98 lines
3.1 KiB
Python
98 lines
3.1 KiB
Python
# import simpy
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#
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# def task(env, name, resource, start_time, duration):
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# """任务进程"""
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# yield env.timeout(start_time) # 等待任务开始时间
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# print(f"{name} tries to use the resource at {env.now}")
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# with resource.request() as req:
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# yield req
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# print(f"{name} starts using the resource at {env.now}")
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# yield env.timeout(duration)
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# print(f"{name} finishes using the resource at {env.now}")
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#
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# # 创建仿真环境
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# env = simpy.Environment()
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#
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# # 创建共享资源
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# resource = simpy.Resource(env, capacity=1)
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#
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# # 启动任务进程
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# env.process(task(env, "Task A", resource, 0, 5)) # 任务A，从时间0开始，持续5个时间单位
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# env.process(task(env, "Task B", resource, 2, 3)) # 任务B，从时间2开始，持续3个时间单位
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#
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# # 运行仿真
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# env.run()
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import simpy
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import numpy as np
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import matplotlib.pyplot as plt
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def task(env, name, resource, start_time, duration, conflicts,taskID):
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"""任务进程"""
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yield env.timeout(start_time) # 等待任务开始时间
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print(f"{name} tries to use the resource at {env.now}")
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with resource.request() as req:
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yield req
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print(f"{name} starts using the resource at {env.now}")
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if resource.count == 1: # 检查是否发生冲突
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conflicts[0] = 1 # 记录冲突事件
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yield env.timeout(duration)
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print(f"{name} finishes using the resource at {env.now}")
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def run_simulation(num_tasks, num_rounds):
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"""运行多轮仿真"""
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# 存储冲突概率的列表
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conflict_probabilities = []
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task_start_times = np.random.randint(0, 10, num_tasks) # 任务开始时间均匀分布
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count = 0
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for round_num in range(num_rounds):
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count = count + 1
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print("=============第" + str(count) + "轮=============")
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# 创建仿真环境
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env = simpy.Environment()
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# 创建共享资源
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resource = simpy.Resource(env, capacity=1)
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# 记录冲突事件的列表
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conflicts = [0]
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# 仿真参数
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task_durations = np.random.normal(5, 1, num_tasks) # 任务持续时间正态分布
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a = np.zeros([num_rounds,num_tasks])
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print(task_start_times[0],task_start_times[1])
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# 启动任务进程
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for i in range(num_tasks):
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##conflicts[i] = 0
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env.process(task(env, f"Task {i}", resource, task_start_times[i], 10, conflicts, i))
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# 运行仿真
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env.run()
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print("=============end=============")
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for j in range(1, num_tasks):
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task_start_times[j] = task_start_times[j] + 10
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# 计算并记录冲突概率
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conflict_probabilities.append(conflicts[0] / num_tasks)
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return conflict_probabilities
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# 参数设置
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num_tasks = 2
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num_rounds = 2
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# 运行多轮仿真
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conflict_probabilities = run_simulation(num_tasks, num_rounds)
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# 绘制多个冲突概率曲线
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plt.plot(conflict_probabilities)
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plt.xlabel('Simulation Round')
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plt.ylabel('Conflict Probability')
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plt.title('Conflict Probability Across Simulation Rounds')
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plt.grid(True)
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plt.show()
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