = Integer.MAX_VALUE;
            for (String server : servers) {
                int currentConnections = connectionCounts.get(server).get();
                if (currentConnections < minConnections) {
                    minConnections = currentConnections;
                    selectedServer = server;
                }
            }
            if (selectedServer != null) {
                connectionCounts.get(selectedServer).incrementAndGet(); // 增加选中服务器的连接数
            }
            return selectedServer;
        }
    }
    public void releaseServer(String server) {
        synchronized (lock) { // 确保线程安全
            if (server != null && connectionCounts.containsKey(server)) {
                connectionCounts.get(server).decrementAndGet(); // 减少服务器的连接数
            }
        }
    }
    public static void main(String[] args) {
        LeastConnectionsLoadBalancer balancer = new LeastConnectionsLoadBalancer();
        for (int i = 0; i < 10; i++) {
            String server = balancer.getServer();
            System.out.println("Selected server: " + server);
            balancer.releaseServer(server); // 假设每次请求结束后释放连接数，实际应用中需要更复杂的管理机制
        }
    }
}

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