COMPARATIVE ANALYSIS OF NEURO- FUZZY AND SIMPLEX OPTIMIZATION MODEL FOR CONGESTION CONTROL IN ATM NETWORK.

Congestion always occurred when the transmission rate increased the data handling capacity of the network. Congestion normally arises when the network resources are not managed efficiently. Therefore if the source delivers at a speed higher then service rate queue, the queue size will be higher. Also if the queue size is finite, then the packet will observed delay. MATLAB Software was used to carry out simulations to develop Congestion control optimization Scheme for ATM Network with the aims to reducing the congestion of Enugu ATM Network. The results of the research reveal the minimization of congestion application model for Enugu ATM using optimization and Neuro-fuzzy. The result shows that congestion control model with Optimization and Neuro-fuzzy were 0.00003153 and 0.00002098 respectively. The ATM Congestion was reduced by 0.0000105, which is 18.2% decrease after Neuro-fuzzy controller was used. The results show the application of Neuro-fuzzy model which can use to control and minimized the ATM Congestion of Enugu ATM Network. The result shows that when Neuro-fuzzy is applied the congestion and the packet queue length in the buffer will be minimized. Key words: Congestion, MATLAB, Optimization, Neuro-fuzzy, ATM DOI: 10.7176/CTI/10-05 Publication date:July 31st 2020

Some aspects of traffic control and performance evaluation of ATM networks

The emerging high-speed Asynchronous Transfer Mode (ATM) networks are expected to integrate through statistical multiplexing large numbers of traffic sources having a broad range of statistical characteristics and different Quality of Service (QOS) requirements. To achieve high utilisation of network resources while maintaining the QOS, efficient traffic management strategies have to be developed. This thesis considers the problem of traffic control for ATM networks. The thesis studies the application of neural networks to various ATM traffic control issues such as feedback congestion control, traffic characterization, bandwidth estimation, and Call Admission Control (CAC). A novel adaptive congestion control approach based on a neural network that uses reinforcement learning is developed. It is shown that the neural controller is very effective in providing general QOS control. A Finite Impulse Response (FIR) neural network is proposed to adaptively predict the traffic arrival process by learning the relationship between the past and future traffic variations. On the basis of this prediction, a feedback flow control scheme at input access nodes of the network is presented. Simulation results demonstrate significant performance improvement over conventional control mechanisms. In addition, an accurate yet computationally efficient approach to effective bandwidth estimation for multiplexed connections is investigated. In this method, a feed forward neural network is employed to model the nonlinear relationship between the effective bandwidth and the traffic situations and a QOS measure. Applications of this approach to admission control, bandwidth allocation and dynamic routing are also discussed. A detailed investigation has indicated that CAC schemes based on effective bandwidth approximation can be very conservative and prevent optimal use of network resources. A modified effective bandwidth CAC approach is therefore proposed to overcome the drawback of conventional methods. Considering statistical multiplexing between traffic sources, we directly calculate the effective bandwidth of the aggregate traffic which is modelled by a two-state Markov modulated Poisson process via matching four important statistics. We use the theory of large deviations to provide a unified description of effective bandwidths for various traffic sources and the associated ATM multiplexer queueing performance approximations, illustrating their strengths and limitations. In addition, a more accurate estimation method for ATM QOS parameters based on the Bahadur-Rao theorem is proposed, which is a refinement of the original effective bandwidth approximation and can lead to higher link utilisation

Dynamic bandwidth allocation in ATM networks

Includes bibliographical references.This thesis investigates bandwidth allocation methodologies to transport new emerging bursty traffic types in ATM networks. However, existing ATM traffic management solutions are not readily able to handle the inevitable problem of congestion as result of the bursty traffic from the new emerging services. This research basically addresses bandwidth allocation issues for bursty traffic by proposing and exploring the concept of dynamic bandwidth allocation and comparing it to the traditional static bandwidth allocation schemes

Application of learning algorithms to traffic management in integrated services networks.

SIGLEAvailable from British Library Document Supply Centre-DSC:DXN027131 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Traffic Management and Congestion Control in the ATM Network Model.

Asynchronous Transfer Mode (ATM) networking technology has been chosen by the International Telegraph and Telephony Consultative Committee (CCITT) for use on future local as well as wide area networks to handle traffic types of a wide range. It is a cell based network architecture that resembles circuit switched networks, providing Quality of Service (QoS) guarantees not normally found on data networks. Although the specifications for the architecture have been continuously evolving, traffic congestion management techniques for ATM networks have not been very well defined yet. This thesis studies the traffic management problem in detail, provides some theoretical understanding and presents a collection of techniques to handle the problem under various operating conditions. A detailed simulation of various ATM traffic types is carried out and the collected data is analyzed to gain an insight into congestion formation patterns. Problems that may arise during migration planning from legacy LANs to ATM technology are also considered. We present an algorithm to identify certain portions of the network that should be upgraded to ATM first. The concept of adaptive burn-in is introduced to help ease the computational costs involved in virtual circuit setup and tear down operations

Layer-based coding, smoothing, and scheduling of low-bit-rate video for teleconferencing over tactical ATM networks

This work investigates issues related to distribution of low bit rate video within the context of a teleconferencing application deployed over a tactical ATM network. The main objective is to develop mechanisms that support transmission of low bit rate video streams as a series of scalable layers that progressively improve quality. The hierarchical nature of the layered video stream is actively exploited along the transmission path from the sender to the recipients to facilitate transmission. A new layered coder design tailored to video teleconferencing in the tactical environment is proposed. Macroblocks selected due to scene motion are layered via subband decomposition using the fast Haar transform. A generalized layering scheme groups the subbands to form an arbitrary number of layers. As a layering scheme suitable for low motion video is unsuitable for static slides, the coder adapts the layering scheme to the video content. A suboptimal rate control mechanism that reduces the kappa dimensional rate distortion problem resulting from the use of multiple quantizers tailored to each layer to a 1 dimensional problem by creating a single rate distortion curve for the coder in terms of a suboptimal set of kappa dimensional quantizer vectors is investigated. Rate control is thus simplified into a table lookup of a codebook containing the suboptimal quantizer vectors. The rate controller is ideal for real time video and limits fluctuations in the bit stream with no corresponding visible fluctuations in perceptual quality. A traffic smoother prior to network entry is developed to increase queuing and scheduler efficiency. Three levels of smoothing are studied: frame, layer, and cell interarrival. Frame level smoothing occurs via rate control at the application. Interleaving and cell interarrival smoothing are accomplished using a leaky bucket mechanism inserted prior to the adaptation layer or within the adaptation layerhttp://www.archive.org/details/layerbasedcoding00parkLieutenant Commander, United States NavyApproved for public release; distribution is unlimited

IP and ATM integration: A New paradigm in multi-service internetworking

ATM is a widespread technology adopted by many to support advanced data communication, in particular efficient Internet services provision. The expected challenges of multimedia communication together with the increasing massive utilization of IP-based applications urgently require redesign of networking solutions in terms of both new functionalities and enhanced performance. However, the networking context is affected by so many changes, and to some extent chaotic growth, that any approach based on a structured and complex top-down architecture is unlikely to be applicable. Instead, an approach based on finding out the best match between realistic service requirements and the pragmatic, intelligent use of technical opportunities made available by the product market seems more appropriate. By following this approach, innovations and improvements can be introduced at different times, not necessarily complying with each other according to a coherent overall design. With the aim of pursuing feasible innovations in the different networking aspects, we look at both IP and ATM internetworking in order to investigating a few of the most crucial topics/ issues related to the IP and ATM integration perspective. This research would also address various means of internetworking the Internet Protocol (IP) and Asynchronous Transfer Mode (ATM) with an objective of identifying the best possible means of delivering Quality of Service (QoS) requirements for multi-service applications, exploiting the meritorious features that IP and ATM have to offer. Although IP and ATM often have been viewed as competitors, their complementary strengths and limitations from a natural alliance that combines the best aspects of both the technologies. For instance, one limitation of ATM networks has been the relatively large gap between the speed of the network paths and the control operations needed to configure those data paths to meet changing user needs. IP\u27s greatest strength, on the other hand, is the inherent flexibility and its capacity to adapt rapidly to changing conditions. These complementary strengths and limitations make it natural to combine IP with ATM to obtain the best that each has to offer. Over time many models and architectures have evolved for IP/ATM internetworking and they have impacted the fundamental thinking in internetworking IP and ATM. These technologies, architectures, models and implementations will be reviewed in greater detail in addressing possible issues in integrating these architectures s in a multi-service, enterprise network. The objective being to make recommendations as to the best means of interworking the two in exploiting the salient features of one another to provide a faster, reliable, scalable, robust, QoS aware network in the most economical manner. How IP will be carried over ATM when a commercial worldwide ATM network is deployed is not addressed and the details of such a network still remain in a state of flux to specify anything concrete. Our research findings culminated with a strong recommendation that the best model to adopt, in light of the impending integrated service requirements of future multi-service environments, is an ATM core with IP at the edges to realize the best of both technologies in delivering QoS guarantees in a seamless manner to any node in the enterprise

A study of self-similar traffic generation for ATM networks

This thesis discusses the efficient and accurate generation of self-similar traffic for ATM networks. ATM networks have been developed to carry multiple service categories. Since the traffic on a number of existing networks is bursty, much research focuses on how to capture the characteristics of traffic to reduce the impact of burstiness. Conventional traffic models do not represent the characteristics of burstiness well, but self-similar traffic models provide a closer approximation. Self-similar traffic models have two fundamental properties, long-range dependence and infinite variance, which have been found in a large number of measurements of real traffic. Therefore, generation of self-similar traffic is vital for the accurate simulation of ATM networks. The main starting point for self-similar traffic generation is the production of fractional Brownian motion (FBM) or fractional Gaussian noise (FGN). In this thesis six algorithms are brought together so that their efficiency and accuracy can be assessed. It is shown that the discrete FGN (dPGN) algorithm and the Weierstrass-Mandelbrot (WM) function are the best in terms of accuracy while the random midpoint displacement (RMD) algorithm, successive random addition (SRA) algorithm, and the WM function are superior in terms of efficiency. Three hybrid approaches are suggested to overcome the inefficiency or inaccuracy of the six algorithms. The combination of the dFGN and RMD algorithm was found to be the best in that it can generate accurate samples efficiently and on-the-fly. After generating FBM sample traces, a further transformation needs to be conducted with either the marginal distribution model or the storage model to produce self-similar traffic. The storage model is a better transformation because it provides a more rigorous mathematical derivation and interpretation of physical meaning. The suitability of using selected Hurst estimators, the rescaled adjusted range (R/S) statistic, the variance-time (VT) plot, and Whittle's approximate maximum likelihood estimator (MLE), is also covered. Whittle's MLE is the better estimator, the R/S statistic can only be used as a reference, and the VT plot might misrepresent the actual Hurst value. An improved method for the generation of self-similar traces and their conversion to traffic has been proposed. This, combined with the identification of reliable methods for the estimators of the Hurst parameter, significantly advances the use of self-similar traffic models in ATM network simulation

The design of a synchronous virtual writing clinic

[[abstract]]The design of an online synchronous writing clinic is described. Two novel mechanisms have been designed to provide the two fundamental capabilities for the clinic: (1) synchronous text co-editing, and (2) Internet voice delivery. Therefore, the participants are able to synchronously edit a common text file on-line with voice communication support by using the synchronous text co-editing tool. Furthermore, the designed policy-based forward error correction voice transmission mechanism delivers good voice conversation quality when handling delay, jitter, and packet loss on the Internet. The developed system not only has great value in supporting applications such as CSCW, Internet Telephony, or Multimedia Instruction on Demand (MID), but also has been applied in the area of Distance Language Learning by exploiting the integration of computer and networking capabilities with linguistic and pedagogical principles.＿[[notice]]補正完畢[[journaltype]]國內[[incitationindex]]EI[[booktype]]紙本[[countrycodes]]TW