基于PH服务的工作休假排队的流模型

研究了带有单重工作休假的M/PH/1排队系统驱动的流体模型.首先,通过拟生灭过程和矩阵几何解法分别得到无穷小生成元和驱动过程的稳态队长分布.其次,建立并分析流体模型,根据平衡方程给出流体模型的稳态联合分布函数满足的矩阵微分方程组,利用Laplace变换(LT)和Laplace-Stieltjes变换(LST)的方法,推导出平稳缓冲器(库)容量的空库概率表达式和稳态条件下的缓冲器(库)容量的均值表达式.最后,给出模型在移动自组织网络(Ad Hoc)中的应用,并通过数值例子讨论系统参数对系统性能指标的影响.     

单重工作休假M/M/c排队驱动的流体模型分析

该文在M/M/c排队驱动系统中加入工作休假策略,研究了单重工作休假多服务台排队驱动的流体模型.利用拟生灭过程和矩阵几何解法得到驱动系统稳态队长分布.构建净输入率结构,导出流体模型的稳态联合分布函数满足的的矩阵微分方程组,进而利用Laplace-Stieltjes变换(LST)方法得到稳态下缓冲器库存量的空库概率及均值表达式.最后,给出模型在多信道无线Mesh网下的应用,通过数值例子展示参数变化对系统性能指标的影响.     

PH/M/1排队系统驱动的流模型

在流模型的研究中,传统的谱分析方法计算量极大,经常导致病态的数值结果.首先把PH/M/1排队系统的队长过程作为外部驱动环境,建立了一个新的流模型.其次,根据平衡条件给出流模型的稳态联合分布满足的矩阵微分方程,利用经典的Laplace变换(LT)方法给出稳态下缓冲器(库)的容量分布,进一步导出了稳态下的主要性能指标——平均缓冲器容量和空库概率的简洁表达式.最后,提出了数值例子展示了系统参数对性能指标的影响.     

双阶段休假M/PH/1排队驱动的流体模型性能分析

本文研究双阶段休假的M/PH/1排队系统驱动的流体模型.首先运用矩阵几何解法计算外部驱动系统的平稳队长.然后建立流排队模型,通过构造有效输入率函数得到流体模型满足的矩阵微分方程,结合矩阵几何解法、矢量化方法和迭代算法对其求解,可推导出缓冲器的平均库存量.最后通过数值实验分析了系统参数对其主要性能指标的影响.     

具有Bernoulli反馈且带有负顾客的PH/M/1排队系统

在PH/M/1排队模型中,引入了负顾客和Bernoulli反馈,并讨论了服务台容量为有限和无限两类模型,其中,模型一为服务台容量为无限的PH/M/1排队模型,利用拟生灭过程和矩阵几何解法得到了系统的转移速率矩阵,给出了系统正常返的充要条件,并得到了系统的稳态队长、忙期长度的拉普拉斯变换,以及系统的其它相关性能指标.模型二为服务台容量为有限的PH/M/1/N排队模型,同样使用拟生灭过程给出了马尔科夫过程的转移速率矩阵,并利用矩阵分析法进行求解,得到了该系统的稳态解和其它相关指标.     

可选服务的M/M/1多重休假排队系统驱动的流模型

在M/M/1多重休假排队驱动系统的基础上引入可选服务,探讨一类体现第二次服务可选的M/M/1多重休假驱动系统的流排队.构建净输入率结构,同时结合拟生灭过程方法获得驱动系统的平稳分布,利用Laplace变换(LT)方法得到流模型稳态库存量的Laplace-Stieltjes(LST),空库概率及均值的表达式.最后,通过数值分析验证系统性能指标的变动规律.     

M/M/c排队驱动的流模型分析

研究了一个多台排队系统队长过程作为外部随机环境的流模型.使用Laplace变换(LT)方法,发现缓冲器容量(库存量)分布的LT具有简洁的幂结构.进一步地,借助于Laplace-Stieltjes变换(LST)和LT之间的内在关系,给出了库存量分布的LST及平均库存量.最后,借助于一些数值例子刻画了系统参数对平均库存量及空库概率的影响.     

带负顾客和N-策略的Geo^{lambda_1, lambda_2/Geo/1(MWV)排队系统分析及最优控制策略N*

分析了一个带有负顾客、N-策略控制的Geo/Geo/1多重工作休假排队系统, 其中正顾客在工作休假及正规忙期以不同的到达率进入系统. 利用拟生灭过程和矩阵几何解方法, 给出了该模型的稳态队长分布及平均队长, 以及系统分别处于假期和忙期的概率. 同时, 对该系统的忙期进行了分析, 并讨论了稳态队长分布在系统容量的优化设计中的应用. 最后, 在给定的费用结构下, 用数值计算例子确定了使系统长期单位时间内期望费用最小的最优控制策 N*.     

带负顾客和N-策略的Geo~(λ_1,λ_2)/Geo/1(MWV)排队系统分析及最优控制策略N~*

分析了一个带有负顾客、N-策略控制的Geo/Geo/1多重工作休假排队系统,其中正顾客在工作休假及正规忙期以不同的到达率进入系统.利用拟生灭过程和矩阵几何解方法,给出了该模型的稳态队长分布及平均队长,以及系统分别处于假期和忙期的概率.同时,对该系统的忙期进行了分析,并讨论了稳态队长分布在系统容量的优化设计中的应用.最后,在给定的费用结构下,用数值计算例子确定了使系统长期单位时间内期望费用最小的最优控制策略N~*.     

具有工作故障及有限容量的MAP/M/1排队系统性能分析

为了拓展随机排队理论,在具有工作故障的MAP/M/1排队的基础上,引入有限容量策略建立起一个新的排队模型.通过Uniformization Technique将连续时间排队模型转化成对应的离散时间排队模型,运用矩阵几何组合解给出系统中的顾客数量和服务器状态的联合稳态概率表达式,并给出基于稳态概率的性能指标.最后通过一些数值例子展示参数对性能指标的影响.     

Exact Solution to Tandem Fluid Queues with Controlled Input

We consider a tandem fluid system composed of multiple buffers connected in a series. The first buffer receives input from a number of independent homogeneous on-off sources and each buffer provides input to the next buffer. The active (on) periods and silent (off) periods follow general and exponential distribution, respectively. Furthermore, the generally distributed active periods are controlled by an exponential timer. Under this assumption, explicit expressions for the distribution of the buffer content for the first buffer fed by a single source is obtained for the fluid queue driven by discouraged arrivals queue and infinite server queue. The buffer content distribution of the subsequent buffers when the first buffer is fed by multiple sources are found in terms of confluent hypergeometric functions. Numerical results are illustrated to compare the trend of the average buffer content for the models under consideration.     

Fluid Model Modulated by an M/M/1 Working Vacation Queue with Negative Customer

This paper investigates a fluid model driven by an M/M/1 queue with working vacations and RCE (Removal of customer in the end) policy of negative customer. In the external environment, the negative customer is not served by the server and only removes the positive customer in the end one-to-one. We establish a fluid flow model based on this stochastic process, and obtain the mean buffer content and the probability of empty buffer for this fluid queue using the LT (Laplace transform) method. Moreover, several special cases of the model here are obtained. Finally, some numerical examples are presented to demonstrate the effects of parameters on the performance indices of the fluid model.     

基于矩阵分析方法的具有双阶段休假的排队系统驱动的流模型性能分析

基于矩阵分析方法研究了具有单重工作休假和多重休假策略M/M/1排队系统驱动的流模型.首先建立了控制该流模型的微分方程组,利用矩阵分析方法,得出了系统平稳库存量的laplace变换(LT)的矩阵阶乘表达式.进而利用LaplaceStieltjes变换(LST)得出了平稳库存量的期望.最后,通过数值例子展示了系统性能指标与参数的关系.     

Fluid queue driven by aGI/GI/1 queue

Consider a model consisting of two phases: the GI/GI/1 queue and a buffer which is fed by a fluid arriving from a single-server queue. The fluid output from the GI/GI/1 queue is of the on/off type with on- and off-periods distributed as successive busy and idle periods in the GI/GI/1 queue. The fluid pours out of the buffer at a constant rate. The steady-state performance of this model is studied. We derive the Laplace-Stieltjes transform of the stationary distribution function of the buffer content in the case of the M/GI/1 queue in the first phase. It is shown that this distribution depends on the form of the service-time distribution. Therefore, the replacement of an M/GI/1 queue by an M/M/1 queue is not correct, in general. Continuity estimates are derived in the cast where the buffer is fed from the GI/GI/1 queue. Proceedings of the Seminar on Stability Problems for Stochastic Models, Moscow Russia, 1996, Part II.     

Fluid model driven by an M/M/1 queue with multiple vacations and N-policy

This paper studies a fluid model driven by an M/M/1 queue with multiple exponential vacations and N-policy. The expression for the Laplace transform of the joint steady-state distribution of the fluid model is of a simple matrix power function form or matrix factorial form. Based on this fact, we introduce a new method of fluid model??modified matrix geometric solution method. The Laplace transform and Laplace-Stieltjes transform of the steady-state distribution of the buffer content are concisely expressed through the minimal positive solution to a crucial quadratic equation. Finally, we give concise expression for the performance measure??mean buffer content, which is useful in parameter design of fluid model and various practical applications.     

对M/T-SPH/1排队平稳指标的进一步研究—数值计算与渐近分析

讨论M/T-SPH/1排队平稳队长分布的数值计算,以及平稳队长和逗留时间分布各阶矩的数值计算及渐近分析.其中T-SPH表示可数状态吸收生灭链吸收时间的分布.在分布PGF和LST的基础上,首先给出了计算平稳队长分布,平稳队长以及逗留时间分布各阶矩的数值结果的递推公式.其次还讨论了平稳队长及平稳逗留时间分布各阶矩的尾部渐近特征.结果表明当参数取不同值时,两个指标尾部具有三种不同类型的衰减方式.最后还用数值例子检验了方法的有效性.     

M/T-SPH/1排队平稳指标分布的尾部衰减特征

讨论M/T-SPH/1排队平稳队长分布和平稳逗留时间分布的尾部衰减特征,其中T-SPH表示可数状态吸收生灭过程吸收时间的分布。在分布PGF和LST的基础上,给出了两个平稳分布衰减规律的完整分析.结果表明,当参数取不同值时,平稳队长与平稳逗留时间的尾部具有三种不同类型的衰减特征.     

On a generic class of two-node queueing systems

This paper analyzes a generic class of two-node queueing systems. A first queue is fed by an on–off Markov fluid source; the input of a second queue is a function of the state of the Markov fluid source as well, but now also of the first queue being empty or not. This model covers the classical two-node tandem queue and the two-class priority queue as special cases. Relying predominantly on probabilistic argumentation, the steady-state buffer content of both queues is determined (in terms of its Laplace transform). Interpreting the buffer content of the second queue in terms of busy periods of the first queue, the (exact) tail asymptotics of the distribution of the second queue are found. Two regimes can be distinguished: a first in which the state of the first queue (that is, being empty or not) hardly plays a role, and a second in which it explicitly does. This dichotomy can be understood by using large-deviations heuristics. This work has been carried out partly in the Dutch BSIK/BRICKS project.     

A spectral theory approach for extreme value analysis in a tandem of fluid queues

We consider a model to evaluate performance of streaming media over an unreliable network. Our model consists of a tandem of two fluid queues. The first fluid queue is a Markov modulated fluid queue that models the network congestion, and the second queue represents the play-out buffer. For this model the distribution of the total amount of fluid in the congestion and play-out buffer corresponds to the distribution of the maximum attained level of the first buffer. We show that, under proper scaling and when we let time go to infinity, the distribution of the total amount of fluid converges to a Gumbel extreme value distribution. From this result, we derive a simple closed-form expression for the initial play-out buffer level that provides a probabilistic guarantee for undisturbed play-out.