贪心算法应用:速率单调调度(RMS)问题详解
Java中的贪心算法应用:速率单调调度(RMS)问题详解
1. 速率单调调度(RMS)概述
速率单调调度(Rate Monotonic Scheduling, RMS)是一种广泛应用于实时系统中的静态优先级调度算法,属于贪心算法在任务调度领域的经典应用。
1.1 基本概念
RMS基于以下原则:
- 每个周期性任务都有一个固定的执行时间©和周期(T)
- 任务的优先级与其周期成反比:周期越短,优先级越高
- 采用抢占式调度方式
1.2 RMS的数学基础
RMS的理论基础是Liu & Layland提出的利用率界限定理:
- 对于n个任务,RMS可调度的充分条件是总利用率U ≤ n(2^(1/n) - 1)
- 当n→∞时,这个界限趋近于ln2 ≈ 0.693
2. RMS问题建模
2.1 任务模型
在Java中,我们可以这样表示一个周期性任务:
class PeriodicTask {private int id; // 任务IDprivate int period; // 周期(ms)private int executionTime; // 执行时间(ms)private int deadline; // 相对截止时间(通常等于period)private int priority; // 优先级// 构造函数public PeriodicTask(int id, int period, int executionTime) {this.id = id;this.period = period;this.executionTime = executionTime;this.deadline = period; // 通常截止时间等于周期this.priority = 1 / period; // 速率单调优先级}// Getters and Setters// ...
}
2.2 调度器模型
class RateMonotonicScheduler {private List<PeriodicTask> taskSet;private int currentTime;private boolean isSchedulable;public RateMonotonicScheduler(List<PeriodicTask> tasks) {this.taskSet = tasks;this.currentTime = 0;// 按照速率单调优先级排序(周期越短优先级越高)Collections.sort(taskSet, Comparator.comparingInt(PeriodicTask::getPeriod));this.isSchedulable = checkSchedulability();}// 检查任务集是否可调度private boolean checkSchedulability() {// 实现将在后面详细讲解}// 执行调度public void schedule() {// 实现将在后面详细讲解}
}
3. RMS可调度性分析
3.1 利用率界限测试
private boolean checkSchedulability() {double totalUtilization = 0.0;for (PeriodicTask task : taskSet) {double utilization = (double) task.getExecutionTime() / task.getPeriod();totalUtilization += utilization;}int n = taskSet.size();double bound = n * (Math.pow(2, 1.0/n) - 1);// 如果总利用率小于界限,则肯定可调度if (totalUtilization <= bound) {return true;}// 否则需要进行时间需求分析return timeDemandAnalysis();
}
3.2 时间需求分析
当利用率超过界限时,需要进行更精确的时间需求分析:
private boolean timeDemandAnalysis() {for (int i = 0; i < taskSet.size(); i++) {PeriodicTask task = taskSet.get(i);boolean found = false;// 检查所有可能的t值for (int t = task.getExecutionTime(); t <= task.getDeadline(); t++) {double demand = calculateTimeDemand(i, t);if (demand <= t) {found = true;break;}}if (!found) {return false;}}return true;
}private double calculateTimeDemand(int taskIndex, int t) {double demand = 0.0;for (int i = 0; i <= taskIndex; i++) {PeriodicTask task = taskSet.get(i);demand += Math.ceil((double)t / task.getPeriod()) * task.getExecutionTime();}return demand;
}
4. RMS调度算法实现
4.1 调度主循环
public void schedule() {if (!isSchedulable) {System.out.println("任务集不可调度!");return;}System.out.println("开始速率单调调度...");// 模拟调度过程int hyperperiod = calculateHyperperiod();for (currentTime = 0; currentTime < hyperperiod; currentTime++) {// 检查是否有任务到达PeriodicTask highestPriorityTask = getHighestPriorityReadyTask();if (highestPriorityTask != null) {executeTask(highestPriorityTask);} else {System.out.println("时间 " + currentTime + "ms: CPU空闲");}}
}
4.2 辅助方法
private int calculateHyperperiod() {int hyperperiod = 1;for (PeriodicTask task : taskSet) {hyperperiod = lcm(hyperperiod, task.getPeriod());}return hyperperiod;
}private int lcm(int a, int b) {return a * (b / gcd(a, b));
}private int gcd(int a, int b) {while (b != 0) {int temp = b;b = a % b;a = temp;}return a;
}private PeriodicTask getHighestPriorityReadyTask() {for (PeriodicTask task : taskSet) {// 检查任务是否到达(时间是否是周期的整数倍)if (currentTime % task.getPeriod() == 0) {return task; // 因为已经按优先级排序,第一个找到的就是最高优先级的}}return null;
}private void executeTask(PeriodicTask task) {System.out.println("时间 " + currentTime + "ms: 执行任务 " + task.getId() + " (周期=" + task.getPeriod() + "ms, 执行时间=" + task.getExecutionTime() + "ms)");// 模拟任务执行int remainingTime = task.getExecutionTime();while (remainingTime > 0 && currentTime < hyperperiod) {remainingTime--;currentTime++;// 检查是否有更高优先级任务到达PeriodicTask higherPriorityTask = checkForHigherPriorityTask(task);if (higherPriorityTask != null) {System.out.println("时间 " + currentTime + "ms: 任务 " + task.getId() + " 被任务 " + higherPriorityTask.getId() + " 抢占");executeTask(higherPriorityTask);}}if (remainingTime == 0) {System.out.println("时间 " + currentTime + "ms: 任务 " + task.getId() + " 完成");}
}private PeriodicTask checkForHigherPriorityTask(PeriodicTask currentTask) {for (PeriodicTask task : taskSet) {if (task.getPeriod() < currentTask.getPeriod() && currentTime % task.getPeriod() == 0) {return task;}}return null;
}
5. 完整示例与测试
5.1 完整RMS调度器实现
import java.util.*;public class RateMonotonicScheduling {public static void main(String[] args) {// 创建任务集List<PeriodicTask> tasks = new ArrayList<>();tasks.add(new PeriodicTask(1, 50, 12)); // 高优先级tasks.add(new PeriodicTask(2, 100, 25)); // 中优先级tasks.add(new PeriodicTask(3, 200, 50)); // 低优先级// 创建调度器RateMonotonicScheduler scheduler = new RateMonotonicScheduler(tasks);// 执行调度scheduler.schedule();}
}class PeriodicTask {private int id;private int period;private int executionTime;private int deadline;public PeriodicTask(int id, int period, int executionTime) {this.id = id;this.period = period;this.executionTime = executionTime;this.deadline = period;}// Getterspublic int getId() { return id; }public int getPeriod() { return period; }public int getExecutionTime() { return executionTime; }public int getDeadline() { return deadline; }
}class RateMonotonicScheduler {private List<PeriodicTask> taskSet;private int currentTime;private boolean isSchedulable;private int hyperperiod;public RateMonotonicScheduler(List<PeriodicTask> tasks) {this.taskSet = new ArrayList<>(tasks);this.currentTime = 0;Collections.sort(taskSet, Comparator.comparingInt(PeriodicTask::getPeriod));this.isSchedulable = checkSchedulability();this.hyperperiod = calculateHyperperiod();}private boolean checkSchedulability() {double totalUtilization = taskSet.stream().mapToDouble(task -> (double)task.getExecutionTime() / task.getPeriod()).sum();int n = taskSet.size();double bound = n * (Math.pow(2, 1.0/n) - 1);System.out.printf("总利用率: %.3f, 界限: %.3f%n", totalUtilization, bound);if (totalUtilization <= bound) {System.out.println("任务集通过利用率界限测试,可调度");return true;}System.out.println("利用率超过界限,进行时间需求分析...");return timeDemandAnalysis();}private boolean timeDemandAnalysis() {for (int i = 0; i < taskSet.size(); i++) {PeriodicTask task = taskSet.get(i);boolean found = false;for (int t = task.getExecutionTime(); t <= task.getDeadline(); t++) {double demand = calculateTimeDemand(i, t);if (demand <= t) {found = true;break;}}if (!found) {System.out.println("任务 " + task.getId() + " 无法满足截止时间要求");return false;}}System.out.println("任务集通过时间需求分析,可调度");return true;}private double calculateTimeDemand(int taskIndex, int t) {double demand = 0.0;for (int i = 0; i <= taskIndex; i++) {PeriodicTask task = taskSet.get(i);demand += Math.ceil((double)t / task.getPeriod()) * task.getExecutionTime();}return demand;}public void schedule() {if (!isSchedulable) {System.out.println("任务集不可调度!");return;}System.out.println("开始速率单调调度...");System.out.println("超周期长度: " + hyperperiod + "ms");for (currentTime = 0; currentTime < hyperperiod; currentTime++) {PeriodicTask highestPriorityTask = getHighestPriorityReadyTask();if (highestPriorityTask != null) {executeTask(highestPriorityTask);} else {System.out.println("时间 " + currentTime + "ms: CPU空闲");}}}private int calculateHyperperiod() {int hyperperiod = 1;for (PeriodicTask task : taskSet) {hyperperiod = lcm(hyperperiod, task.getPeriod());}return hyperperiod;}private int lcm(int a, int b) {return a * (b / gcd(a, b));}private int gcd(int a, int b) {while (b != 0) {int temp = b;b = a % b;a = temp;}return a;}private PeriodicTask getHighestPriorityReadyTask() {for (PeriodicTask task : taskSet) {if (currentTime % task.getPeriod() == 0) {return task;}}return null;}private void executeTask(PeriodicTask task) {System.out.println("时间 " + currentTime + "ms: 执行任务 " + task.getId() + " (周期=" + task.getPeriod() + "ms, 执行时间=" + task.getExecutionTime() + "ms)");int remainingTime = task.getExecutionTime();while (remainingTime > 0 && currentTime < hyperperiod) {remainingTime--;currentTime++;PeriodicTask higherPriorityTask = checkForHigherPriorityTask(task);if (higherPriorityTask != null) {System.out.println("时间 " + currentTime + "ms: 任务 " + task.getId() + " 被任务 " + higherPriorityTask.getId() + " 抢占");executeTask(higherPriorityTask);return;}}if (remainingTime == 0) {System.out.println("时间 " + currentTime + "ms: 任务 " + task.getId() + " 完成");} else {System.out.println("时间 " + currentTime + "ms: 任务 " + task.getId() + " 未完成,剩余时间 " + remainingTime);}}private PeriodicTask checkForHigherPriorityTask(PeriodicTask currentTask) {for (PeriodicTask task : taskSet) {if (task.getPeriod() < currentTask.getPeriod() && currentTime % task.getPeriod() == 0) {return task;}}return null;}
}
5.2 输出示例
运行上述程序,输出可能如下:
总利用率: 0.745, 界限: 0.780
任务集通过利用率界限测试,可调度
开始速率单调调度...
超周期长度: 200ms
时间 0ms: 执行任务 1 (周期=50ms, 执行时间=12ms)
时间 12ms: 任务 1 完成
时间 12ms: CPU空闲
...
时间 50ms: 执行任务 1 (周期=50ms, 执行时间=12ms)
时间 62ms: 任务 1 完成
时间 62ms: CPU空闲
...
6. RMS的优缺点分析
6.1 优点
- 简单高效:优先级分配规则简单,调度开销小
- 最优性:在所有静态优先级调度算法中,RMS对于周期性任务集是最优的
- 可预测性:可以提前进行可调度性分析
- 适合嵌入式系统:实现简单,适合资源受限的实时系统
6.2 缺点
- 利用率限制:最坏情况下CPU利用率不能超过69.3%
- 仅适用于周期性任务:不适合处理非周期性或偶发任务
- 优先级反转问题:高优先级任务可能被低优先级任务阻塞
- 不考虑任务重要性:仅根据周期分配优先级,不考虑任务的实际重要性
7. RMS的扩展与变种
7.1 截止时间单调调度(DMS)
与RMS类似,但优先级根据相对截止时间分配:
// 在PeriodicTask类中添加
public int getRelativeDeadline() {return deadline;
}// 在调度器中使用截止时间排序
Collections.sort(taskSet, Comparator.comparingInt(PeriodicTask::getRelativeDeadline));
7.2 响应时间分析
更精确的可调度性测试方法:
private boolean responseTimeAnalysis() {for (int i = 0; i < taskSet.size(); i++) {PeriodicTask task = taskSet.get(i);int responseTime = calculateResponseTime(i);if (responseTime > task.getDeadline()) {return false;}}return true;
}private int calculateResponseTime(int taskIndex) {PeriodicTask task = taskSet.get(taskIndex);int responseTime = task.getExecutionTime();int prevResponseTime;do {prevResponseTime = responseTime;responseTime = task.getExecutionTime();for (int i = 0; i < taskIndex; i++) {PeriodicTask higherPriorityTask = taskSet.get(i);responseTime += Math.ceil((double)prevResponseTime / higherPriorityTask.getPeriod()) * higherPriorityTask.getExecutionTime();}if (responseTime > task.getDeadline()) {return responseTime; // 已经超过截止时间,无需继续}} while (responseTime != prevResponseTime);return responseTime;
}
8. 实际应用中的考虑
8.1 上下文切换开销
在实际系统中,需要考虑任务切换的开销:
class RateMonotonicScheduler {private final int CONTEXT_SWITCH_TIME = 1; // 假设上下文切换需要1msprivate void executeTask(PeriodicTask task) {// 添加上下文切换时间currentTime += CONTEXT_SWITCH_TIME;System.out.println("时间 " + currentTime + "ms: 上下文切换(1ms)");// ... 原有执行逻辑}
}
8.2 资源共享与优先级继承
处理共享资源时的优先级继承协议:
class SharedResource {private boolean locked = false;private int ceilingPriority = Integer.MAX_VALUE;public synchronized void acquire(int taskPriority) {while (locked && ceilingPriority < taskPriority) {// 优先级继承逻辑// ...}locked = true;}public synchronized void release() {locked = false;notifyAll();}
}
9. 性能优化技巧
9.1 提前终止时间需求分析
private boolean timeDemandAnalysis() {for (int i = 0; i < taskSet.size(); i++) {PeriodicTask task = taskSet.get(i);boolean found = false;// 优化:只检查特定的时间点int t = task.getExecutionTime();while (t <= task.getDeadline()) {double demand = calculateTimeDemand(i, t);if (demand <= t) {found = true;break;}// 下一个可能的t值是当前demand的下一个整数t = (int) Math.ceil(demand);}if (!found) return false;}return true;
}
9.2 利用周期性优化调度
public void schedule() {// ... 初始检查// 只需要调度一个超周期,因为之后模式会重复for (currentTime = 0; currentTime < hyperperiod; currentTime++) {// ... 调度逻辑}System.out.println("调度模式将在每个超周期(" + hyperperiod + "ms)后重复");
}
10. 总结
速率单调调度(RMS)是贪心算法在实时系统中的经典应用,它通过简单的优先级分配规则(周期越短优先级越高)实现了高效的任务调度。本文详细介绍了:
- RMS的基本原理和数学模型
- Java实现RMS的完整代码
- 可调度性分析方法(利用率界限和时间需求分析)
- 实际应用中的各种考虑因素
- 性能优化技巧和扩展变种
RMS虽然简单,但在实时系统领域有着广泛的应用,理解其原理和实现对于开发可靠的实时系统至关重要。