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output printing the len of arrival and service timesI am trying to implement an M/M/1 markovian process with exponential inter arrival and exponential service times using simpy. The code runs fine but I dont quite get the expected results. Also the number of list items in arrival times is lesser than the number of list items in service time after the code is run.

# make a markovian queue
# make a server as a resource
# make customers at random times
# record the customer arrival time
# customer gets the resource
# record when the customer got the resource
# serve the customers for a random time using resource
# save this random time as service time
# customer yields the resource and next is served

import statistics
import simpy
import random


arrival_time = []
service_time = []
mean_service = 2.0
mean_arrival = 1.0
num_servers = 1

class Markovian(object):
    def __init__(self, env, num_servers):
        self.env = env
        self.servers  = simpy.Resource(env, num_servers)
        #self.action = env.process(self.run())
    def server(self,packet ):
        #timeout after random service time
        t = random.expovariate(1.0/mean_service)
        #service_time.append(t)
        yield self.env.timeout(t)
    
    def getting_service(env, packet, markovian):
        # new packet arrives in the system
        arrival_time = env.now
        with markovian.servers.request() as req:
            yield req
            yield env.process(markovian.server(packet))
        service_time.append(env.now - arrival_time)
    
    def run_markovian(env,num_servers):
        markovian = Markovian(env,num_servers)
        packet = 0
        #generate new packets
        while True:
            t = random.expovariate(1.0/mean_arrival)
            arrival_time.append(t)
            yield env.timeout(t)
            packet +=1
            env.process(Markovian.getting_service(env,packet,markovian))

    def get_average_service_time(service_time):
        average_service_time = statistics.mean(service_time)
        return average_service_time
    
def main():
    random.seed(42)

    env= simpy.Environment()
    env.process(Markovian.run_markovian(env,num_servers))
    env.run(until = 50)
    print(Markovian.get_average_service_time(service_time))
    print (arrival_time)
    print (service_time)
    

    
if __name__ == "__main__":
    main()
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1 回答 1

1

您好，您的代码中基本上存在一个错误和两个排队论的误解：

错误 1) 服务器的定义在类内部，这使得模型表现为 M/M/inf 而不是 M/M/1

答：我把你的资源的定义放到class里面，从现在开始传递servers而不是num_servers。

误解1：按照您定义的时间：

mean_service = 2.0 mean_arrival = 1.0

该系统将生成更多的数据包并且能够提供服务。这就是为什么列表的大小如此不同的原因。

答案：mean_service = 1.0 mean_arrival = 2.0

误解二：

您在代码中所说的服务时间实际上是系统时间。

我还在你的代码中放了一些打印，所以我们可以看到它正在做。随意评论他们。并且不需要图书馆统计，所以我也评论了它。

我希望这个答案对你有用。

# make a markovian queue
# make a server as a resource
# make customers at random times
# record the customer arrival time
# customer gets the resource
# record when the customer got the resource
# serve the customers for a random time using resource
# save this random time as service time
# customer yields the resource and next is served

#import statistics
import simpy
import random


arrivals_time = []
service_time = []
waiting_time = []

mean_service = 1.0
mean_arrival = 2.0
num_servers = 1

class Markovian(object):
    def __init__(self, env, servers):
        self.env = env
        #self.action = env.process(self.run())

    #def server(self,packet ):
        #timeout after random service time
     #   t = random.expovariate(1.0/mean_service)
        #service_time.append(t)
      #  yield self.env.timeout(t)
    
    def getting_service(env, packet, servers):
        # new packet arrives in the system

        begin_wait = env.now
        req = servers.request()
        yield req
        
        begin_service = env.now
        waiting_time.append(begin_service - begin_wait)

        print('%.1f Begin Service of packet %d' % (begin_service, packet))
        
        yield env.timeout(random.expovariate(1.0/mean_service))
        
        service_time.append(env.now - begin_service)

        yield servers.release(req)
        print('%.1f End Service of packet %d' % (env.now, packet))

    
    def run_markovian(env,servers):
        markovian = Markovian(env,servers)
        packet = 0
        #generate new packets
        while True:
            t = random.expovariate(1.0/mean_arrival)
            yield env.timeout(t)
            arrivals_time.append(t)
            packet +=1
            print('%.1f Arrival of packet %d' % (env.now, packet))

            env.process(Markovian.getting_service(env,packet,servers))


    def get_average_service_time(service_time):
        average_service_time = statistics.mean(service_time)
        return average_service_time
    
def main():
    random.seed(42)

    env= simpy.Environment()
    servers  = simpy.Resource(env, num_servers)

    env.process(Markovian.run_markovian(env,servers))
    env.run(until = 50)
    
    print(Markovian.get_average_service_time(service_time))
    print ("Time between consecutive arrivals \n", arrivals_time)
    print("Size: ", len(arrivals_time))
    print ("Service Times \n", service_time)
    print("Size: ", len(service_time))
    print ("Waiting Times \n", service_time)
    print (waiting_time)
    print("Size: ",len(waiting_time))


    
if __name__ == "__main__":
    main()
于 2021-05-20T13:11:01.703 回答