45408 - پروژه پایتون (فناوری اطلاعات)

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شرح پروژه

کارشناسی ارشد مهندسی فناوری اطلاعات

من یک پایان نامه با مشخصات زیر دارم ،میخواستم ببینید هزینه اینکه کد من درست کار میکند یا خیر چقدر است ؟ (ضمیمه کردم)

پروژه پایتون:

Station')

plt.title("Loyal LEACH - WSN Simulation")

plt.xlabel("X-axis")

plt.ylabel("Y-axis")

plt.legend()

plt.grid()

plt.show()

import numpy as np

import matplotlib.pyplot as plt

# Parameters

NUM_NODES = 100  # Number of nodes

FIELD_SIZE = (100, 100)  # Area of the network (100x100 units)

INITIAL_ENERGY = 0.5  # Initial energy for each node (in Joules)

BASE_STATION = (50, 50)  # Location of the base station

TRANSMIT_COST = 50e-9  # Energy to transmit (per bit)

RECEIVE_COST = 50e-9  # Energy to receive (per bit)

AMPLIFICATION_COST = 10e-12  # Energy for amplification (per bit per meter^2)

DATA_PACKET_SIZE = 4000  # Packet size in bits

LOYALITY_THRESHOLD = 5  # Number of rounds a node avoids being a cluster head

# Node Class

class Node:

    def _init_(self, x, y):

        self.x = x

        self.y = y

        self.energy = INITIAL_ENERGY

        self.is_cluster_head = False

        self.cluster = None

        self.rounds_since_ch = 0  # Tracks rounds since last CH status

    def distance_to(self, x, y):

        return np.sqrt((self.x - x)*2 + (self.y - y)*2)

# Initialize nodes

nodes = [Node(np.random.uniform(0, FIELD_SIZE[0]), np.random.uniform(0, FIELD_SIZE[1])) for _ in range(NUM_NODES)]

# Loyal LEACH Algorithm

def select_cluster_heads(nodes, p=0.1):

    """Select cluster heads based on energy and loyalty constraints."""

    for node in nodes:

        if (

            node.energy > 0 and

            node.rounds_since_ch >= LOYALITY_THRESHOLD and

            np.random.rand() < p and

            node.energy > np.mean([n.energy for n in nodes if n.energy > 0])

        ):

            node.is_cluster_head = True

            node.rounds_since_ch = 0

        else:

            node.is_cluster_head = False

            node.rounds_since_ch += 1

def assign_clusters(nodes):

    """Assign nodes to the nearest cluster head."""

    for node in nodes:

        if not node.is_cluster_head and node.energy > 0:

            min_dist = float('inf')

            for ch in [n for n in nodes if n.is_cluster_head and n.energy > 0]:

                dist = node.distance_to(ch.x, ch.y)

                if dist < min_dist:

                    min_dist = dist

                    node.cluster = ch

# Energy Consumption

def transmit(node, distance):

    """Calculate energy consumption for transmission."""

    return TRANSMIT_COST * DATA_PACKET_SIZE + AMPLIFICATION_COST * DATA_PACKET_SIZE * distance**2

def receive():

    """Calculate energy consumption for receiving."""

    return RECEIVE_COST * DATA_PACKET_SIZE

# Simulation

NUM_ROUNDS = 100

total_energy_consumed = 0

packets_to_base_station = 0

for round_num in range(NUM_ROUNDS):

    print(f"Round {round_num + 1}")

    # Select cluster heads

    select_cluster_heads(nodes)

    # Assign clusters

    assign_clusters(nodes)

    # Energy consumption for cluster communication

    for node in nodes:

        if node.energy > 0:

            if node.is_cluster_head:

                # Cluster heads receive and transmit

                total_receive_cost = sum(receive() for n in nodes if n.cluster == node)

                distance_to_bs = node.distance_to(*BASE_STATION)

                transmit_cost = transmit(node, distance_to_bs)

                node.energy -= total_receive_cost + transmit_cost

                total_energy_consumed += total_receive_cost + transmit_cost

                packets_to_base_station += 1

            elif node.cluster:

                # Regular nodes transmit to cluster head

                distance_to_ch = node.distance_to(node.cluster.x, node.cluster.y)

                transmit_cost = transmit(node, distance_to_ch)

                node.energy -= transmit_cost

                total_energy_consumed += transmit_cost

    # Remove nodes with no energy

    alive_nodes = sum(1 for node in nodes if node.energy > 0)

    print(f"Alive nodes: {alive_nodes}")

# Plot

plt.figure(figsize=(8, 8))

for node in nodes:

    if node.energy > 0:

        color = 'red' if node.is_cluster_head else 'blue'

        plt.scatter(node.x, node.y, color=color)

    else:

        plt.scatter(node.x, node.y, color='black')

plt.scatter(BASE_STATION[0], BASE_STATION[1], color='green', marker='x', label='Base

داده ها همینقدر است

این پروژه شامل 1 فایل مهم است، لطفا قبل از ارسال پیشنهاد حتما نسبت به بررسی این فایل اقدام فرمایید.

مهارت ها و تخصص های مورد نیاز

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