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https://github.com/TheAlgorithms/Python.git
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313 lines
12 KiB
Python
313 lines
12 KiB
Python
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from collections import deque
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class Process:
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def __init__(self, process_name: str, arrival_time: int, burst_time: int) -> None:
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self.process_name = process_name # process name
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self.arrival_time = arrival_time # arrival time of the process
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# completion time of finished process or last interrupted time
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self.stop_time = arrival_time
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self.burst_time = burst_time # remaining burst time
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self.waiting_time = 0 # total time of the process wait in ready queue
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self.turnaround_time = 0 # time from arrival time to completion time
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class MLFQ:
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"""
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MLFQ(Multi Level Feedback Queue)
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https://en.wikipedia.org/wiki/Multilevel_feedback_queue
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MLFQ has a lot of queues that have different priority
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In this MLFQ,
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The first Queue(0) to last second Queue(N-2) of MLFQ have Round Robin Algorithm
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The last Queue(N-1) has First Come, First Served Algorithm
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"""
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def __init__(
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self,
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number_of_queues: int,
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time_slices: list[int],
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queue: deque[Process],
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current_time: int,
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) -> None:
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# total number of mlfq's queues
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self.number_of_queues = number_of_queues
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# time slice of queues that round robin algorithm applied
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self.time_slices = time_slices
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# unfinished process is in this ready_queue
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self.ready_queue = queue
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# current time
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self.current_time = current_time
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# finished process is in this sequence queue
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self.finish_queue: deque[Process] = deque()
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def calculate_sequence_of_finish_queue(self) -> list[str]:
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"""
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This method returns the sequence of finished processes
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>>> P1 = Process("P1", 0, 53)
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>>> P2 = Process("P2", 0, 17)
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>>> P3 = Process("P3", 0, 68)
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>>> P4 = Process("P4", 0, 24)
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>>> mlfq = MLFQ(3, [17, 25], deque([P1, P2, P3, P4]), 0)
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>>> _ = mlfq.multi_level_feedback_queue()
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>>> mlfq.calculate_sequence_of_finish_queue()
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['P2', 'P4', 'P1', 'P3']
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"""
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sequence = []
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for i in range(len(self.finish_queue)):
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sequence.append(self.finish_queue[i].process_name)
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return sequence
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def calculate_waiting_time(self, queue: list[Process]) -> list[int]:
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"""
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This method calculates waiting time of processes
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>>> P1 = Process("P1", 0, 53)
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>>> P2 = Process("P2", 0, 17)
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>>> P3 = Process("P3", 0, 68)
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>>> P4 = Process("P4", 0, 24)
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>>> mlfq = MLFQ(3, [17, 25], deque([P1, P2, P3, P4]), 0)
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>>> _ = mlfq.multi_level_feedback_queue()
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>>> mlfq.calculate_waiting_time([P1, P2, P3, P4])
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[83, 17, 94, 101]
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"""
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waiting_times = []
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for i in range(len(queue)):
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waiting_times.append(queue[i].waiting_time)
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return waiting_times
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def calculate_turnaround_time(self, queue: list[Process]) -> list[int]:
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"""
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This method calculates turnaround time of processes
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>>> P1 = Process("P1", 0, 53)
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>>> P2 = Process("P2", 0, 17)
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>>> P3 = Process("P3", 0, 68)
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>>> P4 = Process("P4", 0, 24)
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>>> mlfq = MLFQ(3, [17, 25], deque([P1, P2, P3, P4]), 0)
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>>> _ = mlfq.multi_level_feedback_queue()
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>>> mlfq.calculate_turnaround_time([P1, P2, P3, P4])
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[136, 34, 162, 125]
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"""
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turnaround_times = []
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for i in range(len(queue)):
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turnaround_times.append(queue[i].turnaround_time)
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return turnaround_times
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def calculate_completion_time(self, queue: list[Process]) -> list[int]:
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"""
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This method calculates completion time of processes
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>>> P1 = Process("P1", 0, 53)
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>>> P2 = Process("P2", 0, 17)
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>>> P3 = Process("P3", 0, 68)
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>>> P4 = Process("P4", 0, 24)
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>>> mlfq = MLFQ(3, [17, 25], deque([P1, P2, P3, P4]), 0)
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>>> _ = mlfq.multi_level_feedback_queue()
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>>> mlfq.calculate_turnaround_time([P1, P2, P3, P4])
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[136, 34, 162, 125]
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"""
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completion_times = []
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for i in range(len(queue)):
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completion_times.append(queue[i].stop_time)
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return completion_times
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def calculate_remaining_burst_time_of_processes(
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self, queue: deque[Process]
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) -> list[int]:
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"""
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This method calculate remaining burst time of processes
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>>> P1 = Process("P1", 0, 53)
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>>> P2 = Process("P2", 0, 17)
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>>> P3 = Process("P3", 0, 68)
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>>> P4 = Process("P4", 0, 24)
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>>> mlfq = MLFQ(3, [17, 25], deque([P1, P2, P3, P4]), 0)
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>>> finish_queue, ready_queue = mlfq.round_robin(deque([P1, P2, P3, P4]), 17)
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>>> mlfq.calculate_remaining_burst_time_of_processes(mlfq.finish_queue)
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[0]
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>>> mlfq.calculate_remaining_burst_time_of_processes(ready_queue)
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[36, 51, 7]
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>>> finish_queue, ready_queue = mlfq.round_robin(ready_queue, 25)
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>>> mlfq.calculate_remaining_burst_time_of_processes(mlfq.finish_queue)
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[0, 0]
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>>> mlfq.calculate_remaining_burst_time_of_processes(ready_queue)
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[11, 26]
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"""
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return [q.burst_time for q in queue]
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def update_waiting_time(self, process: Process) -> int:
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"""
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This method updates waiting times of unfinished processes
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>>> P1 = Process("P1", 0, 53)
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>>> P2 = Process("P2", 0, 17)
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>>> P3 = Process("P3", 0, 68)
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>>> P4 = Process("P4", 0, 24)
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>>> mlfq = MLFQ(3, [17, 25], deque([P1, P2, P3, P4]), 0)
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>>> mlfq.current_time = 10
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>>> P1.stop_time = 5
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>>> mlfq.update_waiting_time(P1)
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5
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"""
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process.waiting_time += self.current_time - process.stop_time
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return process.waiting_time
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def first_come_first_served(self, ready_queue: deque[Process]) -> deque[Process]:
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"""
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FCFS(First Come, First Served)
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FCFS will be applied to MLFQ's last queue
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A first came process will be finished at first
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>>> P1 = Process("P1", 0, 53)
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>>> P2 = Process("P2", 0, 17)
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>>> P3 = Process("P3", 0, 68)
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>>> P4 = Process("P4", 0, 24)
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>>> mlfq = MLFQ(3, [17, 25], deque([P1, P2, P3, P4]), 0)
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>>> _ = mlfq.first_come_first_served(mlfq.ready_queue)
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>>> mlfq.calculate_sequence_of_finish_queue()
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['P1', 'P2', 'P3', 'P4']
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"""
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finished: deque[Process] = deque() # sequence deque of finished process
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while len(ready_queue) != 0:
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cp = ready_queue.popleft() # current process
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# if process's arrival time is later than current time, update current time
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if self.current_time < cp.arrival_time:
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self.current_time += cp.arrival_time
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# update waiting time of current process
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self.update_waiting_time(cp)
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# update current time
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self.current_time += cp.burst_time
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# finish the process and set the process's burst-time 0
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cp.burst_time = 0
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# set the process's turnaround time because it is finished
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cp.turnaround_time = self.current_time - cp.arrival_time
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# set the completion time
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cp.stop_time = self.current_time
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# add the process to queue that has finished queue
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finished.append(cp)
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self.finish_queue.extend(finished) # add finished process to finish queue
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# FCFS will finish all remaining processes
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return finished
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def round_robin(
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self, ready_queue: deque[Process], time_slice: int
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) -> tuple[deque[Process], deque[Process]]:
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"""
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RR(Round Robin)
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RR will be applied to MLFQ's all queues except last queue
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All processes can't use CPU for time more than time_slice
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If the process consume CPU up to time_slice, it will go back to ready queue
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>>> P1 = Process("P1", 0, 53)
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>>> P2 = Process("P2", 0, 17)
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>>> P3 = Process("P3", 0, 68)
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>>> P4 = Process("P4", 0, 24)
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>>> mlfq = MLFQ(3, [17, 25], deque([P1, P2, P3, P4]), 0)
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>>> finish_queue, ready_queue = mlfq.round_robin(mlfq.ready_queue, 17)
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>>> mlfq.calculate_sequence_of_finish_queue()
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['P2']
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"""
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finished: deque[Process] = deque() # sequence deque of terminated process
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# just for 1 cycle and unfinished processes will go back to queue
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for i in range(len(ready_queue)):
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cp = ready_queue.popleft() # current process
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# if process's arrival time is later than current time, update current time
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if self.current_time < cp.arrival_time:
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self.current_time += cp.arrival_time
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# update waiting time of unfinished processes
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self.update_waiting_time(cp)
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# if the burst time of process is bigger than time-slice
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if cp.burst_time > time_slice:
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# use CPU for only time-slice
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self.current_time += time_slice
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# update remaining burst time
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cp.burst_time -= time_slice
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# update end point time
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cp.stop_time = self.current_time
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# locate the process behind the queue because it is not finished
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ready_queue.append(cp)
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else:
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# use CPU for remaining burst time
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self.current_time += cp.burst_time
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# set burst time 0 because the process is finished
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cp.burst_time = 0
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# set the finish time
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cp.stop_time = self.current_time
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# update the process' turnaround time because it is finished
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cp.turnaround_time = self.current_time - cp.arrival_time
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# add the process to queue that has finished queue
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finished.append(cp)
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self.finish_queue.extend(finished) # add finished process to finish queue
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# return finished processes queue and remaining processes queue
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return finished, ready_queue
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def multi_level_feedback_queue(self) -> deque[Process]:
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"""
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MLFQ(Multi Level Feedback Queue)
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>>> P1 = Process("P1", 0, 53)
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>>> P2 = Process("P2", 0, 17)
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>>> P3 = Process("P3", 0, 68)
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>>> P4 = Process("P4", 0, 24)
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>>> mlfq = MLFQ(3, [17, 25], deque([P1, P2, P3, P4]), 0)
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>>> finish_queue = mlfq.multi_level_feedback_queue()
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>>> mlfq.calculate_sequence_of_finish_queue()
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['P2', 'P4', 'P1', 'P3']
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"""
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# all queues except last one have round_robin algorithm
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for i in range(self.number_of_queues - 1):
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finished, self.ready_queue = self.round_robin(
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self.ready_queue, self.time_slices[i]
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)
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# the last queue has first_come_first_served algorithm
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self.first_come_first_served(self.ready_queue)
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return self.finish_queue
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if __name__ == "__main__":
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import doctest
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P1 = Process("P1", 0, 53)
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P2 = Process("P2", 0, 17)
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P3 = Process("P3", 0, 68)
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P4 = Process("P4", 0, 24)
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number_of_queues = 3
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time_slices = [17, 25]
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queue = deque([P1, P2, P3, P4])
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if len(time_slices) != number_of_queues - 1:
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exit()
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doctest.testmod(extraglobs={"queue": deque([P1, P2, P3, P4])})
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P1 = Process("P1", 0, 53)
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P2 = Process("P2", 0, 17)
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P3 = Process("P3", 0, 68)
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P4 = Process("P4", 0, 24)
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number_of_queues = 3
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time_slices = [17, 25]
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queue = deque([P1, P2, P3, P4])
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mlfq = MLFQ(number_of_queues, time_slices, queue, 0)
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finish_queue = mlfq.multi_level_feedback_queue()
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# print total waiting times of processes(P1, P2, P3, P4)
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print(
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f"waiting time:\
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\t\t\t{MLFQ.calculate_waiting_time(mlfq, [P1, P2, P3, P4])}"
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)
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# print completion times of processes(P1, P2, P3, P4)
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print(
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f"completion time:\
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\t\t{MLFQ.calculate_completion_time(mlfq, [P1, P2, P3, P4])}"
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)
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# print total turnaround times of processes(P1, P2, P3, P4)
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print(
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f"turnaround time:\
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\t\t{MLFQ.calculate_turnaround_time(mlfq, [P1, P2, P3, P4])}"
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)
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# print sequence of finished processes
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print(
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f"sequnece of finished processes:\
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{mlfq.calculate_sequence_of_finish_queue()}"
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)
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