基于排队网络的流水线模拟器任务缓存新分析模型

流水线软件模拟器是嵌入式微处理器软件仿真系统的关键技术,提出对嵌入式微处理器流水线仿真系统的排队网络建模与缓存大小分析方法.对SPARC-V8流水线模拟器建立M/M/1/N型排队网络模型,分析指令到达及服务阻塞机制.为了解决模型计算中的阻塞问题,在排队网络模型中增加"保持节点",得到扩展的等价排队网络模型.采用近似计算迭代算法,得到系统性能评价指标,并建立排队网络节点性能关系曲线,确定各功能模块的任务缓存大小.根据得出的任务缓存计算值设置流水线软件模拟器实际缓存大小,实验表明模型计算数据与实际运行数据基本一致.该评价方法对嵌入式微处理器流水线仿真系统的建模与性能分析具有重要的指导意义.     

离散事件动态系统的分析和优化：排队网络模型方法（上）

排队网络是离散事件动态系统的一个有效模型,本文全面地介绍了基于排队网络模型的各种分析方法.包括随机分析法、运行分析法,平均值分析法、近似分析法、仿真法和摄动分析法.并介绍了排队网络理论在 FMS 中的应用.     

铁路集装箱中心站装卸系统排队模型及分析

针对铁路集装箱中心站装卸系统的设备性能运用闭排队网络模型进行研究。根据铁路集装箱中心站装卸系统的作业特点建立其闭排队网络模型,在该模型中内部集装箱卡车作为顾客在轨道门吊和正面吊两个服务节点以及一个虚设的“运输”服务节点接受服务。由于服务节点的服务时间不能很好地用传统分布表示,导致针对乘积形式排队网络的求解方法并不适用。于是采用近似平均值分析算法求解闭排队网络模型并获得相关的设备性能参数,并分析了装卸系统的设施配置。最终通过与仿真模型所得结果的对比,验证了模型和求解算法的正确性。     

排队理论在网络实时沟通服务系统的应用研究

网络实时沟通服务系统是一种集计算机软件技术、网络技术和排队理论于一体的综合信息系统,在当前的网络营销中已经得到了广泛应用。本文通过对网络实时沟通服务系统的服务的分析,建立了M/M/C/∞/∞排队系统的模型,并由此分析得到排队队长和等待时间等系统运行指标,最后确定出合理的客服数量,实现系统服务质量和效率的平衡。     

计算机系统的排队网络模型及其计算方法

计算机系统性能评价是计算机科学中一门新兴的学科。本文分六节系统介绍在计算机系统性能评价中广泛应用的排队网络模型及其计算方法。第一节简述排队网络模型的由来和发展。第二节描述了几种典型的排队网络模型,定义了用于性能评价的四个基本量——利用率、平均排队长度、平均等待时间和吞吐率。第三节介绍建立排队网络模型的一般方法。第四节简介排队网络模型的理论基础之一——运行分析。第五节论述排队网络模型常用的计算方法——归一化常数法、平均值分析法和某些近似计算方法。第六节介绍分析BCMP型排队网络(目前代表性最广的一种模型)的Pascal程序包,这个程序包已在VAX——11计算机上实现并经过验证。     

网络分组交换中的排队论模型分析

排队论模型在计算机网络通信系统中具有广泛应用,如评价网络性能,设计计算机网络等。作者通过对M/M/l和M/D/1模型的深入分析,得出了M/G/1模型中的最佳排队系统模型。     

网络分组交换中的排队论模型分析

排队论模型在计算机网络通信系统中具有广泛应用,如评价网络性能,设计计算机网络等.作者通过对M/M/1和M/D/1模型的深入分析,得出了M/G/1模型中的最佳排队系统模型.     

离散事件动态系统的分析和优化：排队网络模型方法（下）

5近似分析法前面我们介绍了排队网络的三种分析方法,它们都可以求出准确解。这当然是最理想结果,遗憾的是这些方法并不适用于所有的排队网络模型。因此在这一节里我们接着介绍排队网络模型的近似分析。事实上上节已经介绍了一种近似方法:平均值近似分析法。之所以提出近似分析是因为一方面有许多排队网络用现在的理论还无法求出其准确解,因此不得不借助于近似分析;另     

基于排队网络的多业务网络资源分析方法

随着下一代网络(NGN)的发展和新业务不断涌现,如何优化网络资源是提高业务服务质量(QoS)的重要措施之一.针对资源配置优化问题,采用排队网络理论提出一种多业务网络的资源分析方法,建立了排队服务模型,定义了流量分配方法,进行了模型求解与计算,给出了多种资源与服务质量之间的配置关系.通过仿真实验,验证了该方法的正确性.     

基于分层排队网络模型的分布式系统性能评价

关于并发或分布式系统的性台匕评价是一个广泛研究的课题,提供有效的数学理论工具、直观的模型描述方法和有效的模型分析方法,是系统性能评价所面临的关键问题。传统的性能模型——排队网络模型已很难分析这样复杂的系统,分层排队网络（Layered Queueing Net,LQN）模型是排队网络模型的扩展,可以用来分析相互依赖任务间的冲突。介绍了分层排队网络模型的原理及研究现状,并以DBMS为例,建立了DBMS的分层排队网络模型。     

Dynamic control of service rates in queuing networks

A method for dynamic control of service rates in closed exponential queuing networks is proposed. The performance of queuing networks with the service-rate control is analyzed, and the main steady-state network characteristics are computed using an analytic approximation. A simple example of a queuing network with controlled service rates is considered as an illustration. The efficiency of the service-rate control is confirmed by Monte Carlo simulations, which, as a by-product, also show acceptable accuracy of our analytical approximations.     

Interdeparture times from a queuing system with preemptive resume priority

We derive the Laplace-Stieltjes transform of the limiting interdeparture times distribution for each class of customers of a queuing system with preemptive resume priority, Poisson inputs and general service times. Numerical results and an application to queuing networks are also given.     

一类可修非周期Fork-Join排队网络分析

研究一类排队空间有限且服务台可修的非周期Fork-Join排队网络,给出求解稳态 概率的直接法和等效法,并计算一些排队指标和可修指标(如稳态队长、服务台的可用度和服 务台的失效概率),最后通过仿真验证其正确性.     

Perturbation analysis of closed queueing networks with generalservice time distributions

Perturbation analysis of closed queuing networks with nonexponential service time distributions is studied. Perturbation analysis formulas using realization probabilities are extended to these networks. A perturbation generation function, which generalizes the perturbation generation rule, is defined. equations for realization probability and formulas for sensitivity of the system throughput with respect to service time distribution parameters are presented. The formulas provide an analytical method of calculating throughput sensitivity and an explanation of the application of perturbation analysis algorithms for networks with general service time distributions. The author focuses on the extension of concepts and intuitive explanations of the formulas rather than on mathematical derivations     

A hybrid approach to minimize state space explosion problem for the solution of two stage tandem queues

Two stage open queuing networks are used for modeling the subsystem-behaviour in computers and communication networks, mass storage devices, memory servers, and queuing analysis of wireless mobile cellular networks. The queuing analysis of wireless systems is essential in order to quantify the impact of different factors on quality of service (QoS); performance measures so that wireless protocols can be designed and/or tuned in an optimal manner. In that sense two stage open queuing systems are particularly important to model handoff phenomena, especially for the integration of two different systems such as cellular and wireless local area networks (WLANs). Analytical solutions for two-dimensional Markov processes suffer from the state space explosion problem. The numerical difficulties caused by large state spaces, make it difficult to handle multiple servers at the second stage of a tandem queuing system together with server failures and repairs. This study presents a new approach to analytical modeling of open networks offering improvements in alleviating this problem. The proposed solution is a hybrid version, which combines well known spectral expansion, and hierarchical Markov reward rate approaches. Using this approach, two-stage open networks with multiple servers, break-downs, and repairs at the second stage and feedback can be modeled as three-dimensional Markov processes and solved for performability measures. Comparative results show that the new algorithm used for solution, provides a high degree of accuracy, and it is computationally more efficient than the existing approaches. The proposed model is capable of solving other three-dimensional Markov processes.     

区分服务网络中主动队列管理算法

现有区分服务网络的保证转发服务可提供稳定的带宽保证,但缺乏保证时延和分组丢失性能的有效方案.基于对RIO队列的稳态性能分析,提出两种自适应调整控制策略的主动队列管理算法(ARIO-D和ARIO-L).仿真结果表明,这两种算法在保持RIO算法带宽保证能力的同时,还可以提供稳定的和可区分的时延和分组丢失性能.采用ARIO-D和ARIO-L的保证转发服务可以为多媒体流量提供多种服务质量的定量保证.     

On the exact and approximate throughput analysis of closed queuingnetworks with blocking

A type of blocking is investigated in which, on completion of its service, a job attempts to enter a new station. If, at that moment, the destination station is full, the job is forced to reside in the server of the source station until a place becomes available in the destination station. The server of the source station remains blocked during this period of time. This model is known as a queuing network with transfer blocking. The state space of queuing networks with blocking is reduced by considering finite capacities of the stations. A nonblocking queuing network with the appropriate total number of jobs is derived. The state space of this network is equal to the state space of the blocking queuing network. The transformation of state space is exact for two-station networks and approximate for three-or-more station cases. The approximation has been validated by executing several examples, including stress tests. In all investigated network models, the approximate throughput results deviate, on the average, less than 3% from the simulation results     

Queuing Networks with Random Selection for Service

To the class of queuing networks analyzable by the method of Baskett, Chandy, Muntz, and Palacios, we add service centers whose scheduling is random. That is, upon completion of a service interval, the server chooses next to serve one of the waiting customers selected at random. As in the case of first-come first-served (FCFS) scheduling, all tasks must have the same exponentially distributed service time at such a center. We show that for purposes of this analysis, the results are identical to FCFS queuing. Example applications for random selection scheduling in computer system modeling are provided.     

Invariance of the stationary distribution of states of networks with multimode service, different types of requests, and discriminatory processor sharing

Open and closed queuing networks with multimode strategies and several types of requests are studied. Single-line nodes can operate in several modes. The time spent in each mode has an exponential distribution. The queuing discipline of the server is the discriminatory processor sharing (DPS). The number of requests is a random variable with an arbitrary distribution function. The invariance is established of the stationary distribution of the probabilities of the network states with respect to the functional form of the distributions of the work required to service the requests.