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.

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.

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.

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.

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.

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.

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.

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 scenarios. 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,response time,increasing system throughput and efficiency at queuing level with a slight degradation in call acceptance factor.

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.

Performance analysis of blockchain for civil aviation business data based on M/G/1 queuing theory

An Ethereum blockchain based on proof of stake ( PoS) consensus mechanism is used to achieve the data sharing within the civil aviation service platform for both airport group management and passengers. Considering the Gas consumption of Ethereum, the dynamic batch-service capacity constraint by the Block Gas Limit and the priority mechanism depending on the different Gas Price of transactions, M/ G/1 queuing theory with batch-service is used to construct the service model of transactions confirmation process in the proposed blockchain system, where the effects of transactions arrival rate, block capacity, service rate and number of nodes on the average confirmation time of transactions with different priority are analyzed, and eventually a performance analysis model of blockchain for civil aviation business data is proposed. The simulation results prove the usability and accuracy of the model, which can provide both theoretical basis for data sharing of civil aviation using Ethereum blockchain and the further optimization of transactions confirmation time.

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.

User-Based Discrete-Time Queuing Analysis for Opportunistic Spectrum Access in Cognitive Radio Networks

In cognitive radio networks, the spectrum utilization can be improved by cognitive users opportunistically using the idle channels licensed to the primary users. However, the new arrived cognitive users may not be able to use the channel immediately since the channel usage state is random. This will impose additional time delay for the cognitive users. Excessive waiting delay can make cognitive users miss the spectrum access chances. In this paper, a discrete-time Markov queuing model from a macro point of view is provided. Through the matrix-geometric solution theory, the average sojourn time for cognitive users in the steady state before accessing the spectrum is obtained. Given the tolerant delay of cognitive users, the macro-based throughput is derived and an access control mechanism is proposed. The numerical results show the effects of service completion probability on average sojourn time and throughput. It is confirmed that the throughput can be obviously improved by using the proposed access control mechanism. Finally, the performance evaluations based on users are compared to that based on data packets.

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.

On One Analytical Model of a Probability Estimation of Quality and Efficiency of Functioning of Complex Technical Queuing Systems

The work is dedicated to the development of analytical model of probability estimation of reliability, productivity, quality and efficiency of functioning of the complex technical queuing system consisting of the arbitrary number of marked groups of the service devises (channels, facilities, servers) differing with reliable characteristics (parameters of refusals and restorations) of forming their composition (also of arbitrary number) marked, identical, unreliable and restorable serving channels in which for serving come in requirements with intensities depending on marking of channels. In the considered system it is supposed that the currents of refusals of serving devices and currents of coming requirements are subdued to Poisson, and the currents of restorations of refused devices and the currents of services of coming requirements—exponential laws of distribution of probabilities. A stochastic process of transfers of a system by that is Markovian process with continuous time and discrete states. Correlations linking the basic parameters and exit characteristics of the systems of the pointed out type are obtained in a view of probabilities of the system location in the given moment of time in one of the possible states.

On One Model of Multichannel Queuing System with Unreliable Repairable Servers and Input Memory

The work deals with the development of analytical model of multichannel technical queuing system with unreliable servers and input memory where server failure flows and incoming request flows comply with Poissonian laws, while the flows of failed facilities repairs and flows of incoming requests comply with exponential laws of probability distribution. Random process of system change-over is a Markovian process with continuous time and discrete states. Relations binding basic parameters and output characteristics of the system indicated are obtained as probabilities of system staying in the given moment in one of the possible states. The proposed model is the most generalized compared to some models known in literature which could be considered as special cases of the considered model.

Performance Analysis of Two Priority Queuing Systems in Tandem

In this paper, we consider a tandem of two head-of-line (HOL) non-preemptive priority queuing systems, each with a single server and a deterministic service-time. Two classes of traffic are considered, namely high priority and low priority traffic. By means of a generating function approach, we present a technique to derive closed-form expressions for the mean buffer occupancy at each node and mean delay. Finally, we illustrate our solution technique with some numerical examples, whereby we illustrate the starvation impact of the HOL priority scheduling discipline on the performance of the low-priority traffic stream. Our research highlights the important fact that the unfairness of the HOL priority scheduling becomes even more noticeable at the network level. Thus this priority mechanism should be used with caution.

Mathematical Modeling in Heavy Traffic Queuing Systems

In this article, modeling in queuing systems with heavy traffic customer flows is reviewed. Key areas include their limiting distributions, asymptotic behaviors, modeling issues and applications. Heavy traffic flows are features of queuing in modern communications, transportation and computer systems today. Initially, we reviewed the onset of asymptotic modeling for heavy traffic single server queuing systems and then proceeded to multi server models supporting diffusion approximations developed recently. Our survey shows that queues with heavy traffic customer flows have limiting distributions and extreme value maximum. In addition, the diffusion approximation can conveniently model performance characters such as the queue length or the waiting time distributions in these systems.

Research and Simulate the Queuing Systems Based on the Markov Chain

This paper shows the researches of the queuing theory,especially the Markov Chainand the Poison Process,and implements the efficient way of designing the queuing system.Then simulating the queuing systems based on the“Simply package”in the“Python”programming language.And the paper would discuss and analyze the differences between different queuing systems.

Dragonfly Interaction Algorithm for Optimization of Queuing Delay in Industrial Wireless Networks

In industrial wireless networks,data transmitted from source to destination are highly repetitive.This often leads to the queuing of the data,and poor management of the queued data results in excessive delays,increased energy consumption,and packet loss.Therefore,a nature-inspired-based Dragonfly Interaction Optimization Algorithm(DMOA)is proposed for optimization of the queue delay in industrial wireless networks.The term“interaction”herein used is the characterization of the“flying movement”of the dragonfly towards damselflies(female dragonflies)for mating.As a result,interaction is represented as the flow of transmitted data packets,or traffic,from the source to the base station.This includes each and every feature of dragonfly movement as well as awareness of the rival dragonflies,predators,and damselflies for the desired optimization of the queue delay.These features are juxtaposed as noise and interference,which are further used in the calculation of industrial wireless metrics:latency,error rate(reliability),throughput,energy efficiency,and fairness for the optimization of the queue delay.Statistical analysis,convergence analysis,the Wilcoxon test,the Friedman test,and the classical as well as the 2014 IEEE Congress of Evolutionary Computation(CEC)on the benchmark functions are also used for the evaluation of DMOA in terms of its robustness and efficiency.The results demonstrate the robustness of the proposed algorithm for both classical and benchmarking functions of the IEEE CEC 2014.Furthermore,the accuracy and efficacy of DMOA were demonstrated by means of the convergence rate,Wilcoxon testing,and ANOVA.Moreover,fairness using Jain’s index in queue delay optimization in terms of throughput and latency,along with computational complexity,is also evaluated and compared with other algorithms.Simulation results show that DMOA exceeds other bio-inspired optimization algorithms in terms of fairness in queue delay management and average packet loss.The proposed algorithm is also evaluated for the conflicting objectives at Pareto Front,and its analysis reveals that DMOA finds a compromising solution between the objectives,thereby optimizing queue delay.In addition,DMOA on the Pareto front delivers much greater performance when it comes to optimizing the queuing delay for industry wireless networks.