Influence de la tarification horaire sur le trafic téléphonique

As the evening peakload of trunk traffic became higher than the morning one, a new time-of-day pricing was initiated in France on June 1985. The effects of this tariff change on the traffic profile and the telephone revenues were previously estimated, using an econometric model, fitted from traffic observations provided by similar experiments carried out in Germany and Switzerland. This model, based on probabilistic choice theory, uses the Logit formulation adapted to the case of a continuous set of options (times-of-day), and provides simulations of traffic trade-offs due to changes in the time-of-day pricing. Data collected since June 1984 enable us to measure the actual effects of the new tariffication. Compared with the model forecasts, these observations show a good fitting for the 6 p.m. to 8.30 p.m. period (the 8 p.m. peak-load decrease is consistent with the forecast); in the late evening however, traffic is higher than expected. These new data allowed us to improve the formulation and the fitting of the model; these recent developments are presented here.     

New modelling strategy for representing asymmetric traffic loads on LANs

A new technique for modelling asymmetric traffic load distributions on local area networks (LANs) is presented. The traffic model which is analytical and easy to implement into discrete event computer simulations also has the benefit of providing expressions for the higher mathematical moments of the traffic load distribution.<>     

Optimal resource allocation and adaptive call admission control for voice/data integrated cellular networks

Resource allocation and call admission control (CAC) are key management functions in future cellular networks, in order to provide multimedia applications to mobiles users with quality of service (QoS) guarantees and efficient resource utilization. In this paper, we propose and analyze a priority based resource sharing scheme for voice/data integrated cellular networks. The unique features of the proposed scheme are that 1) the maximum resource utilization can be achieved, since all the leftover capacity after serving the high priority voice traffic can be utilized by the data traffic; 2) a Markovian model for the proposed scheme is established, which takes account of the complex interaction of voice and data traffic sharing the total resources; 3) optimal CAC parameters for both voice and data calls are determined, from the perspective of minimizing resource requirement and maximizing new call admission rate, respectively; 4) load adaption and bandwidth allocation adjustment policies are proposed for adaptive CAC to cope with traffic load variations in a wireless mobile environment. Numerical results demonstrate that the proposed CAC scheme is able to simultaneously provide satisfactory QoS to both voice and data users and maintain a relatively high resource utilization in a dynamic traffic load environment. The recent measurement-based modeling shows that the Internet data file size follows a lognormal distribution, instead of the exponential distribution used in our analysis. We use computer simulations to demonstrate that the impact of the lognormal distribution can be compensated for by conservatively applying the Markovian analysis results.     

A new traffic model for backbone networks and its application to performance analysis

In this paper, we present a new traffic model constructed from a random number of shifting level processes (SLP) aggregated over time, in which the lengths of the active periods of the SLP are of Pareto or truncated Pareto distribution. For both cases, the model has been proved to be asymptotically second‐order self‐similar. However, based on extensive traffic data we collected from a backbone network, we find that the active periods of the constructing SLPs can be approximated better by a truncated Pareto distribution, instead of the Pareto distribution as assumed in existing traffic model constructions. The queueing problem of a single server fed with a traffic described by the model is equivalently converted to a problem with a traffic described by Norros' model. For the tail probability of the queue length distribution, an approximate expression and upper bound have been found in terms of large deviation estimates and are mathematically more tractable than existing results. The effectiveness of the traffic model and performance results are demonstrated by our simulations and experimental studies on a backbone network. Copyright © 2007 John Wiley & Sons, Ltd.     

On the use of fractional Brownian motion in the theory ofconnectionless networks

An abstract model for aggregated connectionless traffic, based on the fractional Brownian motion, is presented. Insight into the parameters is obtained by relating the model to an equivalent burst model. Results on a corresponding storage process are presented. The buffer occupancy distribution is approximated by a Weibull distribution. The model is compared with publicly available samples of real Ethernet traffic. The degree of the short-term predictability of the traffic model is studied through an exact formula for the conditional variance of a future value given the past. The applicability and interpretation of the self-similar model are discussed extensively, and the notion of ideal free traffic is introduced     

Modeling MPEG Coded Video Traffic by Markov-Modulated Self-Similar Processes

Markov modulated self-similar processes are proposed to model MPEG video sequences that can capture the LRD (Long Range Dependency) characteristics of video ACF (Auto-Correlation Function). The basic idea is to decompose an MPEG compressed video sequence into three parts according to different motion/content complexity such that each part can individually be described by a self-similar process. Beta distribution is used to characterize the marginal cumulative distribution (CDF) of the self-similar processes. To model the whole data set, Markov chain is used to govern the transitions among these three self-similar processes. In addition to the analytical derivation, initial simulations have demonstrated that our new model can capture the LRD of ACF and the marginal CDF very well. Network cell loss rate using our proposed synthesized traffic is found to be comparable with that using empirical data as the source traffic.     

Distributed and Energy-Aware MAC for Differentiated Services Wireless Packet Networks: A General Queuing Analytical Framework

We present a novel queuing analytical framework for the performance evaluation of a distributed and energy-aware medium access control (MAC) protocol for wireless packet data networks with service differentiation. Specifically, we consider a node (both buffer-limited and energy-limited) in the network with two different types of traffic, namely, high-priority and low-priority traffic, and model the node as a MAP (Markovian arrival process)/PH (phase-type)/1/K nonpreemptive priority queue. The MAC layer in the node is modeled as a server and a vacation queuing model is used to model the sleep and wakeup mechanism of the server. We study standard exhaustive and number-limited exhaustive vacation models both in multiple vacation case. A setup time for the head-of-line packet in the queue is considered, which abstracts the contention and the back-off mechanism of the MAC protocol in the node. A nonideal wireless channel model is also considered, which enables us to investigate the effects of packet transmission errors on the performance behavior of the system. After obtaining the stationary distribution of the system using the matrix-geometric method, we study the performance indices, such as packet dropping probability, access delay, and queue length distribution, for high-priority packets as well as the energy saving factor at the node. Taking into account the bursty traffic arrival (modeled as MAP) and, therefore, the nonsaturation case for the queuing analysis of the MAC protocol, using phase-type distribution for both the service and the vacation processes, and combining the priority queuing model with the vacation queuing model make the analysis very general and comprehensive. Typical numerical results obtained from the analytical model are presented and validated by extensive simulations. Also, we show how the optimal MAC parameters can be obtained by using numerical optimization     

Packetized voice/data integrated transmission on a token passingring local area network

The performance of a token-passing ring network with packetized voice/data mixed traffic is investigated through extensive simulations. Both data and voice users are modeled in the simulations. Data users produce bursty traffic. Voice traffic is modeled as having alternating talkspurts and silences, with generation of voice packets at a constant rate during talkspurts and no packet generation during silence periods. Token passing ring local area networks are shown to effectively handle both voice and data traffic. The effects of system parameters (e.g. voice packet length, talkspurt/silence lengths, data traffic intensity, and limited exhaustive service disciplines) on network performance are discussed     

Modeling of systems with overflow multi-rate traffic

The article proposes an analytical method for determining occupancy distribution and blocking probability in systems which are offered overflow traffic composed of multi-service traffic streams. The described analytical model enables determination of parameters of traffic overflowed from primary groups in hierarchically constructed telecommunication networks. The proposed method is based on an appropriate modification of the Kaufman-Roberts recursion for the full-availability group with multi-rate traffic and uses the modified Fredericks & Hayward’s approximation. Additionally, an approximate method for dimensioning systems with multi-service overflow traffic is also presented. The analytical results of the blocking probability and the results obtained in the dimensioning processes calculated using the presented methodology are compared with the data obtained from the system simulation process.     

Internet Multicasting of IPTV With Essentially-Zero Delay Jitter

A technology for multicasting packetized multimedia streams such as IPTV over the Internet backbone is proposed and explored through extensive simulations. An RSVP or DiffServ algorithm is used to reserve resources (i.e., bandwidth and buffer space) in each packet-switched IP router in an IP multicast tree. Each IP router uses an Input-Queued (IQ) switch architecture with unity speedup. A recently proposed low-jitter scheduling algorithm is used to pre-compute a deterministic transmission schedule for each IP router. The IPTV traffic will be delivered through the multicast tree in a deterministic manner, with bounds on the maximum delay and jitter of each packet (or cell). A playback buffer is used at each destination to filter out residual network jitter and deliver a very low-jitter video stream to each end-user. Detailed simulations of an IPTV distribution network, multicasting 75 high-definition video streams over a fully-saturated IP backbone are presented. The simulations represent the transmission of 129 billion cells of real video data and where performed on a 160-node cluster computing system. In the steady-state, each IP router buffers approx. 2 cells (128 bytes) of video data per multicast output-port. The observed delay jitter is zero when a playback buffer of 15 milliseconds is used. All simulation parameters are presented.      

Fountain-inspired erasure coding for real-time traffic

An erasure correction strategy based on fountain coding is proposed for traffic with real-time requirements. A sliding window marks the range of non-expired data. Each new block entering the window is once sent as such, followed by probabilistically sending a repair packet. The repair packets are formed as a random combination of the blocks in the current window using a degree distribution as in LT coding. The performance of the method with a given channel loss probability is analyzed using a Markov chain model. The state space, however, has to be truncated for computational tractability. The truncation error is verified to be small enough by simulations. By using the analytical model the optimal degree distribution is found to be of single-degree type. The performance of the proposed scheme is compared with deterministic settings, in which repair packets are sent after fixed number of systematic packets. Further comparison is made against Raptor coding, and we note that using the presented strategy can result in better performance in some situations.     

Dimensioning an ATM switch based on a three-stage Clos interconnection network

ATM (asynchronous transfer mode) is a new technique for transmitting voice, data and video. The performance of atm networks will depend on switch structure. Performance analysis of an atm switch based on a three-stage Clos network is presented. In this paper two types of switches are studied: a switch with input queues in the switching elements and a switch with output queues. This study is at the cell level and intends to dimension the switch. First, the traffic is supposed to be uniform, cells arrive on each input according to a geometric arrival process, they are uniformly directed over all the network outputs. An analytic model is proposed for both input and output queues in the switching elements. A study of the saturation throughput is proposed for input buffer switching elements. This work proves the influence of buffer dimensioning on the different stages of the switch. Dissymmetric switching elements are shown to be better than symmetric ones. A model is then designed for nonuniform traffic patterns and output buffers. Two types of non-uniform traffic are presented: single source to single destination (sssd) and multi-hot spots traffic (mhs). Discrete event simulations are used to validate the different models.     

The Rician inverse Gaussian distribution: a new model for non-Rayleigh signal amplitude statistics.

In this paper, we introduce a new statistical distribution for modeling non-Rayleigh amplitude statistics, which we have called the Rician inverse Gaussian (RiIG) distribution. It is a mixture of the Rice distribution and the inverse Gaussian distribution. The probability density function (pdf) is given in closed form as a function of three parameters. This makes the pdf very flexible in the sense that it may be fitted to a variety of shapes, ranging from the Rayleigh-shaped pdf to a noncentral chi2-shaped pdf. The theoretical basis of the new model is quite thoroughly discussed, and we also give two iterative algorithms for estimating its parameters from data. Finally, we include some modeling examples, where we have tested the ability of the distribution to represent locale amplitude histograms of linear medical ultrasound data and single-look synthetic aperture radar data. We compare the goodness of fit of the RiIG model with that of the K model, and, in most cases, the new model turns out as a better statistical model for the data. We also include a series of log-likelihood tests to evaluate the predictive performance of the proposed model.     

Kinetic parameter estimation from renal measurements with a three-headed SPECT system: a simulation study

We present here a direct least-squares estimation (DLSE) method for the determination of renal kinetic parameters from sequences of very fast acquisitions performed with a three-headed single photon emission computed tomography (SPECT) system. A simple linear model for the behavior of the radiopharmaceutical, as well as a spatial model for its spatial distribution are defined. The model enables one to estimate the kinetic parameters directly from the projections, once the plasma concentration function is known. A new technique for the accurate reconstruction of time-radioactivity curves based on the direct reconstruction of the region-of-interest contents from a series of data from three-projections is presented. The technique is used to determine the plasma concentration function with a sub-second time resolution. The spatially-variant geometrical response is also included in the model to compensate for the spatial resolution of the SPECT system. Results obtained from simulations are presented. Basic spatial and time features of the simulations are derived from a patient study. Noise and segmentation errors are also simulated. The DLSE method is compared with the conventional one of deriving kinetic parameters from the time series of reconstructed images. The standard deviation of results given by DLSE is less than 2%, whereas with the conventional method it is between 5% and 6%. Within the limit of statistical fluctuations, DLSE results are unbiased whereas those of the conventional method are overestimated by 24%.     

Analyzing Control Traffic Overhead versus Mobility and Data Traffic Activity in Mobile Ad-Hoc Network Protocols

This paper proposes a general, parameterized model for analyzing protocol control overhead in mobile ad-hoc networks. A probabilistic model for the network topology and the data traffic is proposed in order to estimate overhead due to control packets of routing protocols. Our analytical model is validated by comparisons with simulations, both taken from literature and made specifically for this paper. For example, our model predicts linearity of control overhead with regard to mobility as observed in existing simulations results. We identify the model parameters for protocols like AODV, DSR and OLSR. Our model then allows accurate predictions of which protocol will yield the lowest overhead depending on the node mobility and traffic activity pattern.     

Throughput analysis of the IEEE 802.4 priority scheme

The IEEE 802.4 token bus standard defines an optional priority scheme to handle multiple classes of data. It allocates the channel bandwidth among different priority classes of messages by a set of timers at each station. An analytical model for the priority scheme is presented. The model relates the throughput of each priority class of messages to the traffic intensities of different classes, the target rotation times, and the high-priority token holding time. The network is assumed to be symmetric with respect to its parameters and the traffic distribution among nodes. Simulation results are used to evaluate the accuracy of the model. The model provides means of evaluating the network throughput and can be used to determine the time values to meet the throughput requirements of different classes of traffic     

时间分辨反射确定生物组织光学参数的研究

从半无限大生物组织出发．研究了从总时间分辨反射确定组织光学参数的方法：将总时间分辨反射漫射理论的结果与Monte Carlo模拟的结果进行了比较．零边界条件(ZBC)和外推边界条件(EBC)的漫射方程对Monte Carlo模拟的数据作非线性拟合确定了约化散射系数和吸收系数．对所确定的光学参数误差作了较详细的分析。研究结果表明．两个漫射模型确定吸收系数的误差小于10％,采用EBC的模型拟合约化散射系数其误差与光学参数有关,ZBC则产生较大的误差。     

A physics-based, dynamic thermal impedance model for SOI MOSFET's

A physics-based compact analytical expression for the thermal impedance of SOI MOSFET's is presented. This new model extends the steady-state thermal model of Goodson and Flik (1992) to allow for transient and ac analyses, while improving self-consistency for large devices. The modified steady-state model compares favorably to measurements. Using the software package Thermal Impedance Pre-Processor (TIPP), a multiple-pole circuit can be fitted to the thermal-impedance model. The new model is compared to three-dimensional (3-D) ANSYS transient simulations with good results. The thermal-equivalent circuit is used in conjunction with a modified version of SOISPICE to give efficient electrothermal simulations in the dc and transient regimes     

WLAN/LTE异构网络中网络选择优化算法

目前,配有多种无线接入技术的多模终端变得越来越流行,与此同时,网络运营商和服务提供商利用各种技术,力争在为用户提供无缝服务的同时,使其成本最低。为了使复杂环境下的操作标准化,3GPP目前正致力于研究IP流的移动性和移动数据卸载的解决方案。本文提出了一种在WLAN/LTE异构网络环境下接入网络选择的优化方案。方案不仅考虑了移动节点中的可用参数和它当前所关联的网络及备选网络,还对异构网络的整体性能进行了优化。文章介绍了一种基于著名的装箱问题近似解的优化模型和分布式处理信号的方案。最后用模拟器对方案进行了验证,结果表明,相比只根据本地可有信息来进行切换,上述解决方案对网络的性能有明显改善。     

Residual Life Predictions in the Absence of Prior Degradation Knowledge

Recent developments in degradation modeling have been targeted towards utilizing degradation-based sensory signals to predict residual life distributions. Typically, these models consist of stochastic parameters that are estimated with the aid of an historical database of degradation signals. In many applications, building a degradation database, where components are run-to-failure, may be very expensive and time consuming, as in the case of generators or jet engines. The degradation modeling framework presented herein addresses this challenge by utilizing failure time data, which are easier to obtain, and readily available (relative to sensor-based degradation signals) from historical maintenance/repair records. Failure time values are first fitted to a Bernstein distribution whose parameters are then used to estimate the prior distributions of the stochastic parameters of an initial degradation model. Once a complete realization of a degradation signal is observed, the assumptions of the initial degradation model are revised and improved for future predictions. This approach is validated using real world vibration-based degradation information from a rotating machinery application.