Cross-Layer optimal connection admission control for variable bit rate multimedia traffic in packet wireless CDMA networks

Next generation wireless code division multiple access (CDMA) networks are required to support packet multimedia traffic. This paper addresses the connection admission control problem for multiservice packet traffic modeled as Markov modulated Poisson process (MMPP) with the quality of service (QoS) requirements on both physical layer signal-to-interference ratio (SIR) and network layer blocking probability. Optimal linear-programming-based algorithms are presented that take into account of SIR outage probability constraints. By exploiting the MMPP traffic models and introducing a small SIR outage probability, the proposed algorithms can dramatically improve the network utilization. In addition, we propose two reduced complexity algorithms that require less computation and can have satisfactory approximation to the optimal solutions. Numerical examples illustrating the performance of the proposed schemes are presented.     

Calculation of Loss Probability in a Finite Size Partitioned Buffer for Quantitative Assured Service

This paper proposes an approximate yet accurate approach to calculate the loss probabilities in a finite size partitioned buffer system for the achievement of a quantitative assured service in differentiated services networks. The input is modeled as a fractional Brownian motion (FBM) process including J classes of traffic with different packet loss requirements. A first-in first- out buffer partitioned with J-1 thresholds is used to provide J loss priorities. Heuristic expressions of the loss probabilities for all the J classes are derived, and validated by computer simulations. The proposed loss calculation technique is then extended to a general input process by using the recently proposed traffic substitution technique, where both long-range dependent and short-range dependent input sources are equivalent to a properly parameterized FBM. We also apply the loss calculation to admission control, where the partition thresholds are optimally configured for quality of service guarantee and maximal resource utilization. Computer simulation results demonstrate that resource allocation based on the accurate finite buffer loss analysis results in much more efficient resource utilization than that based on the classic large-buffer overflow approximation.     

Performance analysis for hierarchical multirate loss networks

The reduced load approximation technique has been extensively applied to flat networks, but the feasibility of applying it to hierarchical network model has seldom been described. Hierarchical routing is essential for large networks such as the Internet inter/intra-domain routing hierarchy and the Private Network to Node Interface (PNNI) standard. Therefore, this paper proposes an efficient and accurate analytical model for evaluating the performance of hierarchical networks with multiple classes of traffic. A performance analysis model with considering multiple classes of traffic, the complexity of analytical and explosion of computation will be extremely increased, and hence, result in inaccurate analytical. The issue of multiple classes of traffic has to be addressed in performance analysis model. In this paper, we first study the reduced load approximation model for loss networks, and then propose a novel performance evaluation model for large networks with multirate hierarchical routing. The hierarchical evaluation model is based on decomposing a hierarchical route into several analytic hierarchical segments. Once the blockings of these hierarchical segments are accurately determined, the blocking of the hierarchical path can be estimated accurately from these segments blocking. Numerical results indicate that the proposed hierarchical reduced load approximation yields quite accurate blocking probabilities as compared to that of simulation results. Furthermore, the accuracy of the proposed hierarchical reduced load approximation heuristic is independent of the blocking or the offered traffic load. Finally, we also draw some remarks on the convergence of the reduced load based approximation analysis model.     

Approximation techniques for computing packet loss infinite-buffered voice multiplexers

Three different approximation techniques are examined. The performance models studied differ primarily in the manner in which the superposition of the voice sources (i.e., the arrival process) is modeled. The first approach models the superimposed voice sources as a renewal process, and performance calculations are based only on the first two moments of the renewal process. The second approach is based on modeling the superimposed voice sources as a Markov modulated Poisson process (MMPP). The choice of parameters for the MMPP attempts to capture aspects of the arrival process in a more intuitive manner than previously proposed approaches for determining the MMPP parameters and is shown to compute loss more accurately. Finally, a fluid flow approximation for computing packet loss is evaluated. For all three approaches, a unifying example, the case of multiplexing voice sources over a T1-rate link is considered. The main conclusion is that both the MMPP model and the fluid flow approximation can provide accurate loss predictions for parameter ranges of practical interest     

DDD Network Optimization in Field Engineering--From Theory to Application

This paper deals with some important practical applications of teletraffic theory to field engineering problems. It is shown that the following tasks concerning line switching telephone networks can be mastered by means of a few handy tables: loss calculation and dimensioning of trunk groups for full or limited access; very accurate loss approximation of link systems with an arbitrary number of stages, operating as group selection or traffic concentrating arrays with point-to-group selection mode (regarding this, and also optimal link structures, wiring, etc., see [7] in this issue); dimensioning groups with limited or full access for offered peaked overflow traffic; cost minimizing partition of the traffic in local or toll networks with alternate routing to the various trunk groups; and computerized dimensioning is of course also possible.     

Blocking probability evaluation of end-to-end dynamic WDM networks

Two mathematical methods for blocking probability evaluation of end-to-end dynamic WDM networks are proposed. The first method can be applied to networks operating with static (fixed) routes. By diminishing the impact of the link independence assumption, the method proposed improves a recently proposed mathematical procedure that assumes link blocking independency and non-Poisson traffic. To do so, the so-called streamline effect is taken into account in the equations. As a result, values closer to that of simulation are obtained. The second method applies to networks operating with alternate routing. In this case, the method simultaneously relaxes three non-realistic assumptions of previous works: the link blocking independence, the Poisson traffic arrival and the homogeneity of the traffic load offered to the network links. Both methods were applied to different network topologies, and their results were compared to those of simulation. Results show that the match between simulation and the proposed methods is excellent, and better than assuming link blocking independence, in all the topologies studied.     

A two-level stochastic approximation for admission control andbandwidth allocation

In an access node to a multiservice network [e.g., a base station in an integrated services cellular wireless network or the optical line terminal (OLT) in a broad-band passive optical network (PON)], the output link bandwidth is adaptively assigned to different users and dynamically shared between isochronous (guaranteed bandwidth) and asynchronous traffic types. The bandwidth allocation is effected by an admission controller, whose goal is to minimize the refusal rate of connection requests as well as the loss probability of cells queued in a finite buffer. Optimal admission control strategies are approximated by means of backpropagation feedforward neural networks, acting on the embedded Markov chain of the connection dynamics; the neural networks operate in conjunction with a higher level bandwidth allocation controller which performs a stochastic optimization algorithm. The case of unknown, slowly varying input rates is explicitly considered. Numerical results are presented that evaluate the approximation and the ability to adapt to parameter variations     

An inversion algorithm to compute blocking probabilities in lossnetworks with state-dependent rates

The algorithm developed in Choudhury et al. (1994) for computing (exact) steady-state blocking probabilities for each class in product-form loss networks is extended to cover general state-dependent arrival and service rates. This generalization allows to consider, for the first time, a wide variety of buffered and unbuffered resource-sharing models with non-Poisson traffic, as may arise with overflows in the context of alternative routing. As before, the authors consider noncomplete-sharing policies involving upper-limit and guaranteed-minimum bounds for the different classes, but in the present paper both bounds are discussed simultaneously. These bounds are important for providing different grades of service with protection against overloads by other classes. The algorithm is based on numerically inverting the generating function of the normalization constant, which is derived in the present paper. Major features of the algorithm are: dimension reduction by elimination of nonbinding resources and by conditional decomposition based on special structure, an effective scaling algorithm to control errors in the inversion, efficient treatment of multiple classes with identical parameters and truncation of large sums. The authors show that the computational complexity of the inversion approach is usually significantly lower than the alternative recursive approach     

基于标值更新通信量模型的ATM缓冲区信元丢失率分析方法

提出了一种不同于传统分析方法（如ＭＭＰＰ／Ｄ／１）的直接基于输入通信量带宽分布和自相关特性的信元丢失率分析方法,应用标值更新模型近似实际输入通信量的低阶统计特性,给出了一个基于马尔柯夫链极限概率的信元丢失率估计公式。该方法可以估计突发级的信元丢失率,而且具有算法简单,计算量小,数值稳定性好等特点。     

MMPP models for multimedia traffic

The paper presents a study on the use of Markov‐Modulated Poisson Processes (MMPP's) for characterizing multimedia traffic with short‐term and long‐term correlation. The applicability of the 2‐state MMPP and a refined moment‐based parameter‐matching technique to model an arbitrary ATM traffic stream in evaluating its queueing performance are examined by simulation. Following a discussion on the limitation of the 2‐state MMPP model, a model using a superposition of N homogeneous 2‐state MMPP to characterize bursty multimedia traffic is presented. The proposed model requires only five parameters which can be estimated from the samples of the traffic counting process by using a pdf‐based matching technique. The introduced pdf‐based parameter‐matching procedure uses the probability density function of the arrival rate and the IDC curve of the traffic samples. An approximation for the probability of loss in MMPP/D/1 queues is also obtained. The versatility and accuracy of the proposed model to characterize bursty multimedia traffic are shown by several case studies and test results. This revised version was published online in June 2006 with corrections to the Cover Date.     

Polynomial cost approximations in Markov decision theory based calladmission control

The problem of call admission control and routing in a multiservice circuit-switched loss network can be solved optimally under certain assumptions by the tools of Markov decision theory. However, in networks of practical size a number of simplifying approximations are needed to make the solution feasible. Assuming link independence, we propose a new method for approximating the state-dependent link costs accurately and relatively efficiently, even on links with extremely large state spaces. The proposed polynomial approximations are optimal in the sense of minimizing the residual in the continuous-time Howard equations of the Markov decision processes associated with the links. Numerical results are presented, and the proposed approximations are found superior to some earlier link-cost approximation methods     

An efficient method for computing cell loss probability for heterogeneous bursty traffic in ATM networks

In this paper, we present an approximation for the probability of cell loss of heterogeneous bursty traffic in broadband integrated packet networks based on the asynchronous transfer mode. The sources considered here alternate between active and silent periods and are characterized by their peak and average transmission rates. The cell loss probability is obtained by considering only the number of active sources at a given time and computing the amount of traffic that exceeds the link capacity. Since the amount of buffered excess traffic is not considered in this computation, this approximation is actually an upper bound of the cell loss probability. The numerical efficiency of this bound enables it to be used as a measure based on which robust and simple resource allocation strategies can be developed for bursty sources. Comparison of this bound with the simulation results has shown that the bound is close to the actual loss probabilities especially for large burst lengths and high utilizations.     

Markovian Arrival Process Parameter Estimation With Group Data

This paper addresses a parameter estimation problem of Markovian arrival process (MAP). In network traffic measurement experiments, one often encounters the group data where arrival times for a group are collected as one bin. Although the group data are observed in many situations, nearly all existing estimation methods for MAP are based on nongroup data. This paper proposes a numerical procedure for fitting a MAP and a Markov-modulated Poisson process (MMPP) to group data. The proposed algorithm is based on the expectation-maximization (EM) approach and is a natural but significant extension of the existing EM algorithms to estimate parameters of the MAP and MMPP. Specifically for the MMPP estimation, we provide an efficient approximation based on the proposed EM algorithm. We examine the performance of proposed algorithms via numerical experiments and present an example of traffic analysis with real traffic data.      

Bandwidth allocation for multiservice access on EPONs

Ethernet passive optical networks are a low-cost high-speed solution to the bottleneck problem of the broadband access network. A major characteristic of EPONs is the shared upstream channel among end users, mandating efficient medium access control to facilitate statistical multiplexing and provision multiple services for different types of traffic. This article addresses and provides an overview of the upstream bandwidth allocation issue for multiservice access provisioning over EPONs, and proposes an algorithm for dynamic bandwidth allocation with service differentiation. Based on the multipoint control protocol (MPCP) and bursty traffic prediction, our algorithm enhances QoS metrics such as average frame delay, average queue length, and frame loss probability over other existing protocols     

On the Calculation of Overflow Systems with a Finite Number of Sources and Full Availiable Groups

This paper deals with the calculation of loss probabilities in overflow systems with a finite number of sources and full available groups. An exact, explicit solution is derived for overflow systems with only one primary group. Furthermore, an exact method is applied in case of overflow systems with two primary groups. For overflow systems with an arbitrary number of primary groups an approximate method is developed which takes into account the variance of offered overflow traffic. This approximate method yields results which are in good agreement with exact calculations and simulation results.     

Dimensioning optical networks under traffic growth models

In this paper, we consider the problem of dimensioning a large optical wavelength-division multiplexing (WDM) network assuming the traffic is growing over time. Traffic between pairs of nodes is carried through lightpaths which are high-bandwidth end-to-end circuits, occupying a wavelength on each link of the path between two nodes. We are interested in dimensioning the WDM links so that the first lightpath request rejection will occur, with high probability, after a specified period of time T. Here we introduce the concept of capacity exhaustion probability - the probability that at least one lightpath request will be rejected in the time period (0,T) due to lack of bandwidth/capacity on some link. We propose a network dimensioning method based on a traffic growth model which eventually results in a nonlinear optimization problem with cost minimization as the objective and route capacity exhaustion probabilities as the constraints. Computation of exact capacity exhaustion probabilities requires large computing resources and is thus feasible only for small networks. We consider a reduced load approximation for estimating capacity exhaustion probabilities of a wavelength routed network with arbitrary topology and traffic patterns. We show that the estimates are quite accurate and converge to the correct values under a limiting regime in the desired range of low-capacity exhaustion probabilities.     

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.     

An efficient modeling and dimensioning approach for integrated streaming and elastic traffic

Recent studies show that both data traffic and real-time traffic grow very fast in wired and wireless networks. To provide better performance guarantee, these applications need efficient network modeling and planning. In this paper, the problem where the total bandwidth of a link is shared by streaming traffic (real time traffic such as voice or video etc.) and elastic traffic (such as data) is studied. Integrating streaming traffic and elastic traffic presents a unique dimensioning problem. This paper considers dimensioning a link to satisfy both quality of service (QoS) requirements for streaming traffic, such as loss probability, and elastic traffic, such as mean waiting (delay) time. The Erlang loss model is applied to streaming traffic and a bursty traffic model is applied to the elastic traffic. Efficient dimensioning algorithms based on classical Markovian models and time-scale decomposition are then proposed. Numerical results show that the proposed methods have good accuracy.     

An empirical real-time approximation of waiting time distributionin MMPP(2)/D/1

We propose a simple, empirical real-time approximation method for calculating the waiting time distribution for the MMPP(2)/D/1 system. Our approach is based on approximation using a two-term exponential function. We match the poles, the residue for the asymptotic constant, and the mean waiting time between the Laplace transforms of the exact distribution and the approximate distribution. Numerical examples show that our method yields quite accurate results over a wide range. The result can be adopted in evaluating asynchronous transfer mode (ATM) multiplexers for real-time ATM traffic control