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。

Spanning tree-based algorithm for hydraulic simulation of large-scale water supply networks

With the purpose of making calculation more efficient in practical hydraulic simulations, an improved algorithm was proposed and was applied in the practical water distribution field. This methodology was developed by expanding the traditional loop-equation theory through utilization of the advantages of the graph theory in efficiency. The utilization of the spanning tree technique from graph theory makes the proposed algorithm efficient in calculation and simple to use for computer coding. The algorithms for topological generation and practical implementations are presented in detail in this paper. Through the application to a practical urban system, the consumption of the CPU time and computation memory were decreased while the accuracy was greatly enhanced compared with the present existing methods.

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 detection and correction process,a CBS integration testing model is sketched by multi-queue multichannel and finite server queuing model(MMFSQM).Compared with the analytical method based on parameters 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 approach is validated to be sound and effective by simulation experiment studies and analysis.

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.

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.

Multiple scenario simulation and optimization of an urban green infrastructure network based on complex network theory:a case study in Harbin City,China

Background:Urban green infrastructure(GI)networks play a significant role in ensuring regional ecological security;however,they are highly vulnerable to the influence of urban development,and the optimization of GI networks with better connectivity and resilience under different development scenarios has become a practical problem that urgently needs to be solved.Taking Harbin,a megacity in Northeast China,as the case study,we set five simulation scenarios by adjusting the economic growth rate and extracted the GI network in multiple scenarios by integrating the minimal cumulative resistance model and the gravity model.The low‑degree‑first(LDF)strategy of complex network theory was introduced to optimize the GI network,and the optimization effect was verified by robustness analysis.Results:The results showed that in the 5%economic growth scenario,the GI network structure was more complex,and the connectivity of the network was better,while in the other scenarios,the network structure gradually degraded with economic growth.After optimization by the LDF strategy,the average degree of the GI network in multiple scenarios increased from 2.368,2.651,2.189,1.972,and 1.847 to 2.783,3.125,2.643,2.414,and 2.322,respectively,and the GI network structure connectivity and resilience were significantly enhanced in all scenarios.Conclusions:Economic growth did not necessarily lead to degradation of the GI network;there was still room for economic development in the study area,but it was limited under existing GI conditions,and the LDF strategy was an effective method to optimize the GI network.The research results provide a new perspective for the study of GI network protection with urban economic growth and serve as a methodological reference for urban GI network optimization.

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.

Generation Reliability Evaluation in Deregulated Power Systems Using Game Theory and Neural Networks

Deregulation policy has caused some changes in the concepts of power systems reliability assessment and enhancement. In the present research, generation reliability is considered, and a method for its assessment is proposed using Game Theory (GT) and Neural Networks (NN). Also, due to the stochastic behavior of power markets and generators’ forced outages, Monte Carlo Simulation (MCS) is used for reliability evaluation. Generation reliability focuses merely on the interaction between generation complex and load. Therefore, in the research, based on the behavior of players in the market and using GT, two outcomes are considered: cooperation and non-cooperation. The proposed method is assessed on IEEE-Reliability Test System with satisfactory results. Loss of Load Expectation (LOLE) is used as the reliability index and the results show generation reliability in cooperation market is better than non-cooperation outcome.

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.

城市轨道交通预约进站配额优化研究

通勤时段客流激增,城市轨道交通车站过度拥挤,安全风险较大.除站外限流外,采用线上预约、快速进站制度可以使乘客合理规划出行时间,提升系统效能.作为1种新解决方案,预约进站制度中,预约时段选择以及预约配额设置仍缺乏科学合理的依据.为此,本研究基于智能卡数据分析通勤高峰时期乘客出行特征,确定预约时段;通过实地调研获取进站时间特征,利用排队论以最小化非预约乘客站外排队时间为目标的预约配额优化模型.以北京地铁沙河站为例,分别采用数值算法以及仿真模型实现并验证了提出模型的适用性,为城市轨道交通预约进站制度的推广应用提供科学的理论指导.

情绪视角下网络舆情发生期的演化博弈与仿真分析

在网络舆情的发生期,信息的传播更多地存在于网民群体内部,相较于政府组织,网民群体极易受到情绪因素的影响,因此分析不同情绪对网民群体决策的影响,有利于提高对网络舆情发生期的有效监管。本文将等级依赖期望效用(Rank Dependent Expected Utility,RDEU)理论与博弈理论相结合,考虑网络舆情发生期情绪因素对于网络舆情演化的影响作用,构建网民与意见领袖演化博弈模型;通过仿真实验,分析不同情绪组合下的均衡策略选择。研究结果表明:在多数情况下,情绪状态能够加快舆情的演化;相较于网民,意见领袖的情绪状态对舆情的演化结果能产生更显著的影响。

基于混沌云量子蝙蝠CNN-GRU大坝变形智能预报方法研究

针对大坝变形影响因素复杂、精准预报难度较大问题,为了提高在大坝安全管理过程中大坝变形的预报精度,本文从大坝变形非线性动力系统时间序列的强非线性出发,引入深度卷积神经网络,对大坝变形及其空间影响特性进行挖掘,引入门控循环单元,对大坝变形的时域特性进行挖掘,构建应用于大坝变形预报的深度卷积神经网络-门控循环单元大坝变形组合深度学习网络;同时,为了获取深度卷积神经网络-门控循环单元组合网络的最佳超参,引入了混沌云量子蝙蝠算法,建立了基于混沌云量子蝙蝠算法算法的深度卷积神经网络-门控循环单元组合网络超参优选方法;最后,提出了深度卷积神经网络-门控循环单元-混沌云量子蝙蝠算法大坝变形组合深度学习智能预报方法。基于实测数据开展预报研究,对比结果表明:与对比模型相比,提出的深度卷积神经网络-门控循环单元-混沌云量子蝙蝠算法预报方法取得了更精确的预报结果,混沌云量子蝙蝠算法算法用于超参优选获得了更佳的超参组合。

WBSN中一种针对重要生命信号传输的DI-RED拥塞控制算法

“互联网+医疗”的新型医护模式使无线生理传感网络(WBSN)面临着流量传输问题,其中解决重要生命信号传输的拥塞控制问题至关重要,为此提出了一种基于DI-RED拥塞控制算法。通过建立多跳的数据传输的系统模型,生物传感器收集到的多类型用户生命信息经信息融合单元进行业务分级,无循环优先级汇聚单元进行分组传输,并通过DI-RED拥塞控制单元进行主动丢弃数据分组、通知发送方降低传输速率以缓解父节点的拥塞问题。将父节点缓存中的队列到达状态、离开状态和保持状态构造成离散时间Markov链,结果采用排队论获得系统稳态和性能评价指标。所提算法的数值模拟实验验证了该算法的有效性。

D-S Evidence Theory Based Trust Ant Colony Routing in WSN

This paper proposes a trust ant colony routing algorithm by introducing a node trust evaluation model based on the D-S evidence theory into the ant colony routing protocol to improve the security of wireless sensor networks. To reduce the influence of conflict evidences caused by malicious nods, the consistent intensity is introduced to preprocess conflict evidences before using the D-S combination rule to improve the reliability of the D-S based trust evaluation. The nodes with high trust values will be selected as the routing nodes to insure the routing security, and the trust values are used as heuristic functions of the ant colony routing algorithm. The simulation tests are conducted by using the network simulator NS2 to observe the outcomes of performance metrics of packets loss rate and average end-to-end delay etc. to indirectly evaluate the security issue under the attack of inside malicious nodes. The simulation results show that the proposed trust routing algorithm can efficiently resist malicious attacks in terms of keeping performances of the average end-to-end delay, the throughtput and the routing packet overhead under attacking from malicious nodes.

Game Theoretic Simulation on the Mimicry Honeypot

A mimicry honeypot framework based on game theory is presented in our work, which can calculate the equilibrium strategy of the deceptive game using non-cooperative incomplete dynamic game theory, and make decisions for the mimicry framework to deploy the simple service, the honeypot and the fake honeypot. A mimicry prototype is implemented using NS2 platform, and simulation experiments are launched to validate the decision-making result and the deceptive performance of the mimicry honeypot. The empirical study shows that the mimicry honeypot framework based on game theory can be able to influence the equilibrium strategy results by dynamically changing the deployment vector of the mimicry system. It validates that the mimicry honeypot framework has better flexibility, activeness and fraudulence than the traditional honeypot.

Applications of Wavelets in 3-D Audio Simulation

Wavelet has been used as a powerful tool in the signal processing and function approximation recently. This paper presents the application of wavelets for solving two key problems in 3-D audio simulation. First, we employ discrete wavelet transform (DWT) combined with vector quantization (VQ) to compress audio data in order to reduce tremendous redundant data storage and transmission times. Secondly, we use wavelets as the activation functions in neural networks called feed-forward wavelet networks to approach auditory localization information cues (head-related transfer functions (HRTFs) are used here). The experimental results demonstrate that the application of wavelets is more efficient and useful in 3-D audio simulation.

Connectivity of sparse vehicular ad hoc networks with channel randomness

In this paper,we investigate the connectivity of vehicular ad hoc networks in free-flow traffic situationwith channel randomness.In order to illustrate the realistic environment,we consider that vehiclesare distributed in free-flow highway according to a Poisson point process,and signal propagation betweenconnected vehicles is subjected to log-normal shadowing effects.We obtain the distribution of the spaceheadway between successive vehicles and the distribution of signal coverage,which allows us to use theequivalent M/G/∞ queue theory to model the connectivity of VANETs in the form of average broadcastpercolation distance and average number of connected nodes.Then,extensive simulation studies are conductedto evaluate the obtained results.The analytical model presented here is able to describe the impactof various system parameters,including traffic parameters and signal propagation parameters on the connectivity.We use our analytical results,along with the common signal propagation data,to understandimpact of channel randomness on the connectivity of VANETs.

拥挤传播对汽车共享系统运行影响的仿真分析

随着共享汽车渗透率的不断增加,站点、路段层面的车辆溢出和拥挤传播现象日趋严重.为刻画拥挤传播对汽车共享系统运行的影响机理,首先,搭建具有时变性和状态相关性的汽车共享系统排队网络;其次,基于C#语言和O2DES离散事件仿真框架,提出并设计考虑车路交互影响和拥挤传播现象的汽车共享系统仿真模型,分析动态随机环境下站点与路段层面的拥挤传播现象对汽车共享系统运行的影响;最后,以成都市三站点的小规模汽车共享系统为例,在不同转运比例、需求和道路拥堵场景下,将该模型与引入虚拟空间的无穷排队模型进行对比分析.研究结果表明:站点和路段层面的拥挤传播现象会导致系统服务率下降9.3%~16.9%,相比无穷排队模型,考虑拥挤传播现象的排队模型更能反映汽车共享系统的实际运营过程;当路网的道路占用率为70%(路网处于中度拥堵)时,考虑拥挤传播现象的汽车共享系统可实现最大收益;汽车共享系统的引入会为道路资源的动态分配带来新变化,当公共交通转向汽车共享系统的用户占比超过70%时,路网拥堵加剧,不利于汽车共享系统的有效运营和可持续发展.

采选充一体化煤炭生产物流系统仿真及优化

为研究煤炭绿色化开采模式,探寻满足基本产能目标下,采选充一体化煤炭生产物流系统生产瓶颈问题,促进井下煤矸物流协同高效运输。选用山西某矿为原型,运用排队论解析该采选充一体化煤炭生产物流系统运行过程,借助Anylogic仿真软件建立离散事件模型进行相关实验优化和计算。根据仿真结果发现:智能分选系统、提升设备和破碎机为该采选充一体化煤炭生产物流系统生产瓶颈,通过进行相关优化,可提高各设备利用率,促进系统协同运行。