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.

Queuing theory based analysis for packet jitter of mixed services

Exploring theory and methods to analyze the impacts of non real-time services on jitter performance of real-time services is a quite challenging but meaningful job. This article puts forward a general theoretical method to calculate packet jitter in network node bearing mixed services. Based on queuing theory and Markov theory, the network node is modeled as a double-queue single-server and limited-cache queuing system with thresholds. Two-state Markov-modulated Bernoulli process （MMBP-2） and interrupted Bernoulli process （IBP） are used to model the arrival processes of real-time services and small data services respectively in a packet switched network. In order to depict the interaction between real-time services and small data services, a four-dimensional discrete-time Markov chain is implemented to describe the transition of the system states. By solving the system model, expressions for packet jitter are obtained. The results given by the model are then compared with the simulation results obtained by network simulator, version 3 （NS-3）.

An Energy-Saving Task Scheduling Strategy Based on Vacation Queuing Theory in Cloud Computing

High energy consumption is one of the key issues of cloud computing systems. Incoming jobs in cloud computing environments have the nature of randomness, and compute nodes have to be powered on all the time to await incoming tasks. This results in a great waste of energy. An energy-saving task scheduling algorithm based on the vacation queuing model for cloud computing systems is proposed in this paper. First, we use the vacation queuing model with exhaustive service to model the task schedule of a heterogeneous cloud computing system.Next, based on the busy period and busy cycle under steady state, we analyze the expectations of task sojourn time and energy consumption of compute nodes in the heterogeneous cloud computing system. Subsequently, we propose a task scheduling algorithm based on similar tasks to reduce the energy consumption. Simulation results show that the proposed algorithm can reduce the energy consumption of the cloud computing system effectively while meeting the task performance.

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.

Coordinated Voltage Control of Distribution Network ConsideringMultiple Types of Electric Vehicles

The couple between the power network and the transportation network(TN)is deepening gradually with the increasing penetration rate of electric vehicles(EV),which also poses a great challenge to the traditional voltage control scheme.In this paper,we propose a coordinated voltage control strategy for the active distribution networks considering multiple types of EV.In the first stage,the action of on-load tap changer and capacitor banks,etc.,are determined by optimal power flow calculation,and the node electricity price is also determined based on dynamic time-of-use tariff mechanism.In the second stage,multiple operating scenarios of multiple types of EVs such as cabs,private cars and buses are considered,and the scheduling results of each EV are solved by building an optimization model based on constraints such as queuing theory,Floyd-Warshall algorithm and traffic flow information.In the third stage,the output power of photovoltaic and energy storage systems is fine-tuned in the normal control mode.The charging power of EVs is also regulated in the emergency control mode to reduce the voltage deviation,and the amount of regulation is calculated based on the fair voltage control mode of EVs.Finally,we test the modified IEEE 33-bus distribution system coupled with the 24-bus Beijing TN.The simulation results show that the proposed scheme can mitigate voltage violations well.

Coordinated scheduling model for intermodal transit hubs based on GI/M^K/1 queuing system

Coordinated scheduling of multimode plays a pivotal role in the rapid gathering and dissipating of passengers in transport hubs. Based on the survey data, the whole-day reaching time distribution at transfer points of passengers from the dominant mode to the connecting mode was achieved. A GI/M K/1 bulk service queuing system was constituted by putting the passengers' reaching time distribution as the input and the connecting mode as the service institution. Through queuing theory, the relationship between average queuing length under steady-state and headway of the connecting mode was achieved. By putting the minimum total cost of system as optimization objective, the headway as decision variable, a coordinated scheduling model of multimode in intermodal transit hubs was established. At last, a dynamic scheduling strategy was generated to cope with the unexpected changes of the dominant mode. The instance analysis indicates that this model can significantly reduce passengers' queuing time by approximately 17% with no apparently increase in departure frequency, which provides a useful solution for the coordinated scheduling of different transport modes in hubs.

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.

Analysis and Optimization of Validation Procedure in Blockchain-Enhanced Wireless Resource Sharing and Transactions

To ensure the security of resource and intelligence sharing in 6G,blockchain has been widely adopted in wireless communications and applications.Although blockchain can ensure the traceability and non-tamperability of data in the concatenated blocks,it cannot guarantee the honest behaviors of users in the application before the generation of transactions.Thus,additional technologies are required to ensure that the source of blockchain data is reliable.In this paper,the detailed procedure is designed for the application-oriented task validation in the blockchainenhanced computing resource sharing and transactions in ultra dense networks(UDN).The corresponding queuing model is built and analyzed with the consideration of the wireless re-transmission and the probability of malicious deception by users.Based on the analysis results,the UDN deployment is optimized to save network cost while ensuring latency performance.Numerical results verify our analysis,and the optimized system deployment including the number and service capacities of both base stations and mobile edge computing(MEC)servers are also given with various system settings.

Analysis on D2D Heterogeneous Networks with State-Dependent Priority Traffic

In this work,we consider the performance analysis of state dependent priority traffic and scheduling in device to device(D2D)heterogeneous networks.There are two priority transmission types of data in wireless communication,such as video or telephone,which always meet the requirements of high priority(HP)data transmission first.If there is a large amount of low priority(LP)data,there will be a large amount of LP data that cannot be sent.This situation will cause excessive delay of LP data and packet dropping probability.In order to solve this problem,the data transmission process of high priority queue and low priority queue is studied.Considering the priority jump strategy to the priority queuing model,the queuing process with two priority data is modeled as a two-dimensionalMarkov chain.A state dependent priority jump queuing strategy is proposed,which can improve the discarding performance of low priority data.The quasi birth and death process method(QBD)and fixed point iterationmethod are used to solve the causality,and the steady-state probability distribution is further obtained.Then,performance parameters such as average queue length,average throughput,average delay and packet dropping probability for both high and low priority data can be expressed.The simulation results verify the correctness of the theoretical derivation.Meanwhile,the proposed priority jump queuing strategy can significantly improve the drop performance of low-priority data.

ANALYSIS ON A TYPE OF SERVICING MACHINES MODEL WITH REPAIRABLE SERVICE STATION

This paper deals with a type of servicing machines model, which service station has a life time of the kth Er-langian distribution and can be repaired just like a new one. The cyclic time and the inefficiency quantities of this system in equilibrium are obtained.

Data Processing Model of Coalmine Gas Early-Warning System

The data processing mode is vital to the performance of an entire coalmine gas early-warning system, especially in real-time performance. Our objective was to present the structural features of coalmine gas data, so that the data could be processed at different priority levels in C language. Two different data processing models, one with priority and the other without priority, were built based on queuing theory. Their theoretical formulas were determined via a M/M/I model in order to calculate average occupation time of each measuring point in an early-warning program. We validated the model with the gas early-warning system of the Huaibei Coalmine Group Corp. The results indicate that the average occupation time for gas data processing by using the queuing system model with priority is nearly 1/30 of that of the model without priority.

Bottleneck Analysis for Data Acquisition in High-Speed Network Traffic Monitoring

The increasing network throughput challenges the current network traffic monitor systems to have compatible high-performance data processing.The design of packet processing systems is guided by the requirements of high packet processing throughput.In this paper,we depict an in-depth research on the related techniques and an implementation of a high-performance data acquisition mechanism.Through the bottleneck analysis with the aid of queuing network model,several performance optimising methods,such as service rate increasing,queue removing and model simplification,are integrated.The experiment results indicate that this approach is capable of reducing the CPU utilization ratio while improving the efficiency of data acquisition in high-speed networks.

Optimization Scheme of Large Passenger Flow in Huoying Station,Line 13 of Beijing Subway System

This paper focuses on the distribution of passenger flow in Huoying Station,Line 13 of Beijing subway system.The transformation measures taken by Line 13 since operation are firstly summarized.Then the authors elaborate the facilities and equipment of this station,especially the node layout and passenger flow field.An optimization scheme is proposed to rapidly distribute the passenger flow in Huoying Station by adjusting the operation time of the escalator in the direction of Xizhimen.The authors adopt Queuing theory and Anylogic simulation software to simulate the original and the optimized schemes of Huoying Station to distribute the passenger flow.The results of the simulation indicate that the optimized scheme could effectively alleviate the traffic congestion in the hall of Huoying Station,and the pedestrian density in other places of the hall is lowered;passengers could move freely in the hall and no new congestion points would form.The rationality of the scheme is thus proved.

Modeling of fast charging station equipped with energy storage

The popularization of EVs(electric vehicles) has brought an increasingly heavy burden to the development of charging facilities. To meet the demand of rapid energy supply during the driving period, it is necessary to establish a fast charging station in public area. However, EVs arrive at the charging station randomly and connect to the distribution network for fast charging, it causes the grid power to fluctuate greatly and the peak-valley loads to alternate frequently, which is harmful to the stability of distribution network. In order to reduce the power fluctuation of random charging, the energy storage is used for fast charging stations. The queuing model is determined to demonstrate the load characteristics of fast charging station, and the state space of fast charging station system is described by Markov chain. After that the power of grid and energy storage is quantified as the number of charging pile, and each type of power is configured rationally to establish the random charging model of energy storage fast charging station. Finally, the economic benefit is analyzed according to the queuing theory to verify the feasibility of the model.

A novel resource co-allocation model with constraints to budget and deadline in computational grid

To address the issue of resource co-allocation with constraints to budget and deadline in grid environments, a novel co-allocation model based on virtual resource agent was proposed. The model optimized resources deployment and price scheme through a three-side co-allocation mechanism, and applied queuing system to model the work of grid resources for providing quantitative deadline guarantees for grid applications. The validity and solutions of the model were presented theoretically. Extensive simulations were conducted to examine the effectiveness and the performance of the model by comparing with other co-allocation policies in terms of deadline violation rate, resource benefit and resource utilization. Experimental results show that compared with the three typical co-allocation policies, the proposed model can reduce the deadline violation rate to about 3.5% for the grid applications with constraints to budget and deadline. Also, the system benefits can be increased by about 30% compared with the those widely-used co-allocation policies.

Component-based software reliability process simulation considering imperfect debugging

In view of the flaws of component-based software （CBS） reliability modeling and analysis, the low recognition degree of debugging process, too many assumptions and difficulties in obtaining the solution, a CBS reliability simulation process is presented incorporating the imperfect debugging and the limitation of debugging resources. Considering the effect of imperfect debugging on fault detec- tion and correction process, a CBS integration testing model is sketched by multi-queue muhichannel and finite server queuing model （MMFSQM）. Compared with the analytical method based on pa- rameters and other nonparametric approaches, the simulation approach can relax more of the usual reliability modeling assumptions and effectively expound integration testing process of CBS. Then, CBS reliability process simulation procedure is developed accordingly. The proposed simulation ap- proach is validated to be sound and effective by simulation experiment studies and analysis.

Probabilistic model for remain passenger queues at subway station platform

The remain passenger problem at subway station platform was defined initially,and the period variation of remain passenger queues at platform was investigated through arriving and boarding analyses.Taking remain passenger queues at platform as dynamic stochastic process,a new probabilistic queuing method was developed based on probabilistic theory and discrete time Markov chain theory.This model can calculate remain passenger queues while considering different directions.Considering the stable or variable train arriving period and different platform crossing types,a series of model deformation research was carried out.The probabilistic approach allows to capture the cyclic behavior of queues,measures the uncertainty of a queue state prediction by computing the evolution of its probability in time,and gives any temporal distribution of the arrivals.Compared with the actual data,the deviation of experimental results is less than 20%,which shows the efficiency of probabilistic approach clearly.

Efficient Resource Allocation in Fog Computing Using QTCS Model

Infrastructure of fog is a complex system due to the large number of heterogeneous resources that need to be shared.The embedded devices deployed with the Internet of Things(IoT)technology have increased since the past few years,and these devices generate huge amount of data.The devices in IoT can be remotely connected and might be placed in different locations which add to the network delay.Real time applications require high bandwidth with reduced latency to ensure Quality of Service(QoS).To achieve this,fog computing plays a vital role in processing the request locally with the nearest available resources by reduced latency.One of themajor issues to focus on in a fog service is managing and allocating resources.Queuing theory is one of the most popular mechanisms for task allocation.In this work,an efficient model is designed to improve QoS with the efficacy of resource allocation based on a Queuing Theory based Cuckoo Search(QTCS)model which will optimize the overall resource management process.

NEW DYNAMIC SLOT ASSIGNMENT SCHEME OF SELF-ORGANIZED TDMA VHF DATA LINK

According to the analysis of the very high frequency (VHF) self organized time division multiple access (S TDMA) aviation data link, a new dynamic slot assignment scheme is proposed in this paper, which adopts variable data frame structure and can eliminate the effect of the idle slot on message delay. By using queue theory, the analysis models of the new scheme and previous scheme are presented, and the performance of message delay and that of system throughput are analyzed under two schemes. The simulation results show that the new scheme has a better performance than the previous one in the message delay and system throughput.