''' HRRN: Highest Response Ratio Next The task is to find the Average Waiting Time and Average Turnaround Time of the given processes with their Burst Time using HRRN Scheduling Algorithm. HRRN is a scheduling policy that selects the waiting process with the Highest Response Ratio to execute next. Response Ratio = (Waiting Time + Current Burst Time)/Current Burst Time HRRN is a Non Pre-emptive Algorithm, hence the process which has the Highest Response Ratio will be served first and the next process will be served only after the previous process is executed completely. HRRN has the advantage of favouring shorter processes. We will consider processes with different arrival time because in case of process arriving at the same time, it follows FCFS Algorithm as the Response Ratio will be same for all processes. Start Time: Time at which the execution of the process starts Completion Time: Time at which the process completes its execution Turnaround Time: Completion Time - Arrival Time Waiting Time: Turnaround Time - Burst Time I have made use of 2 queues in the code: Ready Queue: It stores all the processes which have already arrived. Normal Queue: It stores all the processes which have not arrived yet. '''

class HRRN: def processData(self, no_of_processes): process_data = [] for i in range(no_of_processes): temporary = [] process_id = int(input("Enter Process ID: "))

arrival_time = int(input(f"Enter Arrival Time for Process {process_id}: "))

burst_time = int(input(f"Enter Burst Time for Process {process_id}: "))

temporary.extend([process_id, arrival_time, burst_time, 0]) ''' '0' is the state of the process. 0 means not executed and 1 means execution complete ''' process_data.append(temporary) HRRN.schedulingProcess(self, process_data) def schedulingProcess(self, process_data): start_time = [] exit_time = [] s_time = 0 sequence_of_processes = [] process_data.sort(key=lambda x: x[1]) ''' Sort processes according to the Arrival Time ''' for i in range(len(process_data)): ready_queue = [] temp = [] normal_queue = [] for j in range(len(process_data)): if (process_data[j][1] <= s_time) and (process_data[j][3] == 0): response_ratio = 0 response_ratio = float(((s_time - process_data[j][1]) + process_data[j][2]) / process_data[j][2]) ''' Calculating the Response Ratio foe each process ''' temp.extend([process_data[j][0], process_data[j][1], process_data[j][2], response_ratio]) ready_queue.append(temp) temp = [] elif process_data[j][3] == 0: temp.extend([process_data[j][0], process_data[j][1], process_data[j][2]]) normal_queue.append(temp) temp = [] if len(ready_queue) != 0: ready_queue.sort(key=lambda x: x[3], reverse=True) ''' Sort the processes according to the Highest Response Ratio ''' start_time.append(s_time) s_time = s_time + ready_queue[0][2] e_time = s_time exit_time.append(e_time) sequence_of_processes.append(ready_queue[0][0]) for k in range(len(process_data)): if process_data[k][0] == ready_queue[0][0]: break process_data[k][3] = 1 process_data[k].append(e_time) elif len(ready_queue) == 0: if s_time < normal_queue[0][1]: s_time = normal_queue[0][1] start_time.append(s_time) s_time = s_time + normal_queue[0][2] e_time = s_time exit_time.append(e_time) sequence_of_processes.append(normal_queue[0][0]) for k in range(len(process_data)): if process_data[k][0] == normal_queue[0][0]: break process_data[k][3] = 1 process_data[k].append(e_time) t_time = HRRN.calculateTurnaroundTime(self, process_data) w_time = HRRN.calculateWaitingTime(self, process_data) HRRN.printData(self, process_data, t_time, w_time, sequence_of_processes) def calculateTurnaroundTime(self, process_data): total_turnaround_time = 0 for i in range(len(process_data)): turnaround_time = process_data[i][4] - process_data[i][1] ''' turnaround_time = completion_time - arrival_time ''' total_turnaround_time = total_turnaround_time + turnaround_time process_data[i].append(turnaround_time) average_turnaround_time = total_turnaround_time / len(process_data) ''' average_turnaround_time = total_turnaround_time / no_of_processes ''' return average_turnaround_time def calculateWaitingTime(self, process_data): total_waiting_time = 0 for i in range(len(process_data)): waiting_time = process_data[i][5] - process_data[i][2] ''' waiting_time = turnaround_time - burst_time ''' total_waiting_time = total_waiting_time + waiting_time process_data[i].append(waiting_time) average_waiting_time = total_waiting_time / len(process_data) ''' average_waiting_time = total_waiting_time / no_of_processes ''' return average_waiting_time def printData(self, process_data, average_turnaround_time, average_waiting_time, sequence_of_processes): process_data.sort(key=lambda x: x[0]) ''' Sort processes according to the Process ID ''' print("Process_ID Arrival_Time Burst_Time Completed Completion_Time Turnaround_Time Waiting_Time")

for i in range(len(process_data)): for j in range(len(process_data[i])):

print(process_data[i][j], end="\t\t\t\t") print()

print(f'Average Turnaround Time: {average_turnaround_time}')

print(f'Average Waiting Time: {average_waiting_time}')

print(f'Sequence of Processes: {sequence_of_processes}')

if __name__ == "__main__":

no_of_processes = int(input("Enter number of processes: ")) hrrn = HRRN() hrrn.processData(no_of_processes)

Output:

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