Marginal and joint distribution of inter-departure times for a PH/PH/c queue

IF 1 4区 计算机科学 Q4 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
Ruth Sagron , Yoav Kerner
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引用次数: 0

Abstract

In this paper, we introduce the Laplace–Stieltjes transform (LST) of the inter-departure time distribution in a PH/PH/c queue, and the two-dimensional joint LST of two consecutive inter-departure times to construct their correlation structure. We exploit the properties of phase-type (PH) random variables, as well as the steady-state distribution of the underlying continuous-time Markov chain in a PH/PH/c queue to construct these LSTs. We demonstrate our approach through numerical examples, while validating the results. Later, we analyze the correlation between two consecutive inter-departure times for various PH/PH/c queues. We observe that, if the fundamental elements of the queue have high (low) variability, then the correlation is positive (negative).

PH/PH/c队列出发时间的边际和联合分布
本文引入了PH/PH/c队列出发时间分布的Laplace-Stieltjes变换(LST),以及两个连续出发时间的二维联合LST,构建了它们的关联结构。我们利用相型(PH)随机变量的性质,以及PH/PH/c队列中底层连续时间马尔可夫链的稳态分布来构建这些lst。我们通过数值例子来证明我们的方法,同时验证结果。随后,我们分析了不同PH/PH/c队列的两个连续出发时间之间的相关性。我们观察到,如果队列的基本元素具有高(低)可变性,则相关性为正(负)。
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来源期刊
Performance Evaluation
Performance Evaluation 工程技术-计算机:理论方法
CiteScore
3.10
自引率
0.00%
发文量
20
审稿时长
24 days
期刊介绍: Performance Evaluation functions as a leading journal in the area of modeling, measurement, and evaluation of performance aspects of computing and communication systems. As such, it aims to present a balanced and complete view of the entire Performance Evaluation profession. Hence, the journal is interested in papers that focus on one or more of the following dimensions: -Define new performance evaluation tools, including measurement and monitoring tools as well as modeling and analytic techniques -Provide new insights into the performance of computing and communication systems -Introduce new application areas where performance evaluation tools can play an important role and creative new uses for performance evaluation tools. More specifically, common application areas of interest include the performance of: -Resource allocation and control methods and algorithms (e.g. routing and flow control in networks, bandwidth allocation, processor scheduling, memory management) -System architecture, design and implementation -Cognitive radio -VANETs -Social networks and media -Energy efficient ICT -Energy harvesting -Data centers -Data centric networks -System reliability -System tuning and capacity planning -Wireless and sensor networks -Autonomic and self-organizing systems -Embedded systems -Network science
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