Connection Acceptance Control Research Articles

Economics and scalability of QoS solutions

The paper presents an analysis of the factors which affect the scaling of quality of service (QoS) solutions. This includes analysis of the sources of variance in traffic forecasts and how these contribute to a probability that a network resource will be unable to meet the capacity load placed upon it. While the analysis is general and could be applied to a wide variety of QoS mechanisms, this paper is focused on the scalability of ‘edge connection acceptance control with DiffServ core’ networks for real-time services and concludes that this scaling of such networks is remarkably poor. One way of addressing this poor scalability is for operators to lease from other operators what is for them ‘virtual infrastructure’ in order to construct a network with short topology.

Effective bandwidth estimation and testing for Markov sources

This work addresses the resource sharing problem in broadband communication networks that can guarantee some quality of service (QoS), and develops some results about data source and traffic modelling, especially in aspects of model testing and parameter estimation. The multiplexing of variable bit rate (VBR) sources poses a mathematical and statistical problem: the estimation of the resource requirements of a source or set of sources. The estimation method shall be simple enough to be practically implemented in the connection acceptance control (CAC) function. In this paper, the VBR video sources are taken as a typical case of variable rate, with real-time constraints. This association of requirements makes the case especially interesting. A Markov model is assumed for the VBR sources. The validity of such models is under research; they seem to be appropriate at least in certain time scales. The model is tested against real video traces. In order to estimate the resource allocation or “channel occupation” of each source, the concept of equivalent bandwidth proposed by Kelly [Notes on effective bandwidth, in: F.P. Kelly, S. Zachary, I.B. Ziedins (Eds.), Stochastic Networks: Theory and Applications, Oxford University Press, Oxford, 1996, pp. 141] is used; it is based on a consistent mathematical theory, and has proven to be robust and useful for technical applications. A calculation of the equivalent bandwidth of a Markov source, given its parameters, can be found in the literature [IEEE ACM Trans. Networking 1 (4) (1993) 424]. But in fact, one can only estimate model and parameters. In this work, an estimation of the equivalent bandwidth is given, which can be obtained from real data. The convergence and the consistency of the estimation are studied, and practical bounds are found. Illustrative calculations are performed from real video traces that were obtained using a software MPEG coder, developed by the authors. The mathematical and statistical results are valid for whatever phenomenon that can be modelled as a Markov process.

An ECN probe-based connection acceptance control

Connection acceptance control is a mechanism which can be used to moderate the load placed on a network by turning away connection requests during times of overload. Traditionally these mechanisms have been implemented by setting up state within a network using signalling protocols, such as the IETF's Resource Reservation Protocol. There have been recent proposals for admission control based on end-systems probing the network to infer network load. These distributed algorithms often have less router state and hence scale more easily. This paper discusses an ECN (Explicit Congestion Notification) probe-based admission control protocol that is fast, scalable and robust. The protocol's performance is then studied through simulation. It is concluded that probe-based admission control is viable in both partitioned and integrated networks, but more research is needed to understand the implications for network policy control.

A survey of straightforward statistical multiplexing models for ATM networks

Connection Acceptance Control (CAC) is probably the most important function in the preventive congestion control strategy to be implemented in ATM networks. The CAC function must decide, on the basis of the traffic descriptors provided by an incoming connection, whether the new call can be accepted or not. A key factor in the access decision is the behaviour of the superposition of ATM VCs in a switch output buffer, and in particular the cell loss probability resulting from accepting the connection. Many models have been proposed in the literature in order to investigate this issue. In this paper, we present a survey of the queuing models used to estimate the cell loss probability in ATM networks with straightforward statistical multiplexing. The CAC policy under consideration is based on the so-called Worst Case Traffic allocation corresponding to the traffic descriptor parameters submitted by a VC: itspeak cell rate, cell delay variation tolerance, sustainable cell rate, andintrinsic burst tolerance parameters, when applicable. We plan to investigate the practical application of these models to the problem of CAC; in particular, the important issues of accuracy of the available models, their range of validity and their complexity deserve more attention than they have received up to now. The present survey stands as a first step in that direction.

Deterministic rule based traffic descriptors for broadband ISDN: Worst case behaviour and its impact on connection acceptance controls

AbstractDeterministic rule based traffic descriptors in general, and leaky bucket based (LBB) traffic descriptors in particular, offer many advantages over statistical descriptors for specifying and monitoring traffic in the ATM based broadband ISDN (BISDN). However, these traffic descriptors do not specify the traffic pattern uniquely. Thus, acceptance of a connection request with specific traffic descriptor parameter values implies that the network has agreed to guaranteeing the quality of service (QOS) for the worst case traffic compliant with the traffic descriptor (and hence allowed by the monitor). This poses challenges which have not been addressed adequately. Two of the important ones are: (i) definition of the worst case behaviour and characterization of the worst case traffic compliant with the traffic descriptor; (ii) connection acceptance controls (CAC) for the worst case traffic sources compliant with the traffic descriptors. In this paper we address these questions for leaky bucket based (LBB) traffic descriptors. The focus is on the first problem. The implications on the second problem are discussed briefly. The performance measure and QOS requirements are in terms of the cell loss ratios.We first define the worst case behaviour for homogeneous and heterogeneous environments in terms of collective cell loss ratio (CLR)) from the multiplexer. We consider both the unbuffered and buffered cases. However, most of the results here are for the unbuffered case. FOTthe case of an unbuffered multiplexer and homogeneous source environment, we show that a simple on‐off source represents the worst case behaviour of an LBB source. In a heterogeneous source traffic environment, the on‐off behaviour is the worst only in a limited sense and the use of a collective measure results in anomalous relationships between the source behaviour and the CLR. A more appropriate measure should be based on individual cell loss ratios or on the maximum of the individual CLRs. We analyse LBB sources with respect to these measures and unbuffered resources, and obtain further characterization of the worst case behaviour. However, we also uncover some counter‐intuitive relationships. In particular, a seemingly ‘smooth’ source may be worse for the other sources than a seemingly ‘bursty’ source.For a buffered multiplexer, we show, via an example, that a three‐state source may be worse than an on‐off source even in a homogeneous source traffic environment. A complete characterization of the worst case behaviour for a buffered multiplexer remains an open challenge. Moreover, the LBB sources exhibit deterministic behaviour and their equivalent bandwidth need not be sub‐additive in sources. That is, adding the equivalent bandwidths of individual sources to obtain an ‘estimate’ of the equivalent bandwidth for a collection of such sources could be too optimistic in some situations. A fresh look at the connection acceptance control for such sources is therefore warranted.

Robust connection acceptance control for ATM networks with incomplete source information

Consider an ATM resource where the statistics of each bursty traffic source are not precisely known. How should the resource decide when to accept fresh connections? We address this problem for the case where each source behaves as a simple “On-Off” model and only the peak bandwidth is known. A connection acceptance control algorithm is proposed that relies on the choice of a boundary. The performance of this algorithm is analysed using an approximation based on separation of timescales. The slowly changing call process behaves like the queue process at an infinite server queue, where the arrival process to the queue is dictated by the fast moving burst process. A technique for finding a suitable boundary is also given, based on the Bayesian principle. The algorithm, together with the proposed boundary, could be used in a network to control connection acceptance at each resource along a virtual path.

A novel neural network traffic enforcement mechanism for ATM networks

ATM has been recommended by the CCITT as the transport vehicle for the future B-ISDN networks. In ATM-based networks, a set of user declared parameters that describes the traffic characteristics, is required for the connection acceptance control (CAC) and traffic enforcement (policing) mechanisms. At the call set-up phase, the CAC algorithm uses those parameters to make a call acceptance decision. During the call progress, the policing mechanism uses the same parameters to control the user's traffic within its declared values in order to protect the network's resources and avoid possible congestion problems. A novel policing mechanism using neural networks (NNs) is presented. This is based upon an accurate estimation of the probability density function (pdf) of the traffic via its count process and implemented using NNs. The pdf-based policing is made possible only by NNs because pdf policing requires complex calculations, in real-time, at very high speeds. The architecture of the policing mechanism is composed of two interconnected NNs. The first one is trained to learn the pdf of nonviolating traffic, whereas the second is trained to capture the actual characteristics of the actual offered traffic during the progress of the call. The output of both NNs is compared. Consequently, an error signal is generated whenever the pdf of the offered traffic violates its ideal one. The error signal is then used to shape the traffic back to its original values. >

ATD-specific network management functions and TMN architecture

The paper deals with the ATM (asynchronous transfer mode) - specific functions of source policing and connection acceptance control and their relationship to network management. The aspects of ATM-specific network management are based on the results achieved by the RACE project R1022, ‘Technology for ATD’. It is shown how these functions can be implemented according to the TMN (telecommunications management network) architecture suggested by the RACE project GUIDELINE (R1003). The interaction between these functions and other network management functions is discussed and the interaction of these functions with the management layers is presented in a way which is not dependent on the specific algorithms used for source policing and connection acceptance control.