Video traffic modeling and delivery

Video is becoming a major component of the network traffic, and thus there has been a great interest to model video traffic. It is known that video traffic possesses short range dependence (SRD) and long range dependence (LRD) properties, which can drastically affect network performance. By decomposing a video sequence into three parts, according to its motion activity, Markov-modulated self-similar process model is first proposed to capture autocorrelation function (ACF) characteristics of MPEG video traffic. Furthermore, generalized Beta distribution is proposed to model the probability density functions (PDFs) of MPEG video traffic. It is observed that the ACF of MPEG video traffic fluctuates around three envelopes, reflecting the fact that different coding methods reduce the data dependency by different amount. This observation has led to a more accurate model, structurally modulated self-similar process model, which captures the ACF of the traffic, both SRD and LRD, by exploiting the MPEG structure. This model is subsequently simplified by simply modulating three self-similar processes, resulting in a much simpler model having the same accuracy as the structurally modulated self-similar process model. To justify the validity of the proposed models for video transmission, the cell loss ratios (CLRs) of a server with a limited buffer size driven by the empirical trace are compared to those driven by the proposed models. The differences are within one order, which are hardly achievable by other models, even for the case of JPEG video traffic. In the second part of this dissertation, two dynamic bandwidth allocation algorithms are proposed for pre-recorded and real-time video delivery, respectively. One is based on scene change identification, and the other is based on frame differences. The proposed algorithms can increase the bandwidth utilization by a factor of two to five, as compared to the constant bit rate (CBR) service using peak rate assignment

Video Traffic Modeling using Kolmogorov Smirnov Analysis in Broadband Network

Video Traffic utilization is one of the major issues for Quality of Service (QoS) for network traffic especially in broadband network. Most network administrators are looking at providing best QoS and reliable traffic performances especially on video traffic. Analysis on recent trend and modeling video traffic activity is a crucial task in providing better bandwidth usage. This research presents an analysis on video network traffic in a Broadband Network in Malaysia. Real data from a telecommunications service company based for Business and Home network are collected. Traffic characterization is analyzed and new traffic parameters and model are presented. Goodness of fit (GoF) and Kolmogorov Smirnov (KS) test is used to fit the real traffic in getting the best Traffic distribution model. Results present four top video used in the network traffic which are You Tube, MPEG, TV on Streamyx and Dailymotion using standard video protocol. Fitted traffics presents Pareto model is best fitted on video traffic. Generalized Pareto (GP) with Empirical Cumulative Distribution function (CDF) distribution is identified as the best distribution model. The fitted Generalized Pareto model was identified based on lower Kolmogorov-Smirnov (KS) value and higher probability value (p-value). Test statistics for four particular distribution results at 5% level significance. GP characterization presents three important parameters which are shape, scale and location. A new mathematical formulation is derived based on control parameters gathered for future rate limiting algorithm

SDN and NFV for satellite infrastructures

The integration of SDN and NFV enablers into the satellite network could prove to be an essential means to save on physical sites, improve the time to bring new services to the market and open new ways to improve network resiliency, availability and efficiency. It can be considered that the above two enablers can play a central role in the integration of satellite to terrestrial technologies by using federated management of the network resources.Peer ReviewedPostprint (author's final draft

Performance Measurement Under Increasing Environmental Uncertainty In The Context of Interval Type-2 Fuzzy Logic Based Robotic Sailing

Performance measurement of robotic controllers based on fuzzy logic, operating under uncertainty, is a subject area which has been somewhat ignored in the current literature. In this paper standard measures such as RMSE are shown to be inappropriate for use under conditions where the environmental uncertainty changes significantly between experiments. An overview of current methods which have been applied by other authors is presented, followed by a design of a more sophisticated method of comparison. This method is then applied to a robotic control problem to observe its outcome compared with a single measure. Results show that the technique described provides a more robust method of performance comparison than less complex methods allowing better comparisons to be drawn.Comment: International Conference on Fuzzy Systems 2013 (Fuzz-IEEE 2013

Adaptive Edge-Oriented Shot Boundary Detection

We study the problem of video shot boundary detection using an adaptive edge-oriented framework. Our approach is distinct in its use of multiple multilevel features in the required processing. Adaptation is provided by a careful analysis of these multilevel features, based on shot variability. We consider three levels of adaptation: at the feature extraction stage using locally-adaptive edge maps, at the video sequence level, and at the individual shot level. We show how to provide adaptive parameters for the multilevel edge-based approach, and how to determine adaptive thresholds for the shot boundaries based on the characteristics of the particular shot being indexed. The result is a fast adaptive scheme that provides a slightly better performance in terms of robustness, and a five fold efficiency improvement in shot characterization and classification. The reported work has applications beyond direct video indexing, and could be used in real-time applications, such as in dynamic monitoring and modeling of video data traffic in multimedia communications, and in real-time video surveillance. Experimental results are included

Використання інтервальних функцій належності в задачах кластеризації даних соціального характеру

Розглянуто вплив рівня нечіткості на результати нечіткого кластерного аналізу. Запропоновано підхід до розв’язання задачі кластеризації на основі інтервальних нечітких множин типу 2 із застосуванням індексу вірогідності Квона. Роботу методу продемонстровано на прикладі кластеризації країн світу за рівнем розвитку.Рассмотрено влияние уровня нечеткости на результаты нечеткого кластерного анализа. Предложен подход к решению задачи кластеризации на основе интервальных нечетких множеств типа 2 с применением индекса достоверности Квона. Робота метода продемонстрирована на примере кластеризации стран мира по уровню развития.An approach to the solution of clustering problem on the basis of interval fuzzy sets of 2 type using know validity index, is proposed. The methods working is show on the example of the world countries clustering according to their development level. Influence of degree of fuzziness on fuzzy clustering results is investigated

Использование интервальных функций принадлежности в задачах кластеризации данных социального характера

Розглянуто вплив рівня нечіткості на результати нечіткого кластерного аналізу. Запропоновано підхід до розв’язання задачі кластеризації на основі інтервальних нечітких множин типу 2 із застосуванням індексу вірогідності Квона. Роботу методу продемонстровано на прикладі кластеризації країн світу за рівнем розвитку.An approach to the solution of clustering problem on the basis of interval fuzzy sets of 2 type using know validity index, is proposed. The methods working is show on the example of the world countries clustering according to their development level. Influence of degree of fuzziness on fuzzy clustering results is investigated.Рассмотрено влияние уровня нечеткости на результаты нечеткого кластерного анализа. Предложен подход к решению задачи кластеризации на основе интервальных нечетких множеств типа 2 с применением индекса достоверности Квона. Робота метода продемонстрирована на примере кластеризации стран мира по уровню развития