Estimation of Cell Loss Ratio and Cell Delay for ATM Networks using Novel Genetic Algorithm Approach

Estimating cell loss probability (CLP) in real time for achieving satisfactory call admission control (CAC) remains an important research problem. In estimating CLP which is often specified to be less than 10/sup -9/, fuzzy based techniques have been found to be more promising than crisp statistical techniques. In this paper, we propose a novel fuzzy logic algorithm based on the /spl alpha/-cuts of equivalence relations to estimate CLP in real time for self-similar ATM networks. The /spl alpha/-cuts of fuzzy sets are used to construct the membership functions of the input and output variables and to induce necessary fuzzy rules. The proposed fuzzy approach is validated by comparing the estimated values of CLP with the theoretical values. The new approach not only estimates accurate real time CLP, but also achieves it by using fewer theoretical data.

The statistics of cell loss at both burst and cell levels are studied by simulation based on the configuration of the Singapore One ATM network. A virtual connection through the Singapore One network is modelled as a tandem queueing network to which mixtures of homogeneous discrete-time burst–silence traffic with different burst lengths are offered. Attention is focused on a designated traffic stream as it goes through the tandem queueing network. In the simulation, the authors have not introduced the ‘independence assumption’ between the adjacent queues, i.e. the actual tandem queueing network is used to obtain the performance measures for the designated traffic stream. Cell loss probability and high-order cell loss distributions such as cell loss-free run distribution and cell loss pattern distribution are obtained. These results provide valuable information for the estimation of end-to-end overall quality of service (QoS), design of the cell policing mechanism and flow control schemes in the ATM networks.

Traditional approaches to guaranteeing quality-of-service (QoS) in ATM networks have focused on performance metrics such as cell loss probability, end-to-end cell delay and delay jitter. However, the block loss rate is a more meaningful metric for applications such as medical imaging and real-time video, and for high-level protocols such as IP which will use ATM as the transport mechanism. A block is defined as a group of consecutive ATM cells. A block loss occurs when a single cell from a block is lost. We propose and evaluate, via extensive simulation, a technique for reducing block loss in ATM networks. Our method combines two well-studied approaches for minimizing the impact of information loss during transport over ATM networks which have been considered independently of each other in the past: priority-based cell discarding and forward error correction (FEC). We also study an enhanced buffer management algorithm which we call adaptive pushout (ADP) that accounts for correlations between cell losses. The ADP algorithm reduces block loss rates to near-optimal levels. We consider further performance enhancements to the ADP policy that deliver excellent performance even under very heavy load.

Studies the traffic shaping issues for VBR video services in ATM networks with stress put on the source clock frequency recovery aspect. The authors propose a "three-level traffic shaper" (TLTS) which is able to limit the minimum as well as the maximum cell rate of input VBR traffic. For a VBR video source modeled after a two-state Markov modulated Poisson process, they determine, as performance measures, the cell loss probability, the underflow probability, and the maximum delay that a cell can experience in the proposed TLTS. Then they apply the TLTS for source clock frequency recovery in VBR video services. In extending the existing CBR-based synchronous residual time stamp (SRTS) method for VBR video services, it is necessary to restrict the minimum, as well as the maximum, number of cells generated in a fixed period of time to ensure the transmission of timing information, and the proposed TLTS is tailored to meet this necessity by adopting an optimal dimensioning procedure based on the genetic algorithm (GA). Finally the authors provide some numerical examples to demonstrate the optimal dimensioning procedure of TLTS and the related performances of statistical multiplexing and source clock frequency recovery.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Constant increase in urban road traffic is forcing traffic authorities to confront unavoidable congestion problems these days. This creates new challenges for city planners to generate traffic routes with better designs and improve the existing roads. In order to analyze and improve traffic routes, there is a need to understand movement patterns of major vehicular traffic inside the city. Origin Destination(OD) estimation is one such method for understanding the movement patterns. The objective is to find an optimal OD matrix for city traffic, which is a subtle process for classic algorithms. The solution to this problem is Genetic Algorithm (GA) approach which is a search heuristics to find optimal solution from a set of random solutions. A Genetic Algorithm approach has been developed to find an optimal OD matrix, showing the actual travel patterns of significant number of vehicles inside the city. Once the best OD matrix is obtained, it yields a big opportunity for traffic planners to analyze and improve traffic scenario. Genetic Algorithm can play a major role in solving complex problems. In this paper, one such problem of estimating OD matrix of a city is discussed and implemented. In conjunction to genetic algorithm, Mean Absolute Percentage Error(MAPE) has been used as a fitness criteria for finding the optimal OD matrix.

This study deals with estimation of the total and industrial sector electricity consumption based on genetic algorithm (GA) approach, and then proposes two scenarios to project future consumptions. Total electricity consumption is estimated based on gross national product (GNP), population, import and export figures of Turkey. Industrial sector electricity is calculated based on the GNP, import and export figures. Three forms of the genetic algorithm electricity demand (GAED) models for the total and two forms for the industrial electricity consumption are developed. The best-fit GAED model in terms of total minimum relative average errors between observed and estimated values is selected for future demand estimation. ‘High- and low-growth scenarios’ are proposed for predicting the future electricity consumption. Results showed that the GAED estimates the electricity demand in comparison with the other electricity demand projections. The GAED model plans electricity demand of Turkey until 2020. Copyright © 2005 John Wiley & Sons, Ltd.

Design and analysis of ATM networks in which sources are represented as fluid on/off is addressed. It is critical that cell loss rate as an important QOS measure be related to the call blocking, an important network design parameter, and this relation be used in link capacity sizing, call admission, and routing design. Recently, some research on the relation of cell loss and call blocking have appeared. However, they ignore buffering in the multiplexer. In this paper, it is shown that call blocking in a buffered ATM multiplexer behaves as an Erlang-B loss system. For analytic purposes system buffer is assumed infinite and transmission rate of the link (C) is assumed to be finite. Using past results on probability of cell loss and properties of Nearly Completely Decomposable Markov Chains, the aggregate cell loss when system is in different states is determined. It is shown that call blocking performance for a given link capacity is independent of the individual source parameters. An extended set of application of the results and an inverse problem is stated.

The application of genetic algorithms in behavioural ecology, illustrated with a model of anti-predator vigilance

This paper deals with a robust track-following system design problem with multiple constraints using genetic algorithm and LMI approach. A robust H ∞ constraint is introduced to attenuate vibration disturbance within error limits and a robust loop gain constraint is considered to minimize the variations of the tracking loop characteristics against actuator uncertainties. The robust H ∞ constraint can be expressed by a matrix inequality and the robust loop gain constraint can be treated by an objective function of a genetic algorithm. Accordingly, a robust tracking controller can be obtained by integrating a genetic algorithm and LMI approach. The proposed track-following system design method is applied to the track-following system of a DVD recording drive and is evaluated through experimental results.

Investment is one of the economic growth factors of countries, especially in Indonesia. Stocks is a form of investment, which is liquid. In determining the stock investment decisions which need to be considered by investors is to choose stocks that can generate maximum returns with a minimum risk level. Therefore, we need to know how to allocate the capital which may give the optimal benefit. This study discusses the issue of stock investment based on CAPM which is estimated using covariance and Genetic Algorithm approach. It is assumed that the stocks analyzed follow the CAPM model. To do the estimation of beta parameter on CAPM equation is done by two approach, first is to be represented by covariance approach, and second with genetic algorithm optimization. As a numerical illustration, in this paper analyzed ten stocks traded on the capital market in Indonesia. The results of the analysis show that estimation of beta parameters using covariance and genetic algorithm approach, give the same decision, that is, six underpriced stocks with buying decision, and four overpriced stocks with a sales decision. Based on the analysis, it can be concluded that the results can be used as a consideration for investors buying six under-priced stocks, and selling four overpriced stocks.

The use of active vibration control may induce a delay leading to detrimental degradation of the performance of active vibration control. This is particularly true in the case of mechanical systems subjected to friction-induced vibration and noise for which such time-delays can lead to the appearance of undesirable instability. Furthermore, conducting a stability analysis of time-delay systems and estimation of the critical time delay are challenging, due to the infinite nature of the characteristic (quasi) polynomial of the associated closed-loop system, having an infinite number of roots.The objective of this paper is to discuss a strategy for the estimation of the critical time delay for the problem of Friction-Induced Vibration and noisE (FIVE). To achieve such an objective, the prediction of the stability analysis of time delay systems and the estimation of the associated critical time delay are first performed by applying the frequency sweep test and the eigenvalue problem approximation using the Taylor series expansion of the delayed term. In a second time, a mixed approach is proposed to predict effectively the real critical time delay of autonomous controlled systems subjected to friction-induced vibration. The efficiency of the proposed approach is illustrated by numerical examples for the prediction of self-sustaining vibrations of a phenomenological model with two degrees of freedom for which it is possible to provide a clear understanding and illustration of the phenomena involved and observed.

Estimating the cell loss probability in an ATM multiplexer is a key issue in network management and traffic control such as call admission control and bandwidth allocation. In this paper, we derive a new approximation to estimate the total and individual cell loss probabilities in an ATM multiplexer fed by a superposition of heterogeneous on-off sources with exponentially distributed on and off periods. Based on this approximation, a simple and accurate method is proposed to estimate the aggregate required bandwidth by a given mix of traffic to guarantee a given cell loss probability.

Estimating the cell loss probability in an ATM multiplexer is a key issue in network management and traffic control tasks such as call admission control and bandwidth allocation. In this paper, we derive a new approximation to estimate the total and individual cell loss probabilities in an ATM multiplexer fed by a superposition of heterogeneous on‐off sources. Based on this approximation, a simple algorithm is proposed to estimate accurately the aggregate required bandwidth to guarantee a given cell loss probability. Numerical results and comparisons to alternative approaches are also shown.

Design of two-dimensional FIR digital filters for sampling structure conversion by genetic algorithm approach

Clinching is a convenient and efficient cold forming process that can join two sheets without any additional part. This study establishes an intelligent system for optimizing the clinched joint. Firstly, a mathematical model which introduces the ductile damage constraint to prevent cracking during clinching process is proposed. Meanwhile, an optimization methodology and its corresponding computer program are developed by integrated finite element model (FEM) and genetic algorithm (GA) approach. Secondly, Al6061-T4 alloy sheets with a thickness of 1.4mm are used to verify this optimization system. The optimization program automatically acquires the largest axial strength which is approximately equal to 872N. Finally, sensitivity analysis is implemented, in which the influence of geometrical parameters of clinching tools on final joint strength is analyzed. The sensitivity analysis indicates the main parameters to influence joint strength, which is essential from an industrial point of view.