ABOUT THE AVERAGE MAXIMUM VALUES OF QUEUES IN QUEUING SYSTEMS

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Abstract

In the classical theory of queuing systems, the assumption of mutual independence of events is fundamental, so we propose to consider the basic principles of the interval method of traffic analysis, which allows us to replace analysis of time intervals between neighboring requests and time intervals for processing requests by analyzing one random variable, i. e. the number of requests received during successive intervals of time for processing each of requests. The concepts of mean maximum values of queues and limiting maximum values are introduced. It is shown that the limit maximum value in a queue will be the largest of the possible maximum values for a given total value of requests in queues during one service cycle. The mean maximum score is the average of the maximum queue values. To determine the characteristics of traffic, we use the well-known «Leaky_bucket» algorithm. The proposed traffic model is based on the total number of requests during their processing cycles. Experimental modeling of the proposed method showed that variance and correlation properties of a specified random variable for a given load completely characterize the average queue size in a queuing system.
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关于排队系统中排队的平均最大值
在经典的排队系统理论中,事件相互独立的假设是基本的,因此我们提出考虑流量分析的间隔方法的基本原理,该方法允许我们通过分析一个随机变量,即在处理每个请求的连续时间间隔内收到的请求的数量,来取代相邻请求之间的时间间隔和处理请求的时间间隔的分析。引入了队列均值最大值和极限最大值的概念。结果表明,队列中的极限最大值将是一个服务周期内队列中给定请求总价值的可能最大值中最大的一个。平均最大分数是最大队列值的平均值。为了确定流量的特征,我们使用了众所周知的«Leaky_bucket»算法。所建议的流量模型基于处理周期内的请求总数。该方法的实验建模表明,对于给定负载,指定随机变量的方差和相关性质完全表征了排队系统中的平均队列大小。
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