The queuing latencyðLqueueÞ: is the time a data waits in a queue till it can be executed. In a switched network, this is the time between the completion of signaling by the call originator and the arrival of a ringing signal at the call receiver. We calculate this delay by applying the queuing networks theory in M cascaded M=M=1 queues. We consider also a general analysis where the control procedure is applied in the form of \sliding window" by N frames or \ack at end of window" by a window equal to w.

排队延迟（Lqueue）是数据在队列中等待执行的时间。在交换网络中，这是呼叫发起者完成信令和呼叫接收者接收到振铃信号之间的时间。我们通过将排队网络理论应用于M级级联的M=M=1队列来计算这个延迟。我们还考虑了一个通用的分析，其中控制过程以N帧的形式应用，或者以窗口大小为w的“滑动窗口”形式应用“窗口结束时的ack”。

相关问题

The veri¯cation of latency time for distributed hard real-time systems is considered to be the most important performance metrics. It is important for safety critical applications and for performance evaluation of the transmission systems. The integration of a middleware in such application, can induce some communication delays. Therefore, we focused our interest to the computation of end to end latency. Some existing works, adopt optimization or scheduling methods in network computation.35,36 In our work, we propose the WCRT to take into account all possible delays. Latency is considered as the period of time since a message is written by a DataWriter until it is received by a DataReader. It consists of delay caused by signal processing, propagation, queuing and transmission. We detail the computation of latency period of a packet on its entire network path, and we verify its validity with DDS QoS:

对于分布式硬实时系统的延迟时间的验证被认为是最重要的性能指标。对于安全关键应用程序和传输系统的性能评估而言，它非常重要。在这种应用程序中集成中间件可能会引入一些通信延迟。因此，我们将重点放在计算端到端延迟上。一些现有的工作在网络计算中采用了优化或调度方法。在我们的工作中，我们提出了WCRT来考虑所有可能的延迟。延迟被认为是从消息被DataWriter写入到被DataReader接收的一段时间。它包括信号处理、传播、排队和传输引起的延迟。我们详细说明了数据包在整个网络路径上的延迟周期的计算，并通过DDS QoS验证其有效性。

Latency.: Let T = [tk]K×1 denotes the total latency that occurs during transmission, where tk is the total latency of user k. The tk can be calculated as tk = tk,1 + tk,2 + tk,3 + tk,4, (2) where tk,1 represents the queuing delay of user k, tk,2 is the resource access delay of user k, tk,3 is the processing delay of user k and tk,4 represents the propagation delay of user k. Specifically, tk,4 is calculated as tk,4 = di,k/v, (3) where di,k denotes the communication distance from UAV i to user k and v represents the propagation speed of electro- magnetic waves in the channe将这段文字用python代码表示

这段文字是一个数学公式，需要使用LaTeX语法进行表示。以下是使用Python中的matplotlib库将其表示为图片的代码：

import matplotlib.pyplot as plt

# Latex equation
equation = r'$t_k = t_{k,1} + t_{k,2} + t_{k,3} + t_{k,4}$' + '\n' \
           r'$t_{k,1}$ represents the queuing delay of user $k$,' + '\n' \
           r'$t_{k,2}$ is the resource access delay of user $k$,' + '\n' \
           r'$t_{k,3}$ is the processing delay of user $k$,' + '\n' \
           r'$t_{k,4}$ represents the propagation delay of user $k$.' + '\n' \
           r'Specifically, $t_{k,4}$ is calculated as $t_{k,4} = \frac{d_{i,k}}{v}$,' + '\n' \
           r'where $d_{i,k}$ denotes the communication distance from UAV $i$ to user $k$' \
           r' and $v$ represents the propagation speed of electromagnetic waves in the channel.'

# Plot equation
fig, ax = plt.subplots(figsize=(8, 4))
ax.text(0.5, 0.5, equation, ha='center', va='center', fontsize=14)
plt.axis('off')
plt.show()

输出的结果是一张包含该公式和相关说明的图片。