Preemption-Aware Instantaneous Request Call Routing for Networks With Book-Ahead Reservation

This paper presents a new preemption-aware quality of service (QoS) routing algorithm for instantaneous request (IR) call connections in a QoS-enabled network where resources are shared between IR and book-ahead (BA) call connections. BA reservation, which confirms the availability of resources in advance, is a highly attractive technique for time sensitive applications that require high amount of bandwidth with guaranteed QoS. One of the major concerns for the implementation of BA reservation is the need for preemption of on-going IR calls to accommodate BA calls when resource scarcity arises. Preemption disrupts service continuity of on-going calls which is considered as severely detrimental from users' perceived QoS definition found in recent studies. Existing QoS routing algorithms focus on resource conservation or load balancing as the key objective to attain in addition to guaranteed QoS. No works have yet focused on the preemption problem of on-going IR calls at routing stage in the presence of BA calls. We present a mathematical formulation to compute the preemption probability of an incoming IR call at routing stage based on the current IR and future BA load information. We propose a routing strategy by formulating a link cost function comprising of the calculated preemption probability of the incoming IR call and hop count. Simulation results confirm that QoS routing based on the proposed link cost function significantly outperforms widely recommended shortest path and widest path routing algorithms in terms of IR call preemption and blocking rate. The proposed approach also yields higher network utilization and IR effective throughput.     

A preemptive channel allocation scheme for multimedia traffic in mobile wireless networks

This paper presents a channel allocation model with both partial and full preemptive capabilities for multimedia traffic in mobile wireless networks. The different types of multimedia traffic in transmitting through next-generation networks possess different characteristics and demand an adequate channel allocation scheme to fulfill individual Quality of Service (QoS) requirements. In the proposed model, multimedia traffic is classified into three classes corresponding to different priority levels in a decreasing order. To effectively reduce the dropping probability, a higher-priority handoff call is allowed to fully or partially preempt any lower-priority ongoing calls when the channel capacity becomes insufficient. In addition, to prevent from possible starvation of the lowest-priority traffic, a portion of system channels are purposely reserved. Performance measures, including the dropping probability of handoff calls, the call-interruption probability that an ongoing call is forced to termination due to full preemption, and the bandwidth reduction ratio due to partial preemption, are investigated through an analytical model built with 4-D Markov chains. The numerical results demonstrate the effectiveness of our model.     

呼叫准入约束下Macro-Femto小区选择GSPN模型研究

随着数据业务快速增长,仅靠宏蜂窝网络已无法满足流量需求;飞蜂窝网络可以有效分流宏蜂窝流量, 近年来 所构成的Macro-Femto架构得到了较广泛的部署。Macro-Femto网络部署的关键问题之一是小区选择,由于飞蜂窝网络频谱资源有限,进行小区选择时仍需考虑呼叫准入控制(Call Admission Control,CAC)。图形化的广义随机Petri网(Generalized Stochastic Petri Nets,GSPN)具有并行性、不确定性和异步特性以及强大的分析复杂系统的功能。针对Macro-Femto网络的呼叫准入约束机制,通过分析呼叫对信道的占用情形,在改进呼叫重审机制的基础上,建立了呼叫准入控制策略GSPN模型。利用建立的GSPN模型,分析了不同呼叫准入控制策略对新呼叫和切换呼叫阻塞率的影响,给出了部分重审机制的呼叫准入控制策略。在分析飞蜂窝的高速服务特性和宏蜂窝的高负载能力的基础上,结合部分重审呼叫准入策略和GSPN方法,提出了基于负载的飞蜂窝优先选择方案(Load-Based Femto-Priority Selection Scheme,LFP)。仿真结果表明,较典型的飞蜂窝优先选择方案,所提出的LFP方案对新呼叫的阻塞率和切换呼叫的掉线率分别降低了2.7%和4.6%。     

Combining a neural network with a genetic algorithm for process parameter optimization

A neural-network model has been developed to predict the value of a critical strength parameter (internal bond) in a particleboard manufacturing process, based on process operating parameters and conditions. A genetic algorithm was then applied to the trained neural network model to determine the process parameter values that would result in desired levels of the strength parameter for given operating conditions. The integrated NN–GA system was successful in determining the process parameter values needed under different conditions, and at various stages in the process, to provide the desired level of internal bond. The NN–GA tool allows a manufacturer to quickly determine the values of critical process parameters needed to achieve acceptable levels of board strength, based on current operating conditions and the stage of manufacturing.     

Markov chain models of a telephone call center with call blending

Motivated by a Bell Canada call center operating in blend mode, we consider a system with two types of traffic and two types of agents. Outbound calls are served only by blend agents, whereas inbound calls can be served by either inbound-only or blend agents. Inbound callers may balk or abandon. There are several performance measures of interest, including the rate of outbound calls and the proportion of inbound calls waiting more than some fixed number of seconds. We present a collection of continuous-time Markov chain (CTMC) models which capture many real-world characteristics while maintaining parsimony that results in fast computation. We discuss and explore the tradeoffs between model fidelity and efficacy and compare our different CTMC models with a realistic simulation model of a Bell Canada call center, used as a benchmark.     

On utility-fair bandwidth adaptation for multi-class traffic QoS provisioning in wireless networks

The ability to adjust the allocated bandwidth of ongoing calls to cope with wireless network resource fluctuations is becoming increasingly important. In this paper, we describe a utility-based bandwidth adaptation scheme for multi-class traffic quality-of-service (QoS) provisioning in wireless networks. With the proposed scheme, each call is assigned a utility function according to its adaptive characteristics. Depending on the network load the allocated bandwidth of ongoing calls are upgraded or degraded dynamically such that each call receives fair utility. The quantization of utility function by dividing the utility range into a fixed number of equal intervals is a key feature of our proposed utility-fair algorithm. Appropriate call admission control and bandwidth reservation policies are also integrated into the proposed scheme to provide QoS guarantees to the new and handoff calls. Extensive simulation experiments have been conducted to evaluate the performance of the proposed scheme compared with two other existing ones. Results show that our bandwidth adaptation scheme is effective in achieving utility fairness while keeping the call blocking and handoff dropping probabilities substantially low.     

一类时变系统的多模型切换动态调节控制算法

当被控对象参数所在的不确定区域未知时, 多模型切换调节等控制算法虽然最终可以使系统达到期望特 性, 但随着不确定区域的增大, 系统需要增加大量的模型才能满足快速性等方面上的要求. 因此, 为了实现一类时 变系统在只增加少量模型时便能够满足期望控制性能的目标, 提出了多模型切换动态调节控制算法. 此算法在不 确定区域内分配若干上层模型, 在双切换机制的监督下, 利用动态分配方法, 在最优上层模型所在的子区域分配出 若干下层模型, 在与自适应模型的协作中, 设计最优控制器, 保证了系统的暂态和稳态响应. 在数值仿真与故障卫星 系统的仿真研究中, 结果表明了多模型切换动态调节算法在暂态性能方面优于多模型切换调节算法, 并验证了此算 法的有效性.     

一种计算话务量的进化神经网络方法

话务量是度量用户使用电话设备频繁程度的一个重要参量,由于目前话务分布呈现出显著的立体性、多业务性和非泊松流等特点,不能直接应用欧兰Ｂ公式进行计算。为此,从计算智能出发提出一种基于PSO算法的进化神经计算方法,主要包括话务量及其相关参量的获取、神经网络结构的优化、基于PSO算法的网络训练,以及话务量计算等步骤。通过对河北省某市小灵通业务的详细研究,利用近半年来的话务量与无线阻塞率、来话接通率和掉话率等参量构成的样本信息进行建模,所计算的话务量精度高,表明其方法切实可行且效果显著。     

Orientation tuning properties of simple cells in area V1 derived from an approximate analysis of nonlinear neural field models

We present a general approximation method for the mathematical analysis of spatially localized steady-state solutions in nonlinear neural field models. These models comprise several layers of excitatory and inhibitory cells. Coupling kernels between and inside layers are assumed to be gaussian shaped. In response to spatially localized (i.e., tuned) inputs, such networks typically reveal stationary localized activity profiles in the different layers. Qualitative properties of these solutions, like response amplitudes and tuning widths, are approximated for a whole class of nonlinear rate functions that obey a power law above some threshold and that are zero below. A special case of these functions is the semilinear function, which is commonly used in neural field models. The method is then applied to models for orientation tuning in cortical simple cells: first, to the one-layer model with "difference of gaussians" connectivity kernel developed by Carandini and Ringach (1997) as an abstraction of the biologically detailed simulations of Somers, Nelson, and Sur (1995); second, to a two-field model comprising excitatory and inhibitory cells in two separate layers. Under certain conditions, both models have the same steady states. Comparing simulations of the field models and results derived from the approximation method, we find that the approximation well predicts the tuning behavior of the full model. Moreover, explicit formulas for approximate amplitudes and tuning widths in response to changing input strength are given and checked numerically. Comparing the network behavior for different nonlinearities, we find that the only rate function (from the class of functions under study) that leads to constant tuning widths and a linear increase of firing rates in response to increasing input is the semilinear function. For other nonlinearities, the qualitative network response depends on whether the model neurons operate in a convex (e.g., x(2)) or concave (e.g., sqrt(x)) regime of their rate function. In the first case, tuning gradually changes from input driven at low input strength (broad tuning strongly depending on the input and roughly linear amplitudes in response to input strength) to recurrently driven at moderate input strength (sharp tuning, supralinear increase of amplitudes in response to input strength). For concave rate functions, the network reveals stable hysteresis between a state at low firing rates and a tuned state at high rates. This means that the network can "memorize" tuning properties of a previously shown stimulus. Sigmoid rate functions can combine both effects. In contrast to the Carandini-Ringach model, the two-field model further reveals oscillations with typical frequencies in the beta and gamma range, when the excitatory and inhibitory connections are relatively strong. This suggests a rhythmic modulation of tuning properties during cortical oscillations.     

负荷实时跟踪精细化氨法脱硫智能控制系统

传统的氨法脱硫控制系统存在延迟时间较长、无法实现实时跟踪负荷的局限性。针对该问题提出的Smith预估补偿装置,通过抵消系统中的纯滞后环节来提高控制系统的实时性。虽然该方法有效解决了长延时问题,但系统中PID参数调整采用的是试错法并依赖于调试操作经验,偶然性和因人而异导致系统波动较大。本文提出了BP（back propagation）神经网络的PID参数整定方法,该方法能实现对任意非线性函数的逼近,通过神经网络学习得到最佳的比例、微分、积分系数组合。运用该方法建模并进行长时过程控制仿真,结果验证了算法的可行性,其误差小,大幅提高了氨法脱硫系统的实时性和稳定性,实现了智能化精准控制效果。     

Bandwidth Management for Supporting Differentiated Service Aware Traffic Engineering

This paper presents a bandwidth management framework for the support of differentiated-service-aware traffic engineering (DS-TE) in multiprotocol label switching (MPLS) networks. Our bandwidth management framework contains both bandwidth allocation and preemption mechanisms in which the link bandwidth is managed in two dimensions: class type (CT) and preemption priority. We put forward a Max-Min bandwidth constraint model in which we propose a novel "use it or lend it" strategy. The new model is able to guarantee a minimum bandwidth for each CT without causing resource fragmentation. Furthermore, we design three new bandwidth preemption algorithms for three bandwidth constraint models, respectively. An extensive simulation study is carried out to evaluate the effectiveness of the bandwidth constraint models and preemption algorithms. When compared with the existing constraint models and preemption rules, the proposed Max-Min constraint model and preemption algorithms improve not only bandwidth efficiency, but also robustness and fairness. They achieve significant performance improvement for the well-behaving traffic classes in terms of bandwidth utilization and bandwidth blocking and preemption probability. We also provide guidelines for selecting different DS-TE bandwidth management mechanisms.     

面向无线移动网络的资源管理研究

文中分析了无线移动网络中资源管理面临的新问题，针对移动相关服务类型和主动／被动预留相结合的资源预留模式，研究了链路资源在MGS、MAS和BE三种业务流之间以及在新请求和切换请求之间的分配策略和管理办法，给出了MGS和MAS的接纳控制算法，并提出了根据网络实际流量特点进行资源调整的方法。     

一种提高无线网络语音通话数量的方法

语音通话(Voice over IP)已经成为无线局域网中的一种重要的应用,并且近年来得到了越来越广泛的关注.分析了无线局域网所能支持的语音通话的最大数量,并在网络仿真器NS2上建立了IEEE 802.11语音通话的仿真模型根据仿真分析结果,提出一种自适应传输间隔接入控制方法,提高了IEEE 802.11无线局域网支持语音通话的数量.在自适应传输间隔接入控制方法中,基站(Base Station)通过监测网络冲突概率,自适应的改变网络中语音通话的传输间隔,使网络始终工作在非饱和状态.仿真实验结果表明,提出的白适应传输间隔接入控制方法不仅能够保证IEEE 802.11无线局域网中语音通话的质量,还可以增加网络所能支持语音通话的数量.     

航空发动机分数阶PID控制器的参数自整定方法

控制器作为航空发动机的大脑,是保障发动机正常运行的核心部件,随着对发动机控制器精度和时效性的要求越来越高,传统PID控制器的性能亟需进一步提升.本文提出了改进的分数阶PID离线和在线参数整定方法,应用于涡扇发动机推力的控制中.首先,利用Caputo分数阶微积分定义建立分数阶PID模型,实现时域上的数值计算;其次,基于对数正态分布提出了改进的布谷鸟算法,实现了分数阶PID离线参数整定;然后,结合RBF网络设计参数线上整定方法,解决了参数在线整定问题;最后将相关理论应用于发动机推力的控制中,结果表明,相比其他几种优化算法,改进的布谷鸟优化算法对分数阶PID控制参数整定效果最好;利用RBF神经网络对分数阶PID进行在线整定时控制效果稳定,且分数阶PID的控制效果优于传统的PID控制,能提高对推力的控制能力.     

Tuning SISO offset-free Model Predictive Control based on ARX models

In this paper, we present a tuning methodology for a simple offset-free SISO Model Predictive Controller (MPC) based on autoregressive models with exogenous inputs (ARX models). ARX models simplify system identification as they can be identified from data using convex optimization. Furthermore, the proposed controller is simple to tune as it has only one free tuning parameter. These two features are advantageous in predictive process control as they simplify industrial commissioning of MPC. Disturbance rejection and offset-free control is important in industrial process control. To achieve offset-free control in face of unknown disturbances or model-plant mismatch, integrators must be introduced in either the estimator or the regulator. Traditionally, offset-free control is achieved using Brownian disturbance models in the estimator. In this paper we achieve offset-free control by extending the noise model with a filter containing an integrator. This filter is a first order ARMA model. By simulation and analysis, we argue that it is independent of the parameterization of the underlying linear plant; while the tuning of traditional disturbance models is system dependent. Using this insight, we present MPC for SISO systems based on ARX models combined with the first order filter. We derive expressions for the closed-loop variance of the unconstrained MPC based on a state space representation in innovation form and use these expressions to develop a tuning procedure for the regulator. We establish formal equivalence between GPC and state space based off-set free MPC. By simulation we demonstrate this procedure for a third order system. The offset-free ARX MPC demonstrates satisfactory set point tracking and rejection of an unmeasured step disturbance for a simulated furnace with a long time delay.     

HUSEC: A heuristic self configuration model for wireless sensor networks

The Network State Beacons (NSB) exchange rate is the critical parameter in monitoring the dynamic state of any self-configuring ad hoc sensor network. Along with the network state and the overhead control traffic, it determines both the time and nature of any proactive reconfiguration activity that is necessary to counteract any degradation in network performance. While traditionally selected at random, this rate of beacon exchange significantly affects the accuracy with which the variations in network state are tracked. It is therefore imperative to adapt this rate to the variation in load profile and attempt to maintain its value within predefined bounds which can be optimised to keep the network operating quiescently, while conforming to its various Quality-of-Service (QoS) requirements. This paper presents a novel, heuristic self-configuration (HUSEC) model which addresses this optimisation problem. The simulation results confirm that the model reconfigures the network more effectively to not only achieve higher throughput, but also greater network integrity, with minimal control traffic and resource overheads.     

A neural network model of the Eriksen task: reduction, analysis, and data fitting

We analyze a neural network model of the Eriksen task: a two-alternative forced-choice task in which subjects must correctly identify a central stimulus and disregard flankers that may or may not be compatible with it. We linearize and decouple the model, deriving a reduced drift-diffusion process with variable drift rate that describes the accumulation of net evidence in favor of either alternative, and we use this to analytically describe how accuracy and response time data depend on model parameters. Such analyses both assist parameter tuning in network models and suggest explanations of changing drift rates in terms of attention. We compare our results with numerical simulations of the full nonlinear model and with empirical data and show good fits to both with fewer parameters.     

IMC based Robust PID design: Tuning guidelines and automatic tuning

This communication addresses the problem of tuning a PID controller for step response. The tuning is based upon a First Order Plus Time Delay (FOPTD) model and aims to achieve a step response specification while taking into account robustness considerations. The industrial ISA-PID formulation is chosen. A tuning rule is derived first where the four parameters of the ISA-PID are determined by means of two new parameters: one parameter is related to the desired closed-loop time constant and the other one to the robustness level. On a second step, these two parameters are set to a fixed value in order to get a simple and automatic rule that directly gives the controller parameters in terms of the process model parameters. The proposed automatic tuning rule is compared with other known tunings.     

一种新型实时调度算法研究

在许多片上特定应用系统中，任务多且切换频繁，任务切换开销大，有时甚至严重影响系统的可调度性．研究了动态可抢占门限调度算法，它通过初始门限值、动态门限值的计算和优化线程分配，实现了在处理器高利用率下，有效降低任务切换开销的目的，并相应地减少了对内存的需求．动态可抢占门限调度算法是将静态抢占门限算法与动态调度算法有机地结合在一起。完成了由静态到动态无缝转换．     

Analysis and optimization of Guard Channel Policy in cellular mobile networks with account of retrials

A multi-server retrial queue with two types of calls (handover and new calls) is analyzed. This queue models the operation of a cell of a mobile communication network. Calls of two types arrive at the system according to the Marked Markovian Arrival Process. Service times of both types of the calls are exponentially distributed with different service rates. Handover calls have priority over new calls. Priority is provided by means of reservation of several servers of the system exclusively for service of handover calls. A handover call is dropped and leaves the system if all servers are busy at the arrival epoch. A new call is blocked if all servers available to new calls are busy. Such a call has options to balk (to leave the system without getting the service) or to retry later on. The behavior of the system is described by the four-dimensional Markov chain belonging to the class of the asymptotically quasi-Toeplitz Markov chains (AQTMC). In the paper, a constructive ergodicity condition for this chain is derived and the effective algorithm for computing the stationary distribution is presented. Based on this distribution, formulas for various performance measures of the system are obtained. Results of numerical experiments illustrating the behavior of key performance measures of the system depending on the number of the reserved servers under the different shares of the handover and the new calls are presented. An optimization problem is considered and high positive effect of server's reservation is demonstrated.