实现先来先服务调度算法、短 进程优先调度算法、时间片轮转调度算法和优先级调度算法（抢占式）、高响应 比优先调度算法设计的步骤

这里给出实现先来先服务调度算法、短进程优先调度算法、时间片轮转调度算法和优先级调度算法（抢占式）、高响应比优先调度算法的大致步骤：

1. 首先需要设计进程控制块（PCB）来记录每个进程的信息，如进程ID、进程状态、进程优先级、进程到达时间、进程执行时间等。

2. 实现先来先服务调度算法，按照进程到达时间的先后顺序将进程加入就绪队列，每次从队列头取出一个进程进行执行，直到该进程执行完毕。

3. 实现短进程优先调度算法，将所有进程按照执行时间的长短排序，执行时间短的进程先执行，可以使用插入排序或者堆排序等算法。

4. 实现时间片轮转调度算法，设置一个时间片大小，将所有进程放入就绪队列中，每次从队列头取出一个进程执行固定时间片大小，如果该进程没有执行完，则重新放回队列尾部，等待下一次执行。

5. 实现优先级调度算法（抢占式），将所有进程按照优先级排序，执行优先级高的进程，如果有新的高优先级进程到达，则抢占当前正在执行的进程。

6. 实现高响应比优先调度算法，计算每个进程的响应比，响应比越高的进程先执行，可以使用动态优先级或者静态优先级来计算响应比。

需要注意的是，不同的算法实现可能需要使用不同的数据结构和算法技术，需要根据具体情况进行选择和实现。

相关问题

编程实现：先来先服务调度算法、短 进程优先调度算法、时间片轮转调度算法和优先级调度算法（抢占式）、高响应 比优先调度算法。

先来先服务调度算法（FCFS）：

def fcfs(processes):
    """
    First-Come, First-Served (FCFS) scheduling algorithm
    Input:
        processes: a list of dictionaries containing process information
                   Each dictionary should have the following keys:
                   - 'pid': process ID
                   - 'arrival_time': arrival time of the process
                   - 'burst_time': burst time of the process
    Output:
        a list of tuples containing the order in which the processes are executed
        Each tuple should have the following format:
        (process ID, start time, end time)
    """
    # Sort the processes by arrival time
    sorted_processes = sorted(processes, key=lambda x: x['arrival_time'])
    
    # Initialize the start and end times of the first process
    start_time = sorted_processes[0]['arrival_time']
    end_time = start_time + sorted_processes[0]['burst_time']
    
    # Initialize the order list with the first process
    order = [(sorted_processes[0]['pid'], start_time, end_time)]
    
    # Loop through the remaining processes and update the start and end times
    for i in range(1, len(sorted_processes)):
        if sorted_processes[i]['arrival_time'] > end_time:
            # If there is a gap between processes, update the start time
            start_time = sorted_processes[i]['arrival_time']
        else:
            # If the next process arrives before the current process finishes,
            # update the end time
            start_time = end_time
        end_time = start_time + sorted_processes[i]['burst_time']
        
        # Add the process to the order list
        order.append((sorted_processes[i]['pid'], start_time, end_time))
    
    return order

短进程优先调度算法（SJF）：

def sjf(processes):
    """
    Shortest-Job-First (SJF) scheduling algorithm
    Input:
        processes: a list of dictionaries containing process information
                   Each dictionary should have the following keys:
                   - 'pid': process ID
                   - 'arrival_time': arrival time of the process
                   - 'burst_time': burst time of the process
    Output:
        a list of tuples containing the order in which the processes are executed
        Each tuple should have the following format:
        (process ID, start time, end time)
    """
    # Sort the processes by arrival time and burst time
    sorted_processes = sorted(processes, key=lambda x: (x['arrival_time'], x['burst_time']))
    
    # Initialize the start and end times of the first process
    start_time = sorted_processes[0]['arrival_time']
    end_time = start_time + sorted_processes[0]['burst_time']
    
    # Initialize the order list with the first process
    order = [(sorted_processes[0]['pid'], start_time, end_time)]
    
    # Loop through the remaining processes and update the start and end times
    for i in range(1, len(sorted_processes)):
        if sorted_processes[i]['arrival_time'] > end_time:
            # If there is a gap between processes, update the start time
            start_time = sorted_processes[i]['arrival_time']
        else:
            # If the next process arrives before the current process finishes,
            # update the end time
            start_time = end_time
        end_time = start_time + sorted_processes[i]['burst_time']
        
        # Add the process to the order list
        order.append((sorted_processes[i]['pid'], start_time, end_time))
    
    return order

时间片轮转调度算法（RR）：

def rr(processes, quantum):
    """
    Round-Robin (RR) scheduling algorithm
    Input:
        processes: a list of dictionaries containing process information
                   Each dictionary should have the following keys:
                   - 'pid': process ID
                   - 'arrival_time': arrival time of the process
                   - 'burst_time': burst time of the process
        quantum: the time quantum for the algorithm
    Output:
        a list of tuples containing the order in which the processes are executed
        Each tuple should have the following format:
        (process ID, start time, end time)
    """
    # Sort the processes by arrival time
    sorted_processes = sorted(processes, key=lambda x: x['arrival_time'])
    
    # Initialize the start and end times of the first process
    start_time = sorted_processes[0]['arrival_time']
    end_time = min(start_time + sorted_processes[0]['burst_time'], sorted_processes[1]['arrival_time']) if len(sorted_processes) > 1 else start_time + sorted_processes[0]['burst_time']
    
    # Initialize the order list with the first process
    order = [(sorted_processes[0]['pid'], start_time, end_time)]
    
    # Initialize the queue with the remaining processes
    queue = sorted_processes[1:]
    
    # Loop through the queue until all processes are executed
    while queue:
        # Get the next process in the queue
        current_process = queue.pop(0)
        
        # If the process has not arrived yet, skip it
        if current_process['arrival_time'] > end_time:
            queue.append(current_process)
            continue
        
        # Calculate the remaining burst time for the current process
        remaining_time = current_process['burst_time']
        start_time = end_time
        
        # Loop through the time slices until the process finishes
        while remaining_time > 0:
            # If the time slice is smaller than the remaining time, update the end time
            if remaining_time > quantum:
                end_time = start_time + quantum
                remaining_time -= quantum
            else:
                end_time = start_time + remaining_time
                remaining_time = 0
            
            # Add the process to the order list
            order.append((current_process['pid'], start_time, end_time))
            
            # Update the start time for the next time slice
            start_time = end_time
            
            # Check if there are any new processes that have arrived
            for process in queue:
                if process['arrival_time'] <= end_time:
                    queue.remove(process)
                    queue.append(current_process)
                    current_process = process
                    remaining_time = current_process['burst_time']
                    break
    
    return order

优先级调度算法（抢占式）：

def priority_preemptive(processes):
    """
    Priority scheduling algorithm (preemptive)
    Input:
        processes: a list of dictionaries containing process information
                   Each dictionary should have the following keys:
                   - 'pid': process ID
                   - 'arrival_time': arrival time of the process
                   - 'burst_time': burst time of the process
                   - 'priority': priority of the process (higher number = higher priority)
    Output:
        a list of tuples containing the order in which the processes are executed
        Each tuple should have the following format:
        (process ID, start time, end time)
    """
    # Sort the processes by arrival time and priority
    sorted_processes = sorted(processes, key=lambda x: (x['arrival_time'], -x['priority']))
    
    # Initialize the start and end times of the first process
    start_time = sorted_processes[0]['arrival_time']
    end_time = start_time + sorted_processes[0]['burst_time']
    
    # Initialize the order list with the first process
    order = [(sorted_processes[0]['pid'], start_time, end_time)]
    
    # Initialize the queue with the remaining processes
    queue = sorted_processes[1:]
    
    # Loop through the queue until all processes are executed
    while queue:
        # Get the highest-priority process in the queue
        current_process = max(queue, key=lambda x: x['priority'])
        
        # If the process has not arrived yet, skip it
        if current_process['arrival_time'] > end_time:
            queue.remove(current_process)
            continue
        
        # Calculate the remaining burst time for the current process
        remaining_time = current_process['burst_time']
        start_time = end_time
        
        # Loop through the remaining processes to check if there is a higher-priority process
        for process in queue:
            if process['arrival_time'] <= end_time and process['priority'] > current_process['priority']:
                # If there is a higher-priority process, preempt the current process
                queue.remove(process)
                queue.append(current_process)
                current_process = process
                remaining_time = current_process['burst_time']
                break
        
        # Loop through the time slices until the process finishes
        while remaining_time > 0:
            # If the next process has a higher priority, preempt the current process
            if queue and max(queue, key=lambda x: x['priority'])['priority'] > current_process['priority']:
                break
            
            # If the time slice is smaller than the remaining time, update the end time
            if remaining_time > 1:
                end_time += 1
                remaining_time -= 1
            else:
                end_time += 1
                remaining_time = 0
            
            # Add the process to the order list
            order.append((current_process['pid'], start_time, end_time))
            
    return order

高响应比优先调度算法：

def hrrn(processes):
    """
    Highest-Response-Ratio-Next (HRRN) scheduling algorithm
    Input:
        processes: a list of dictionaries containing process information
                   Each dictionary should have the following keys:
                   - 'pid': process ID
                   - 'arrival_time': arrival time of the process
                   - 'burst_time': burst time of the process
    Output:
        a list of tuples containing the order in which the processes are executed
        Each tuple should have the following format:
        (process ID, start time, end time)
    """
    # Sort the processes by arrival time
    sorted_processes = sorted(processes, key=lambda x: x['arrival_time'])
    
    # Initialize the start and end times of the first process
    start_time = sorted_processes[0]['arrival_time']
    end_time = start_time + sorted_processes[0]['burst_time']
    
    # Initialize the order list with the first process
    order = [(sorted_processes[0]['pid'], start_time, end_time)]
    
    # Initialize the queue with the remaining processes
    queue = sorted_processes[1:]
    
    # Loop through the queue until all processes are executed
    while queue:
        # Calculate the response ratio for each process in the queue
        response_ratios = []
        for process in queue:
            wait_time = max(0, end_time - process['arrival_time'])
            response_ratio = (wait_time + process['burst_time']) / process['burst_time']
            response_ratios.append(response_ratio)
        
        # Get the process with the highest response ratio
        index = response_ratios.index(max(response_ratios))
        current_process = queue.pop(index)
        
        # Calculate the remaining burst time for the current process
        remaining_time = current_process['burst_time']
        start_time = end_time
        
        # Loop through the time slices until the process finishes
        while remaining_time > 0:
            # If the next process has a higher response ratio, preempt the current process
            response_ratios = []
            for process in queue:
                wait_time = max(0, end_time - process['arrival_time'])
                response_ratio = (wait_time + process['burst_time']) / process['burst_time']
                response_ratios.append(response_ratio)
            
            if queue and max(response_ratios) > ((end_time - current_process['arrival_time']) / current_process['burst_time']):
                break
            
            # If the time slice is smaller than the remaining time, update the end time
            if remaining_time > 1:
                end_time += 1
                remaining_time -= 1
            else:
                end_time += 1
                remaining_time = 0
            
            # Add the process to the order list
            order.append((current_process['pid'], start_time, end_time))
    
    return order

用c++综合实现：先来先服务调度算法、短 进程优先调度算法、时间片轮转调度算法和优先级调度算法（抢占式）、高响应 比优先调度算法。

以下是用 C++ 综合实现先来先服务调度算法、短进程优先调度算法、时间片轮转调度算法和优先级调度算法（抢占式）、高响应比优先调度算法的示例代码。

先来先服务调度算法：

#include<iostream>
#include<algorithm>
using namespace std;
struct node{
    int id;
    int arriveTime;
    int serveTime;
    int startTime;
    int waitTime;
    int finishTime;
    bool operator < (const node &b) const{
        return arriveTime<b.arriveTime;
    }
}a[1005];
int main(){
    int n;
    cin>>n;
    for(int i=1;i<=n;i++){
        cin>>a[i].arriveTime>>a[i].serveTime;
        a[i].id=i;
    }
    sort(a+1,a+n+1);
    a[1].startTime=a[1].arriveTime;
    a[1].finishTime=a[1].startTime+a[1].serveTime;
    a[1].waitTime=0;
    for(int i=2;i<=n;i++){
        if(a[i].arriveTime<=a[i-1].finishTime){
            a[i].startTime=a[i-1].finishTime;
        }
        else{
            a[i].startTime=a[i].arriveTime;
        }
        a[i].finishTime=a[i].startTime+a[i].serveTime;
        a[i].waitTime=a[i].startTime-a[i].arriveTime;
    }
    for(int i=1;i<=n;i++){
        cout<<"Process "<<a[i].id<<":\n";
        cout<<"Start time: "<<a[i].startTime<<endl;
        cout<<"Finish time: "<<a[i].finishTime<<endl;
        cout<<"Wait time: "<<a[i].waitTime<<endl;
        cout<<endl;
    }
    return 0;
}

短进程优先调度算法：

#include<iostream>
#include<algorithm>
using namespace std;
struct node{
    int id;
    int arriveTime;
    int serveTime;
    int startTime;
    int waitTime;
    int finishTime;
    bool operator < (const node &b) const{
        if(arriveTime!=b.arriveTime){
            return arriveTime<b.arriveTime;
        }
        else{
            return serveTime<b.serveTime;
        }
    }
}a[1005];
int main(){
    int n;
    cin>>n;
    for(int i=1;i<=n;i++){
        cin>>a[i].arriveTime>>a[i].serveTime;
        a[i].id=i;
    }
    sort(a+1,a+n+1);
    a[1].startTime=a[1].arriveTime;
    a[1].finishTime=a[1].startTime+a[1].serveTime;
    a[1].waitTime=0;
    for(int i=2;i<=n;i++){
        int pos=i;
        for(int j=i-1;j>=1;j--){
            if(a[j].finishTime<=a[i].arriveTime){
                break;
            }
            if(a[j].serveTime<a[pos].serveTime){
                pos=j;
            }
        }
        swap(a[i],a[pos]);
        if(a[i].arriveTime<=a[i-1].finishTime){
            a[i].startTime=a[i-1].finishTime;
        }
        else{
            a[i].startTime=a[i].arriveTime;
        }
        a[i].finishTime=a[i].startTime+a[i].serveTime;
        a[i].waitTime=a[i].startTime-a[i].arriveTime;
    }
    for(int i=1;i<=n;i++){
        cout<<"Process "<<a[i].id<<":\n";
        cout<<"Start time: "<<a[i].startTime<<endl;
        cout<<"Finish time: "<<a[i].finishTime<<endl;
        cout<<"Wait time: "<<a[i].waitTime<<endl;
        cout<<endl;
    }
    return 0;
}

时间片轮转调度算法：

#include<iostream>
#include<algorithm>
#include<queue>
using namespace std;
struct node{
    int id;
    int arriveTime;
    int serveTime;
    int startTime;
    int waitTime;
    int finishTime;
    int leftTime;
    bool operator < (const node &b) const{
        if(arriveTime!=b.arriveTime){
            return arriveTime<b.arriveTime;
        }
        else{
            return serveTime<b.serveTime;
        }
    }
}a[1005];
queue<node> q;
int main(){
    int n,timeSlice;
    cin>>n>>timeSlice;
    for(int i=1;i<=n;i++){
        cin>>a[i].arriveTime>>a[i].serveTime;
        a[i].id=i;
        a[i].leftTime=a[i].serveTime;
    }
    sort(a+1,a+n+1);
    a[1].startTime=a[1].arriveTime;
    a[1].finishTime=a[1].startTime+min(a[1].leftTime,timeSlice);
    a[1].waitTime=a[1].startTime-a[1].arriveTime;
    if(a[1].leftTime<=timeSlice){
        a[1].leftTime=0;
    }
    else{
        a[1].leftTime-=timeSlice;
        q.push(a[1]);
    }
    int currentTime=a[1].finishTime;
    int cnt=1;
    while(!q.empty()||cnt<n){
        while(cnt<n&&a[cnt+1].arriveTime<=currentTime){
            cnt++;
            q.push(a[cnt]);
        }
        if(q.empty()){
            cnt++;
            q.push(a[cnt]);
            currentTime=a[cnt].arriveTime;
        }
        node tmp=q.front();
        q.pop();
        tmp.startTime=currentTime;
        tmp.finishTime=currentTime+min(tmp.leftTime,timeSlice);
        tmp.waitTime=tmp.startTime-tmp.arriveTime;
        currentTime=tmp.finishTime;
        if(tmp.leftTime<=timeSlice){
            tmp.leftTime=0;
        }
        else{
            tmp.leftTime-=timeSlice;
            q.push(tmp);
        }
        a[tmp.id]=tmp;
    }
    for(int i=1;i<=n;i++){
        cout<<"Process "<<a[i].id<<":\n";
        cout<<"Start time: "<<a[i].startTime<<endl;
        cout<<"Finish time: "<<a[i].finishTime<<endl;
        cout<<"Wait time: "<<a[i].waitTime<<endl;
        cout<<endl;
    }
    return 0;
}

优先级调度算法（抢占式）：

#include<iostream>
#include<algorithm>
#include<queue>
using namespace std;
struct node{
    int id;
    int arriveTime;
    int serveTime;
    int startTime;
    int waitTime;
    int finishTime;
    int priority;
    bool operator < (const node &b) const{
        if(arriveTime!=b.arriveTime){
            return arriveTime<b.arriveTime;
        }
        else{
            return priority<b.priority;
        }
    }
}a[1005];
struct cmp{
    bool operator () (node x,node y) const{
        return x.priority<y.priority;
    }
};
priority_queue<node,vector<node>,cmp> q;
int main(){
    int n;
    cin>>n;
    for(int i=1;i<=n;i++){
        cin>>a[i].arriveTime>>a[i].serveTime>>a[i].priority;
        a[i].id=i;
    }
    sort(a+1,a+n+1);
    a[1].startTime=a[1].arriveTime;
    a[1].finishTime=a[1].startTime+a[1].serveTime;
    a[1].waitTime=a[1].startTime-a[1].arriveTime;
    for(int i=2;i<=n;i++){
        if(a[i].arriveTime<=a[i-1].finishTime){
            a[i].startTime=a[i-1].finishTime;
        }
        else{
            a[i].startTime=a[i].arriveTime;
        }
        a[i].finishTime=a[i].startTime+a[i].serveTime;
        a[i].waitTime=a[i].startTime-a[i].arriveTime;
    }
    int currentTime=a[1].finishTime;
    int cnt=1;
    while(!q.empty()||cnt<n){
        while(cnt<n&&a[cnt+1].arriveTime<=currentTime){
            cnt++;
            q.push(a[cnt]);
        }
        if(q.empty()){
            cnt++;
            q.push(a[cnt]);
            currentTime=a[cnt].arriveTime;
        }
        node tmp=q.top();
        q.pop();
        tmp.startTime=currentTime;
        tmp.finishTime=currentTime+tmp.serveTime;
        tmp.waitTime=tmp.startTime-tmp.arriveTime;
        currentTime=tmp.finishTime;
        a[tmp.id]=tmp;
    }
    for(int i=1;i<=n;i++){
        cout<<"Process "<<a[i].id<<":\n";
        cout<<"Start time: "<<a[i].startTime<<endl;
        cout<<"Finish time: "<<a[i].finishTime<<endl;
        cout<<"Wait time: "<<a[i].waitTime<<endl;
        cout<<endl;
    }
    return 0;
}

高响应比优先调度算法：

#include<iostream>
#include<algorithm>
#include<queue>
using namespace std;
struct node{
    int id;
    int arriveTime;
    int serveTime;
    int startTime;
    int waitTime;
    int finishTime;
    int priority;
    double ratio;
    bool operator < (const node &b) const{
        if(arriveTime!=b.arriveTime){
            return arriveTime<b.arriveTime;
        }
        else{
            return ratio<b.ratio;
        }
    }
}a[1005];
struct cmp{
    bool operator () (node x,node y) const{
        return x.priority<y.priority;
    }
};
priority_queue<node,vector<node>,cmp> q;
int main(){
    int n;
    cin>>n;
    for(int i=1;i<=n;i++){
        cin>>a[i].arriveTime>>a[i].serveTime>>a[i].priority;
        a[i].id=i;
        a[i].ratio=1.0*a[i].serveTime/a[i].waitTime;
    }
    sort(a+1,a+n+1);
    a[1].startTime=a[1].arriveTime;
    a[1].finishTime=a[1].startTime+a[1].serveTime;
    a[1].waitTime=a[1].startTime-a[1].arriveTime;
    for(int i=2;i<=n;i++){
        if(a[i].arriveTime<=a[i-1].finishTime){
            a[i].startTime=a[i-1].finishTime;
        }
        else{
            a[i].startTime=a[i].arriveTime;
        }
        a[i].finishTime=a[i].startTime+a[i].serveTime;
        a[i].waitTime=a[i].startTime-a[i].arriveTime;
    }
    int currentTime=a[1].finishTime;
    int cnt=1;
    while(!q.empty()||cnt<n){
        while(cnt<n&&a[cnt+1].arriveTime<=currentTime){
            cnt++;
            a[cnt].waitTime=currentTime-a[cnt].arriveTime;
            a[cnt].ratio=1.0*a[cnt].serveTime/a[cnt].waitTime;
            q.push(a[cnt]);
        }
        if(q.empty()){
            cnt++;
            a[cnt].waitTime=0;
            a[cnt].ratio=1.0*a[cnt].serveTime;
            q.push(a[cnt]);
            currentTime=a[cnt].arriveTime;
        }
        node tmp=q.top();
        q.pop();
        tmp.startTime=currentTime;
        tmp.finishTime=currentTime+tmp.serveTime;
        tmp.waitTime=tmp.startTime-tmp.arriveTime;
        currentTime=tmp.finishTime;
        a[tmp.id]=tmp;
    }
    for(int i=1;i<=n;i++){
        cout<<"Process "<<a[i].id<<":\n";
        cout<<"Start time: "<<a[i].startTime<<endl;
        cout<<"Finish time: "<<a[i].finishTime<<endl;
        cout<<"Wait time: "<<a[i].waitTime<<endl;
        cout<<endl;
    }
    return 0;
}