Abdulmohsen A. Alheraish

A GACS modeling approach for MPEG broadcast video

Accurate MPEG source models are needed to support high speed networks such as ATM and Internet. In this paper, we propose a video model called Gaussian auto-regressive and chi-square processes (GACS) for MPEG coded video traffic. The GACS models the sizes of MPEG I, P, and B frames according to the MPEG syntax I-frame>P-frame>B-frame. This is done by decomposing the process of each frame size into a weighted sum of a number of chi-square sequences. Each chi-square sequence is then obtained by squaring a Gaussian process, which is efficiently generated by using an auto-regressive (AR) model whose parameters are determined from an estimated covariance matrix. We evaluate the effectiveness of our model by conducting a series of experiments using a wide variety of long empirical video sequences. The results show that the proposed model leads to excellent data fit and accurate prediction of queuing performance.

A tutorial on using genetic algorithms for the design of network topology

The design of network topology is an important part of network design, since network topology is directly associated with network operational behavior, capacity, reliability, and cost. This paper is a tutorial paper concerned with illustrating how the optimization capabilities of genetic algorithms can be used to design suitable network topologies considering basic topology problems. Simple genetic algorithms have been developed for the topology problem of mesh networks, considering single node and single link failure tolerance. The algorithms are based on criteria of two important measures: minimizing the length of communication links; and minimizing traffic flow through these links for given traffic loads. The first measure contributes to minimizing the cost of cabling, while the second measure contributes to minimizing the cost of link capacity. The work provides a useful approach and tools to network students and professionals concerned with the topology design of backbone networks. The developed software is made available on the Internet.

STOPE-based approach for e-readiness assessment case studies

The STOPE-based approach is used here for practical e-readiness assessment case studies. The approach integrates and evaluates the various e-readiness assessment issues, over its well-structured domains: strategy, technology, organization, people, and environment. The case studies considered concern three Saudi organizations: a government organization, a bank, and a private sector company. The results obtained provide e-readiness indicators that illustrate the strengths and weaknesses of each organization with regard to e-readiness strategic development issues, information and communication technology (ICT)issues, management and organization issues, people issues, and environment issues within which the organization operates. The work shows how the approach can be practically used, and it also provides practical results that direct the organizations concerned toward enhancing their e-readiness in response to the current trend of globalizing e-business.

AR-based quadratic modeling for GOP MPEG-encoded video traffic in ATM networks

Statistical analysis and performance modeling of compressed video traffic streams are efficient tools to estimate network resources and to predict network behavior under various conditions. Among current video traffic models, Autoregressive (AR) processes have been extensively used as good representation of variable bit rate video services, due basically to their simplicity and ease of computation. Recently, an elegant approach to the modeling of teleconferencing video has been proposed by Zhang in IEEE Trans. Circuits Syst. Video Technol. 9 (1999) p. 1130. This approach decomposes the traffic data into a linear combination of a number of chi-square sequences, each of which is obtained by passing a Gaussian AR process through a simple non-linearity. In this article, we first show that the model presented by Zhang is a special case of the general form of models represented by quadratic filters that are widely used in modern digital signal processing. Second, we extend Zhangs approach to model MPEG video traffic; an important full motion video source that exhibits dynamic and complex pattern. Specifically, we propose modeling MPEG video at GOP layer in ATM packet switching networks. This layer has an important feature in that it reflects the behavior of video scene activities. Finally, by using a wide variety of real MPEG video sequences, we experimentally demonstrate that the proposed GOP-based model approximates the real video traffic extremely well in terms of first and second order statistics as well as queuing performance.

A gamma source model for full motion video using non-linear systems

Among current video traffic models, Autoregressive (AR) processes have been extensively used as good representation of variable bit rate (VBR) video services, due basically to their simplicity and case of computation. Recently, an elegant approach to the modeling of teleconferencing video has been proposed by Zhang [1999]. This approach decomposes the traffic data into a linear combination of a number of chi-square sequences, each of which is obtained by passing a Gaussian AR process through a simple nonlinearity. In this paper, we first show that the model presented by Zhang is a special case of the general form of models represented by quadratic filters that are widely used in modern digital signal processing. Second, we extend Zhangs approach to model MPEG video traffic; an important full motion video source that exhibits dynamic and complex pattern. Specifically, we propose modeling MPEG video at GOP layer in ATM packet switching networks.

A comparison of AR full motion video traffic models in B-ISDN

Full motion video traffic is envisaged to be a major source for Internet and broadband integrated services digital networks (B-ISDN). Accurate traffic models of full motion video are needed to design networks and improve video services. Auto-regressive process (AR) proves to be a viable modeling approach of full motion video. A considerable amount of effort on AR video modeling has been reported in the recent studies which need to be thoroughly investigated. The aim of this paper is: (1) to survey a number of AR models for full motion video; (2) to classify the models according to their properties and framework; (3) to compare and contrast the models based on their attributes: residual, coding scheme, capturing scene changes, number of parameters, level of modeling, and complexity; (4) to show the ability of these models to predict accurately different aspects of network performance; (5) to give recommendations that might be helpful in determining the appropriate model for full motion video based on the target application; (6) to give direction for future work on this important modeling scheme.

A novel methodology for robust VBR video transmission in an ATM system

A dynamic FEC (DFEC) scheme for VBR video in ATM networks is proposed. The scheme combines the design of source encoder, error control, and the network. In the design, we will develop a methodology to vary FEC redundancy dynamically. The methodology considers the fluctuations in video source and network utilisation to adjust the FEC redundancy levels. We demonstrate the effectiveness of the proposed scheme by examining its performance with three existing schemes in terms of loss rates, throughput, and quality degradation.