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另一位用户在最短作业优先 (SJF) 上发布了此问题。这是示例:在此处输入图像描述

接下来如何解决最短剩余时间?Shortest Job First 的抢先版。

我了解选择执行剩余时间最少的过程。但是,如果一个新进程到达,其突发时间与当前执行进程的剩余完成时间完全相同,会发生什么?

在一个新进程到达的情况下,其突发时间与当前执行进程相同(如本例所示),那么当前执行的进程是否继续?

甘特图显示了我如何理解将安排的流程:在此处输入图像描述

我的理解正确吗?先感谢您。

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2 回答 2

1

引用维基百科的最短剩余时间

在这种调度算法中,选择执行剩余时间最少的进程。由于根据定义,当前执行的进程是剩余时间最短的进程,并且由于该时间只会随着执行的进行而减少,因此进程将始终运行直到它们完成或添加需要更短时间的新进程

最短的剩余时间是有利的,因为短的过程处理得非常快。该系统还需要很少的开销,因为它只在进程完成或添加新进程时做出决定,而当添加新进程时,算法只需将当前正在执行的进程与新进程进行比较,而忽略所有其他进程目前正在等待执行。//强调我的。

如果一个新进程到达,其突发时间与当前正在执行的进程的剩余完成时间完全相同,那么 CPU 将继续执行当前进程。做出这个决定是因为进程上下文切换更重,因此在剩余突发时间相等的情况下,当前正在执行的进程将继续执行直到完成,或者新的短进程到达。

而且,是的,您的甘特图已正确绘制。

但是,请也阅读这些限制 // 来自 Wikipedia:

与最短作业下一次调度一样,最短剩余时间调度很少在专业环境之外使用,因为它需要准确估计每个进程的运行时间。

于 2018-05-12T19:31:08.603 回答
0

如果新进程的执行时间比当前进程短,则在 CPU 上运行的进程会被新进程抢占。我们可以使用以下python函数实现抢占式最短剩余时间下一次调度的算法,并模拟CPU上进程的执行:

import pandas as pd

def SRTN(df): # df is the data frame with arrival / burst time of processes

    queue = []
    cpu, cur_pdf = None, None
    alloc, dalloc = {}, {}

    time = 0

    while True: # simulate the CPU scheduling algorithm

        # check if all processes finished execution
        if df['RemainingTime'].max() == 0:
            break

        # get current process assigned to cpu, if any
        if cpu:
            cur_pdf =  df[df.Process == cpu]    

        # check if a process arrived at this time instance and put it into wait queue
        pdf = df[df.ArrivalTime == time]

        if len(pdf) > 0:
            for p in pdf['Process'].values:
                queue.append(p)

        if len(queue) > 0:
            pdf = df[df['Process'].isin(queue)]

            # find the process with shortest remaining time
            if len(pdf) > 0:
                pdf = pdf[pdf['RemainingTime']==pdf['RemainingTime'].min()]

            # allocate a process to CPU, pre-empt the running one if required
            if (cpu is None) or (len(pdf) > 0 and pdf['RemainingTime'].values[0] < cur_pdf['RemainingTime'].values[0]):
                if cpu:
                    # prempt the current process
                    dalloc[cpu] = dalloc.get(cpu, []) + [time]
                    queue.append(cpu)
                    print('Process {} deallocated from CPU at time {}'.format(cpu, time))
                cur_pdf = pdf
                cpu = cur_pdf['Process'].values[0]
                queue.remove(cpu)
                print('Process {} allocated to CPU at time {}'.format(cpu, time))
                alloc[cpu] = alloc.get(cpu, []) + [time]

        df.loc[df['Process']==cpu,'RemainingTime'] -= 1

        time += 1 # increment timer

        # deallocate process
        if df[df['Process']==cpu]['RemainingTime'].values[0] == 0:
            print('Process {} deallocated from CPU at time {}'.format(cpu, time))
            dalloc[cpu] = dalloc.get(cpu, []) + [time]
            cpu = cur_pdf = None
            
    return alloc, dalloc

现在,对以下数据(进程到达/突发时间)运行 SRTN:

df = pd.DataFrame({'Process':['A','B','C','D'], 'BurstTime':[3,5,3,2], 'ArrivalTime':[0,2,5,6]})
df.sort_values('ArrivalTime', inplace=True)
df['RemainingTime'] = df.BurstTime

df

在此处输入图像描述

alloc, dalloc = SRTN(df)
# Process A allocated to CPU at time 0
# Process A deallocated from CPU at time 3
# Process B allocated to CPU at time 3
# Process B deallocated from CPU at time 8
# Process D allocated to CPU at time 8
# Process D deallocated from CPU at time 10
# Process C allocated to CPU at time 10
# Process C deallocated from CPU at time 13
 
# alloc
# {'A': [0], 'B': [3], 'D': [8], 'C': [10]}
# dalloc
# {'A': [3], 'B': [8], 'D': [10], 'C': [13]}

以下动画显示了使用上述实现获得抢占式 SRTN 调度算法的甘特图:

在此处输入图像描述

让我们考虑下面3个进程的到来的输入表,在数据帧上运行SRTN,得到对应的甘特图:

在此处输入图像描述

alloc, dalloc, events = SRTN(df)
# Process A allocated to CPU at time 0
# Process A deallocated from CPU at time 1
# Process B allocated to CPU at time 1
# Process B deallocated from CPU at time 5
# Process A allocated to CPU at time 5
# Process A deallocated from CPU at time 11
# Process C allocated to CPU at time 11
# Process C deallocated from CPU at time 19

上表对应的甘特图如下动画所示,使用上述算法得到:

在此处输入图像描述

于 2022-01-27T15:31:41.283 回答