Considet the code:
import simpy
import random
import matplotlib.pyplot as plt

# Parameters
num_edge_nodes = 1
edge_buffer_size = 15
cloud_buffer_size = 20


# service times
cloud_server_time = 10
A_edge_service_time = 4
A_cloud_service_time = 2
B_edge_sevice_time = 2
B_cloud_service_partialprocess = 4
B_cloud_service_fullprocess = 5
propagation_delay = 1


arrival_rate = .8


# Measurements

class Measure:
    def __init__(self, N_arr_a, N_arr_b, drop):
        self.N_arr_A = N_arr_a
        self.N_arr_B = N_arr_b
        self.drop = drop

measurements = Measure(0, 0, 0)


def packet_arrivals(env, micro_data_center, cloud_data_center, data, edge_buffer, cloud_buffer):
    packet_type_options = ['A', 'B']
    packet_id = 1

    while True:
        packet_type = random.choices(packet_type_options, weights=(1 - f, f))[0]

        # Updating arrival data
        if packet_type == "A":
            data.N_arr_A = data.N_arr_A + 1
        else:
            data.N_arr_B = data.N_arr_B + 1



        if len(micro_data_center.items) < edge_buffer:
            if packet_type == "A":
                micro_data_center.put((packet_id, packet_type, A_edge_service_time))
            elif packet_type == "B":
                micro_data_center.put((packet_id, packet_type, B_edge_sevice_time))


        else:
            if len(cloud_data_center.items) < cloud_buffer:
                if packet_type == "A":
                    cloud_data_center.put(
                        (packet_id, packet_type, A_cloud_service_time + propagation_delay))

                elif packet_type == "B":
                    cloud_data_center.put(
                        (packet_id, packet_type, B_cloud_service_fullprocess + propagation_delay))

            else:
                data.drop = data.drop + 1


        yield env.timeout(random.expovariate(arrival_rate))
        packet_id += 1


def edge_node(env, micro_data_center, cloud_data_center, node_id):
    while True:
        packet_id, packet_type, packet_processing_time = yield micro_data_center.get()

        yield env.timeout(packet_processing_time)
        print(f"Edge Node {node_id} processed packet {packet_id} of type {packet_type} at time {env.now}")

        if packet_type == 'B':
            yield cloud_data_center.put((packet_id, packet_type, B_cloud_service_partialprocess + propagation_delay))


def cloud_server(env, cloud_data_center):
    while True:
        packet_id, packet_type, packet_processing_time = yield cloud_data_center.get()

        yield env.timeout(packet_processing_time)
        print(
            f"Cloud Server processed {packet_type} packet {packet_id} (including propagation delay) at time {env.now}")


# Simulation setup


f = 0.5  # Fraction of packets of type B


simtime = 10000
# Recording data


# Run the simulation
losses = []
buffer_size_local = list(range(1, 100000 + 1, 10000))
for buffer_local in buffer_size_local:
    env = simpy.Environment()
    micro_data_center = simpy.Store(env)
    cloud_data_center = simpy.Store(env)
    env.process(packet_arrivals(env, micro_data_center, cloud_data_center, measurements, buffer_local, cloud_buffer_size))
    for node_id in range(num_edge_nodes):
        env.process(edge_node(env, micro_data_center, cloud_data_center, node_id + 1))
    env.process(cloud_server(env, cloud_data_center))
    env.run(until=simtime)
    losses.append( 100*  measurements.drop/ ( measurements.N_arr_A+ measurements.N_arr_B))


plt.plot(buffer_size_local, losses)
#plt.axvline(x=2000, color='red', linestyle='--')
#plt.text(2000, max(losses), 'Transition Period', color='red', va='bottom', ha='center')
plt.xlabel('Different local buffer sizes')
plt.ylabel('Loss Probability at Cloud (%)')
plt.title('Loss Probability over Different local buffer sizes')
plt.show()


I use the above code to perform the task below which is a part of simulating a network system, taking into account the output of the code, write an anlytic result for the task considering the task requirements.
The task:
Consider the overall system operation, including both the Micro Data Center and
the Cloud Data Center.
(a) How does the size of the buffer in the micro Data Center impact on the overall
system performance?