Effects of pooling,specialization,and discretionary task completion on queueing performance

Pooling,unpooling/specialization,and discretionary task completion are typical operational strategies in queueing systems that arise in healthcare,call centers,and online sales.These strategies may have advantages and disadvantages in different operational environments.This paper uses the M/M/1 and M/M/2 queues to study the impact of pooling,specialization,and discretionary task completion on the average queue length.Closed-form solutions for the average M/M/2 queue length are derived.Computational examples illustrate how the average queue length changes with the strength of pooling,specialization,and discretionary task completion.Finally,several conjectures are made in the paper.

The MAP/PH(PH/PH)/1 Discrete-time Queuing System with Repairable Server

In this paper, we discuss a discrete time repairable queuing system with Markovian arrival process, where lifetime of server, service time and repair time of server are all discrete phase type random variables. Using the theory of matrix geometric solution, we give the steady state distribution of queue length and waiting time. In addition, the stable availability of the system is also provided.

Optimal gateway deployment under different queuing mechanisms in smart grid

By optimizing the network topology, this paper proposes a newmethod of queuing theory clustering algorithm based on dynamic programming in a home energy management system（ HEMS）. First, the total cost of the HEMS system is divided into two parts, the gateway installation cost and the data transmission cost. Secondly, through comparing two kinds of different queuing theories, the cost problem of the HEMS is converted into the problem of gateway deployment. Finally, a machine-to-machine（ M2M） gateway configuration scheme is designed to minimize the cost of the system. Simulation results showthat the cost of the HEMS system mainly comes from the installation cost of the gateways when the gateway buffer space is large enough. If the gateway buffer space is limited, the proposed queue algorithm can effectively achieve optimal gateway setting while maintaining the minimal cost of the HEMS at desired levels through marginal analyses and the properties of cost minimization.

基于BIM-Queuing Theory的超高层施工电梯配置方法研究

随着中国经济的高速发展,相对发达的城市都在建设超高层建筑并将其作为自己的地标性建筑。由于超高层建筑施工过程中工作面有限,投入资金量大,加快施工进度从而降低施工成本显得尤为重要。目前施工单位的施工管理水平有限,进度与成本两个目标的权衡变得很困难,施工单位在布置施工电梯时多是根据经验进行粗略估算,这可能会造成巨大的资源浪费。通过搜集和研究当前施工电梯在超高层建筑中的应用现状,应用BIM技术与排队论,结合施工电梯的实际应用状况,对施工电梯布置方法进行研究,力求为施工单位在配置施工电梯时提供一种新的思路,加强施工单位在施工过程中的管理水平,从而提高经济效益。

基于Queuing Theory的收费服务系统模型优化及仿真

针对目前诸多形态的收费服务系统运行效率不高的现状,通过对收费服务系统排队规定和措施的研究分析,基于排队论对收费服务系统数学模型进行优化,并以超市为实证对象,对优化模型进行仿真。根据仿真结果,所提出的收费服务系统优化模型能在一定程度上减少排队时间或者是在排队时间既定的情况下,减少收费资源的投入。

Application of the Queuing Theory in Characterizing and Optimizing the Passenger Flow at the Airport Security

This paper presents mathematics models that describe and optimize the passenger flow at the airport security checkpoints by applying the queuing theory. Firstly, a Poisson process is used to estimate the flow of passengers waiting for going through the security. Then, the Poisson distribution is combined with a multiple M/M/s model. Following that, an arrival model (passengers’ arriving at the checkpoints preparing for security examination and departure) with Gumbel extreme value estimation is described that predicts the busiest time in the busiest airport. Real case data collected from several major airports worldwide is used for creating a hybrid Poisson model to generate the simulation of passenger volume. At last, Markov Chain theory is applied to the analysis to randomly simulate the flow of enplaned passengers again, and the results of these two simulations are compared and discussed, revealing that the hybrid Poisson model is the more accurate one. After successfully characterizing the passenger flow mathematically, two methods for optimizing the passenger flow are then provided in two different respects: one is bypassing passengers and creating an express pass;while the other one promotes Pre-Check service application.

Using Poisson Modeling and Queuing Theory to Optimize Staffing and Decrease Patient Wait Time in the Emergency Department

Introduction: Studies have shown Emergency Department (ED) crowding contributes to reduced quality of patient care, delays in starting treatments, and increased number of patients leaving without being seen. This analysis shows how to theoretically and optimally align staffing to demand. Methods: The ED value stream was identified and mapped. Patients were stratified into three resource-driven care flow cells based on the severity indices. Time observations were conducted for each of the key care team members and the manual cycle times and service rate were calculated and stratified by severity indices. Using X32 Healthcare’s Online Staffing Optimization (OSO) tool, staffing inefficiencies were identified and an optimal schedule was created for each provider group. Results: Lower Severity Indices (higher acuity patient) led to longer times for providers, nurses, patient care assistants, and clerks. The patient length of stay varied from under one hour to over five hours. The flow of patients varied considerably over the 24 hours’ period but was similar by day of the week. Using flow data, we showed that we needed more nurses, more care team members during peak times of patient flow. Eight hour shifts would allow better flexibility. We showed that the additional salary hours added to the budget would be made up for by increased revenue recognized by decreasing the number of patients who leave without being seen. Conclusion: If implemented, these changes will improve ED flow by using lean tools and principles, ultimately leading to timeliness of care, reduced waits, and improved patient experience.

Integration of naval distributed tactical training simulation system based on advanced message queuing protocol

Aiming at the problems of unreliable data transmission,poor steadiness,nonsupport of complex data types,direct couple between data transmission and exchange,a high-level method based on advanced message queuing protocol( AMQP) is proposed to integrate naval distributed tactical training simulation system after serious consideration with current information exchange features of military combat system. Transferring layer in traditional user datagram protocol is implemented by publishing and subscribing scheme of message middleware. By creating message model to standardize message structure,integration architecture is formulated to resolve potential information security risks from inconsistent data type and express data transmission. Meanwhile,a communication model is put forward based on AMQP,which is in the center position of the whole transmission framework and responsible for reliably transferring battlefield data among subsystems. Experiments show that the method can accurately post amounts of data to the subscriber without error and loss,and can get excellent real-time performance of data exchange.

Queuing Management in Wireless Sensor Networks for QoS Measurement

Data transmission in multimedia WSNs are required high bandwidth and reliable transfer because of large amount of data size. However, some applications of WSNs are required high quality. In this context, main factor in quality of services (QoS) metrics in WSNs becomes longevity of the network and high quality. In sensor nodes, choosing relevant transceiver and microcontroller components plays important role in assembling sensor devices, in which data controls should be designed so that packet loss is minimized. Available QoS metrics based on queuing/buffer management in wired and other wireless networks don’t applicable in WSNs because of its unique characteristics. In this paper the simplest model of QoS model-bufferless system were proposed. In the proposed model, measurement of the probability of blocking of the arrival packets was suggested by using queuing theory in order to increase QoS. Given probability of blocking (PB) illustrates clear picture how system specification should be chosen so that blocking state would be minimized.

The Effect of Queuing Mechanisms First in First out (FIFO), Priority Queuing (PQ) and Weighted Fair Queuing (WFQ) on Network’s Routers and Applications

The paper presents the simulation results of the comparison of three Queuing Mechanisms, First in First out (FIFO), Priority Queuing (PQ), and Weighted Fair Queuing (WFQ). Depending on their effects on the network’s Routers, the load of any algorithm of them over Router’s CPUs and memory usage, the delay occurred between routers when any algorithm has been used and the network application throughput. This comparison explains that, PQ doesn’t need high specification hardware (memory and CPU) but when used it is not fair, because it serves one application and ignore the other application and FIFO mechanism has smaller queuing delay, otherwise PQ has bigger delay.

Hospital Bed Allocation Strategy Based on Queuing Theory during the COVID-19 Epidemic

During the current epidemic,it is necessary to ensure the rehabilitation treatment of children with serious illness.At the same time,however,it is essential to effectively prevent cross-infection and prevent infections from occurring within the hospital setting.To resolve this contradiction,the rehabilitation department of Nanjing Children’s Hospital adjusted its bed allocation based on the queuing model,with reference to the regional source and classification of the children’s conditions in the rehabilitation department ward.The original triple rooms were transformed into a double room to enable the treatment of severely sick children coming from other places.A M/G/2 queuing model with priority was also applied to analyze the state of patient admissions.Moreover,patients in Nanjing were also classified into mild and severe cases.The M/M/1 queuing model with priority was used for analysis of this situation,so that severely ill children could be treated in time while patients with mild symptoms could be treated at home.This approach not only eases the bed tension in the ward,but also provides suitable conditions for controlling cross-infection.

Using multi-class queuing network to solve performance models of e-business sites

Due to e-business' s variety of customers with different navigational patterns and demands, multiclass queuing network is a natural performance model for it. The open multi-class queuing network(QN) models are based on the assumption that no service center is saturated as a result of the combined loads of all the classes. Several formulas are used to calculate performance measures, including throughput, residence time, queue length, response time and the average number of requests. The solution technique of closed multi-class QN models is an approximate mean value analysis algorithm (MVA) based on three key equations, because the exact algorithm needs huge time and space requirement. As mixed multi-class QN models, include some open and some closed classes, the open classes should be eliminated to create a closed multi-class QN so that the closed model algorithm can be applied. Some corresponding examples are given to show how to apply the algorithms mentioned in this article. These examples indicate that multi-class QN is a reasonably accurate model of e-business and can be solved efficiently.

Semi-Markovian Model of Two-Line Queuing System with Losses

In the present paper, to build model of two-line queuing system with losses GI/G/2/0, the approach introduced by V.S. Korolyuk and A.F. Turbin, is used. It is based on application of the theory of semi-Markov processes with arbitrary phase space of states. This approach allows us to omit some restrictions. The stationary characteristics of the system have been defined, assuming that the incoming flow of requests and their service times have distributions of general form. The particular cases of the system were considered. The used approach can be useful for modeling systems of various purposes.

Performance Analysis for Multimedia Communication Systems with a Multilayer Queuing Network Model

Software performance evaluation in multimedia communication systems is typically formulated into a multi-layered client-server queuing network(MLCSQN) problem. However, the existing analytical methods to MLCSQN model cannot provide satisfactory solution in terms of accuracy, convergence and consideration of interlocking effects. To this end, this paper proposes a heuristic solving method for MLCSQN model to boost the performance prediction of distributed multimedia software systems. The core concept of this method is referred to as the basic model, which can be further decomposed into two sub-models: client sub-model and server sub-model. The client sub-model calculates think time for server sub-model, and the server sub-model calculates waiting time for client sub-model. Using a breadthfirst traversal from leaf nodes to the root node and vice versa, the basic model is then adapted to MLCSQN, with net sub-models iteratively resolved. Similarly, the interlocking problem is effectively addressed with the help of the basic model. This analytical solver enjoys advantages of fast convergence, independence on specific average value analysis(MVA) methods and eliminating interlocking effects.Numerical experimental results on accuracy and computation efficiency verify its superiority over anchors.

Implementation and Evaluation of Dynamically Weighted Low Complexity Fair Queuing(DWLC-FQ) Algorithm for Packet Scheduling in WiMAX Networks

Services provided by internet need guaranteed network performance. Efficient packet queuing and scheduling schemes play key role in achieving this. Internet engineering task force(IETF) has proposed Differentiated Services(Diff Serv) architecture for IP network which is based on classifying packets in to different service classes and scheduling them. Scheduling schemes of today's wireless broadband networks work on service differentiation. In this paper, we present a novel packet queue scheduling algorithm called dynamically weighted low complexity fair queuing(DWLC-FQ) which is an improvement over weighted fair queuing(WFQ) and worstcase fair weighted fair queuing+(WF2Q+). The proposed algorithm incorporates dynamic weight adjustment mechanism to cope with dynamics of data traffic such as burst and overload. It also reduces complexity associated with virtual time update and hence makes it suitable for high speed networks. Simulation results of proposed packet scheduling scheme demonstrate improvement in delay and drop rate performance for constant bit rate and video applications with very little or negligible impact on fairness.

Modeling and analysis of multiservice queuing system for WiMAX network

An analytical queuing model is proposed for the classified services of WiMAX network. Simulation model is also developed that corresponds to the Markovian analytical model using Java modeling tool （JMT）. This is a new and efficient discrete event tool for queuing network modeling and workload analysis. QoS metrics have been evaluated for the multi-rate traffic in multiple scenari- os. Results obtained from simulation are compared for validation and analysis. Outcomes show that the proposed model is more efficient than the conventional method by improving residence time, re- sponse time, increasing system throughput and efficiency at queuing level with a slight degradation in call acceptance factor.

Neural Network Based Scheduling for Variable-Length Packets in Gigabit Router with Crossbar Switch Fabric and Input Queuing

A high-speed and effective packet scheduling method is crucial to the performance of Gigabit routers. The paper studies the variable-length packet scheduling problem in Gigabit router with crossbar switch fabric and input queuing, and a scheduling method based on neural network is proposed. For the proposed method, a scheduling system structure fit for the variable-length packet case is presented first, then some rules for scheduling are given. At last, an optimal scheduling method using Hopfield neural network is proposed based on the rules. Furthermore, the paper discusses that the proposed method can be realized by hardware circuit. The simulation result shows the effectiveness of the proposed method.

Ergodicity and Invariance of Flows in Queuing Systems

In this paper, we investigate the flow of customers through queuing systems with randomly varying intensities. The analysis of the Kolmogorov-Chapman system of stationary equations for this model showed that it is not possible to construct a convenient symbolic solution. In this paper an attempt is made to circumvent this requirement by referring to the ergodicity theorems, which gives the conditions for the existence of the limit distribution in the service processes, but do not require knowledge of them.

On One Model of Complex Technical Queuing System with Unreliable Devices and with Time Redundancy

The given article deals with the development of analytical model of request service process by multichannel technical system with unreliable, repaired and reconfigured service facilities. It is assumed that the system is functioning in service mode of random length random request flows. The system considers the existence of time redundancy for afterservice of calls, the service of which is interrupted with refusal, non-depreciating the performed part of the task. Special probability functions are introduced which on the basis of probability reasoning allow to make the systems of integral equations describing the dynamics of request service process.

Improving Queuing System Throughput Using Distributed Mean Value Analysis to Control Network Congestion

In this paper, we have used the distributed mean value analysis (DMVA) technique with the help of random observe property (ROP) and palm probabilities to improve the network queuing system throughput. In such networks, where finding the complete communication path from source to destination, especially when these nodes are not in the same region while sending data between two nodes. So, an algorithm is developed for single and multi-server centers which give more interesting and successful results. The network is designed by a closed queuing network model and we will use mean value analysis to determine the network throughput (b) for its different values. For certain chosen values of parameters involved in this model, we found that the maximum network throughput for β≥0.7?remains consistent in a single server case, while in multi-server case for β≥ 0.5?throughput surpass the Marko chain queuing system.