半马尔可夫过程的极限分布及其推广

本文运用马尔可夫骨架过程的极限理论研究齐次可列半马尔可夫过程,得到其极限分布.当更新间隔的分布不是格子分布时,本文的结果和邓永录等[1]中的结果一致,但采用的方法不同,本文采用的是马尔可夫骨架过程的理论方法,而[1]中采用的是交替更新过程的方法;而且关于更新间隔服从格子分布的情形,[1]中没有研究,而本文给出了结果.最...     

两个更新过程叠加的特征问题

N_1(t),N_2(t)是两个独立更新过程,如N(t)=N_1(t)+N_2(t)仍是一更新过程,本文证明了当N_1(t),N_2(t)的间隔分布属于NBUE(NWUE)分布类时,N_1(t),N_2(t),N(t)都是Poisson过程,并改进了Karlin书中的结论。在§2中对更广的具有延迟和镇住时间的两更新过程的叠加问题得到了类似的结论。     

Threshold分红策略下带干扰的两类索赔风险模型的Geber-Shiu函数

本文研究了在threshold分红策略下带干扰的两类索赔风险模型的Geber-Shiu函数.这里假设两个索赔计数过程为独立的更新过程,其中一个为Poisson过程另一个为时间间隔服从广义Erlang(2)分布的更新过程.本文得到了threshold分红策略下Gerber-Shiu函数所满足的积分-微分方程及其边界条件....     

常利率下复合泊松-更新风险模型的破产问题

本文研究了常数利率下,保费收入为复合Poisson过程,理赔到达过程为一般更新过程的风险模型.利用离散化的方法,获得了该风险模型的破产概率、破产时余额分布及破产前瞬间余额分布的级数展开式,推广了文[1]和文[2]中的相关结果.     

常利率下复合泊松-更新风险模型的破产问题

本文研究了常数利率下, 保费收入为复合Poisson 过程, 理赔到达过程为一般更新过程的风险模型. 利用离散化的方法, 获得了该风险模型的破产概率、破产时余额分布及破产前瞬间余额分布的级数展开式, 推广了文[1] 和文[2] 中的相关结果.     

服务台休假的GI/Geom/1离散时间排队

本文研究了具有位相型休假、位相型启动和单重几何休假的离散时间排队,假定 顾客到达间隔服从一般分布,服务时间服从几何分布,运用矩阵解析方法我们得到了这 些排队系统中顾客在到达时刻稳态队长分布及其随机分解.     

PH/M/c可修排队系统

研究了一个修理工和c个服务台的可修排队系统.假设顾客的到达过程为PH更新过程,服务台在忙时与闲时具有不同的故障率.顾客的服务时间、服务台的寿命以及服务台的修理时间均服从指数分布.通过建立系统的拟生灭过程,得到了系统稳态分布存在的充要条件.利用矩阵几何解方法,给出了系统的稳态队长.在此基础上,得到了系统的某些排队论和可靠性指标.     

基于p-进入规则和单重休假的Min(N,V)-策略M/G/1排队

研究具有p-进入规则和基于服务员单重休假Min(N,V)-策略控制的M/G/1排队系统,其中在服务员休假期间到达的顾客以概率p (0≤p≤1)进入系统.运用全概率分解技术和拉普拉斯变换工具,借助更新过程理论,讨论了系统从任意初始状态出发,在任意时刻t的瞬态队长分布,得到了瞬态队长分布的拉普拉斯变换表达式.进一步获得了稳态队长分布的递推表达式,并给出了p=0与p=1的特殊结果.最后,通过数值计算实例讨论了系统容量的最优设计问题.     

一类索赔额服从指数幂尾型分布的风险模型及其破产概率的渐近性质

本文研究了一类风险模型,其个体索赔额服从指数-幂尾型分布,索赔次数过程为一更新过程,其更新时间间隔服从指数族分布；给出了这类模型在有限时间内破产概率的渐近性质；并讨论了在破产发生后的特征．     

保费到达为更新过程的复合更新风险模型

本在经典风险模型基础上，把索赔到达过程Nt加以推广为更新过程。且在保单到达非均匀的前提下，把保单到送过程推广为更新过程Mt，得到有限时间t孕余的瞬时分布ψ（u,θ0,t,α），然后求得时刻t的生存概率ψ（t,u，θ0)。     

TRANSIENT SOLUTION FOR QUEUE-LENGTH DISTRIBUTION OF Geometry/G/1 QUEUEING MODEL

In this paper, the Geometry/G/1 queueing model with inter-arrival times generated by a geometric（parameter p） distribution according to a late arrival system with delayed access and service times independently distributed with distribution {gj }, j≥ 1 is studied. By a simple method （techniques of probability decomposition, renewal process theory） that is different from the techniques used by Hunter（1983）, the transient property of the queue with initial state i（i ≥ 0） is discussed. The recursion expression for u -transform of transient queue-length distribution at any time point n^＋ is obtained, and the recursion expression of the limiting queue length distribution is also obtained.     

The Gerber-Shiu function and the generalized Cramér-Lundberg model

In this paper we extend some results in Cramér [7] by considering the expected discounted penalty function as a generalization of the infinite time ruin probability. We consider his ruin theory model that allows the claim sizes to take positive as well as negative values. Depending on the sign of these amounts, they are interpreted either as claims made by insureds or as income from deceased annuitants, respectively. We then demonstrate that when the events’ arrival process is a renewal process, the Gerber-Shiu function satisfies a defective renewal equation. Subsequently, we consider some special cases such as when claims have exponential distribution or the arrival process is a compound Poisson process and annuity-related income has Erlang(n, β) distribution. We are then able to specify the parameter and the functions involved in the above-mentioned defective renewal equation.     

Bounds for the tail distribution in a queue with a superposition of general periodic Markov sources: theory and application

An efficient yet accurate estimation of the tail distribution of the queue length has been considered as one of the most important issues in call admission and congestion controls in ATM networks. The arrival process in ATM networks is essentially a superposition of sources which are typically bursty and periodic either due to their origin or their periodic slot occupation after traffic shaping. In this paper, we consider a discrete-time queue where the arrival process is a superposition of general periodic Markov sources. The general periodic Markov source is rather general since it is assumed only to be irreducible, stationary and periodic. Note also that the source model can represent multiple time-scale correlations in arrivals. For this queue, we obtain upper and lower bounds for the asymptotic tail distribution of the queue length by bounding the asymptotic decay constant. The formulas can be applied to a queue having a huge number of states describing the arrival process. To show this, we consider an MPEG-like source which is a special case of general periodic Markov sources. The MPEG-like source has three time-scale correlations: peak rate, frame length and a group of pictures. We then apply our bound formulas to a queue with a superposition of MPEG-like sources, and provide some numerical examples to show the numerical feasibility of our bounds. Note that the number of states in a Markov chain describing the superposed arrival process is more than 1.4 × 10⁸⁸. Even for such a queue, the numerical examples show that the order of the magnitude of the tail distribution can be readily obtained.     

Asymptotic analysis of the effect of arrival model uncertainties in some optimal routing problems

We study the effect of arrival model uncertainties on the optimal routing in a system of parallel queues. For exponential service time distributions and Bernoulli routing, the optimal mean system delay generally depends on the interarrival time distribution. Any error in modeling the arriving process will cause a model-based optimal routing algorithm to produce a mean system delay higher than the true optimum. In this paper, we present an asymptotic analysis of the behavior of this error under heavy traffic conditions for a general renewal arrival process. An asymptotic analysis of the error in optimal mean delay due to uncertainties in the service time distribution for Poisson arrivals was reported in Ref. 6, where it was shown that, when the first moment of the service time distribution is known, this error in performance vanishes asymptotically as the traffic load approaches the system capacity. In contrast, this paper establishes the somewhat surprising result that, when only the first moment of the arrival distribution is known, the error in optimal mean delay due to uncertainties in the arrival model is unbounded as the traffic approaches the system capacity. However, when both first and second moments are known, the error vanishes asymptotically. Numerical examples corroborating the theoretical results are also presented.This work was supported by the National Science Foundation under Grants ECS-88-01912 and EID-92-12122 and by NASA under Contract NAG 2-595.The authors wish to thank an anonymous referee for pointing out Ref. 20, thus avoiding the need for an explicit proof of convexity of the cost function considered in the paper.     

Empirical Bayesian analysis for traffic intensity:M/M/1 queues with covariates

In this paper, we consider a set of individualM/M/1 queues in which variations in both arrival rates and service rates are partly explained by some covariates representing associated characteristics of individual queues. The random error that takes into account the remaining variation is assumed to follow a gamma distribution. Bayes and empirical Bayes procedures are suggested to make inferences concerning individual traffic intensity parameters that can be applied to several industrial queueing problems.     

用燕尾突变理论来讨论交通流预测

交通流本身是一个动态过程，运用尖点突变理论来分析交通流的预测时只考虑了流量和密度，而忽视了时间因素，这本身就不是很合理的．基于这个基础之上，采用燕尾突变理论来讨论交通流预测时将时间因素考虑进去，并给出一个算例表明了此方法预测的效果更符合现实。     

On a multivariate renewal-reward process involving time delays and discounting: applications to IBNR processes and infinite server queues

This paper considers a particular renewal-reward process with multivariate discounted rewards (inputs) where the arrival epochs are adjusted by adding some random delays. Then, this accumulated reward can be regarded as multivariate discounted Incurred But Not Reported claims in actuarial science and some important quantities studied in queueing theory such as the number of customers in \(G/G/\infty \) queues with correlated batch arrivals. We study the long-term behaviour of this process as well as its moments. Asymptotic expressions and bounds for quantities of interest, and also convergence for the distribution of this process after renormalization, are studied, when interarrival times and time delays are light tailed. Next, assuming exponentially distributed delays, we derive some explicit and numerically feasible expressions for the limiting joint moments. In such a case, for an infinite server queue with a renewal arrival process, we obtain limiting results on the expectation of the workload, and the covariance of queue size and workload. Finally, some queueing theoretic applications are provided.     

Tandem behavior of a telecommunication system with finite buffers and repeated calls

The tandem behavior of a telecommunication system with finite buffers and repeated calls is modeled by the performance of a finite capacityG/M/1 queueing system with general interarrival time distribution, exponentially distributed service time, the first-come-first-served queueing discipline and retrials. In this system a fraction of the units which on arrival at a node of the system find it busy, may retry to be processed, by merging with the incoming arrival units in that node, after a fixed delay time. The performance of this system in steady state is modeled by a queueing network and is approximated by a recursive algorithm based on the isolation method. The approximation outcomes are compared against those from a simulation study. Our numerical results indicate that in steady state the non-renewal superposition arrival process, the non-renewal overflow process, and the non-renewal departure process of the above system can be approximated with compatible renewal processes.     

Analyzing <Emphasis Type="Italic">M/M/</Emphasis>1 Queues with Perturbations in the Arrival Process

This paper investigates when the M/M/1 model can be used to predict accurately the operating characteristics of queues with arrival processes that are slightly different from the Poisson process assumed in the model. The arrival processes considered here are perturbed Poisson processes. The perturbations are deviations from the exponential distribution of the inter-arrival times or from the assumption of independence between successive inter-arrival times. An estimate is derived for the difference between the expected numbers in perturbed and M/M/1 queueing systems with the same traffic intensity. The results, for example, indicate that the M/M/1 model can predict the performance of the queue when the arrival process is perturbed by inserting a few short inter-arrival times, an occasional batch arrival or small dependencies between successive inter-arrival times. In contrast, the M/M/1 is not a good model when the arrival process is perturbed by inserting a few long inter-arrival times.     

Finite-size corrections to Poisson approximations in general renewal-success processes

Consider a renewal process, and let K?0 denote the random duration of a typical renewal cycle. Assume that on any renewal cycle, a rare event called “success” can occur. Such successes lend themselves naturally to approximation by Poisson point processes. If each success occurs after a random delay, however, Poisson convergence can be relatively slow, because each success corresponds to a time interval, not a point. If K is an arithmetic variable, a “finite-size correction” (FSC) is known to speed Poisson convergence by providing a second, subdominant term in the appropriate asymptotic expansion. This paper generalizes the FSC from arithmetic K to general K. Genomics applications require this generalization, because they have already heuristically applied the FSC to p-values involving absolutely continuous distributions. The FSC also sharpens certain results in queuing theory, insurance risk, traffic flow, and reliability theory.