QoS provisioning in multimedia streaming

Multimedia consists of voice, video, and data. Sample applications include video conferencing, video on demand, distance learning, distributed games, and movies on demand. Providing Quality of Service (QoS) for multimedia streaming has been a difficult and challenging problem. When multimedia traffic is transported over a network, video traffic, though usually compressed/encoded for bandwidth reduction, still consumes most of the bandwidth. In addition, compressed video streams typically exhibit highly variable bit rates as well as long range dependence properties, thus exacerbating the challenge in meeting the stringent QoS requirements of multimedia streaming with high network utilization. Dynamic bandwidth allocation in which video traffic prediction can play an important role is thus needed. Prediction of the variation of the I frame size using Least Mean Square (LMS) is first proposed. Owing to a smoother sequence, better prediction has been achieved as compared to the composite MPEG video traffic prediction scheme. One problem with this LMS algorithm is its slow convergence. In Variable Bit Rate (VBR) videos characterized by frequent scene changes, the LMS algorithm may result in an extended period of intractability, and thus may experience excessive cell loss during scene changes. A fast convergent non-linear predictor called Variable Step-size Algorithm (VSA) is subsequently proposed to overcome this drawback. The VSA algorithm not only incurs small prediction errors but more importantly achieves fast convergence. It tracks scene changes better than LMS. Bandwidth is then assigned based on the predicted I frame size which is usually the largest in a Group of Picture (GOP). Hence, the Cell Loss Ratio (CLR) can be kept small. By reserving bandwidth at least equal to the predicted one, only prediction errors need to be buffered. Since the prediction error was demonstrated to resemble white noise or exhibits at most short term memory, smaller buffers, less delay, and higher bandwidth utilization can be achieved. In order to further improve network bandwidth utilization, a QoS guaranteed on-line bandwidth allocation is proposed. This method allocates the bandwidth based on the predicted GOP and required QoS. Simulations and analytical results demonstrate that this scheme provides guaranteed delay and achieves higher bandwidth utilization. Network traffic is generally accepted to be self similar. Aggregating self similar traffic can actually intensify rather than diminish burstiness. Thus, traffic prediction plays an important role in network management. Least Mean Kurtosis (LMK), which uses the negated kurtosis of the error signal as the cost function, is proposed to predict the self similar traffic. Simulation results show that the prediction performance is improved greatly as compared to the LMS algorithm. Thus, it can be used to effectively predict the real time network traffic. The Differentiated Service (DiffServ) model is a less complex and more scalable solution for providing QoS to IP as compared to the Integrated Service (IntServ) model. We propose to transport MPEG frames through various service classes of DiffServ according to the MPEG video characteristics. Performance analysis and simulation results show that our proposed approach can not only guarantee QoS but can also achieve high bandwidth utilization. As the end video quality is determined not only by the network QoS but also by the encoded video quality, we consider video quality from these two aspects and further propose to transport spatial scalable encoded videos over DiffServ. Performance analysis and simulation results show that this can provision QoS guarantees. The dropping policy we propose at the egress router can reduce the traffic load as well as the risk of congestion in other domains

Improved learning automata applied to routing in multi-service networks

Multi-service communications networks are generally designed, provisioned and configured, based on source-destination user demands expected to occur over a recurring time period. However due to network users' actions being non-deterministic, actual user demands will vary from those expected, potentially causing some network resources to be under- provisioned, with others possibly over-provisioned. As actual user demands vary over the recurring time period from those expected, so the status of the various shared network resources may also vary. This high degree of uncertainty necessitates using adaptive resource allocation mechanisms to share the finite network resources more efficiently so that more of actual user demands may be accommodated onto the network. The overhead for these adaptive resource allocation mechanisms must be low in order to scale for use in large networks carrying many source-destination user demands. This thesis examines the use of stochastic learning automata for the adaptive routing problem (these being adaptive, distributed and simple in implementation and operation) and seeks to improve their weakness of slow convergence whilst maintaining their strength of subsequent near optimal performance. Firstly, current reinforcement algorithms (the part causing the automaton to learn) are examined for applicability, and contrary to the literature the discretised schemes are found in general to be unsuitable. Two algorithms are chosen (one with fast convergence, the other with good subsequent performance) and are improved through automatically adapting the learning rates and automatically switching between the two algorithms. Both novel methods use local entropy of action probabilities for determining convergence state. However when the convergence speed and blocking probability is compared to a bandwidth-based dynamic link-state shortest-path algorithm, the latter is found to be superior. A novel re-application of learning automata to the routing problem is therefore proposed: using link utilisation levels instead of call acceptance or packet delay. Learning automata now return a lower blocking probability than the dynamic shortest-path based scheme under realistic loading levels, but still suffer from a significant number of convergence iterations. Therefore the final improvement is to combine both learning automata and shortest-path concepts to form a hybrid algorithm. The resulting blocking probability of this novel routing algorithm is superior to either algorithm, even when using trend user demands

Measurement and application of many-to-one data flows.

Ho, Po Yee.Thesis (M.Phil.)--Chinese University of Hong Kong, 2007.Includes bibliographical references (leaves 77-81).Abstracts in English and Chinese.Acknowledgements --- p.iAbstract --- p.ii摘要 --- p.iiiChapter Chapter 1 --- Introduction --- p.1Chapter Chapter 2 --- Background and Related Work --- p.4Chapter 2.1 --- Link/Path Capacity --- p.4Chapter 2.2 --- Unutilized Bandwidth --- p.5Chapter 2.3 --- Achievable Bandwidth --- p.5Chapter Chapter 3 --- Measurement Methodology --- p.7Chapter 3.1 --- PlanetLab Measurement --- p.8Chapter 3.2 --- FTP Measurement --- p.10Chapter Chapter 4 --- Analysis of Measurement Data --- p.12Chapter 4.1 --- Per-Flow Achievable Bandwidth --- p.13Chapter 4.2 --- Inter-Flow Correlation --- p.14Chapter 4.3 --- Intra-Flow Temporal Correlation --- p.16Chapter 4.4 --- Intra-Flow Bandwidth Variation --- p.18Chapter 4.5 --- Predictability of Bandwidth Properties --- p.22Chapter 4.6 --- Long-term Flow Properties --- p.26Chapter Chapter 5 --- A Mathematical Framework --- p.28Chapter 5.1 --- Bandwidth Variations --- p.28Chapter 5.2 --- Bandwidth Predictability --- p.31Chapter 5.3 --- Sensitivity Analysis --- p.34Chapter Chapter 6 --- Predictive Buffering Algorithm --- p.41Chapter 6.1 --- Related Work --- p.43Chapter 6.2 --- System Model --- p.44Chapter 6.3 --- Prediction Algorithm for Constant Bit-Rate Videos --- p.45Chapter 6.4 --- Prediction Algorithm for Variable Bit-Rate Videos --- p.46Chapter 6.5 --- Parameter Estimation --- p.47Chapter Chapter 7 --- Performance Evaluation --- p.49Chapter 7.1 --- Trace-Driven Simulation Setup --- p.49Chapter 7.2 --- Performance over CBR Videos --- p.50Chapter 7.2.1 --- Video Playback Performance --- p.51Chapter 7.2.2 --- Buffering Time --- p.57Chapter 7.3 --- Performance over VBR Videos --- p.61Chapter 7.3.1 --- Video Playback Performance --- p.62Chapter 7.3.2 --- Buffering Time --- p.66Chapter Chapter 8 --- Future Work --- p.69Chapter 8.1 --- Playback Rate Adaptation --- p.70Chapter 8.2 --- Sender Selection Algorithm --- p.71Chapter 8.3 --- Dynamic Flow Allocation --- p.72Chapter 8.4 --- Predictive Flow Allocation --- p.73Chapter 8.5 --- Challenge in P2P Applications --- p.74Chapter Chapter 9 --- Conclusion --- p.76Bibliograph

Life patterns : structure from wearable sensors

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, February 2003.Includes bibliographical references (leaves 123-129).In this thesis I develop and evaluate computational methods for extracting life's patterns from wearable sensor data. Life patterns are the reoccurring events in daily behavior, such as those induced by the regular cycle of night and day, weekdays and weekends, work and play, eating and sleeping. My hypothesis is that since a "raw, low-level" wearable sensor stream is intimately connected to the individual's life, it provides the means to directly match similar events, statistically model habitual behavior and highlight hidden structures in a corpus of recorded memories. I approach the problem of computationally modeling daily human experience as a task of statistical data mining similar to the earlier efforts of speech researchers searching for the building block that were believed to make up speech. First we find the atomic immutable events that mark the succession of our daily activities. These are like the "phonemes" of our lives, but don't necessarily take on their finite and discrete nature. Since our activities and behaviors operate at multiple time-scales from seconds to weeks, we look at how these events combine into sequences, and then sequences of sequences, and so on. These are the words, sentences and grammars of an individual's daily experience. I have collected 100 days of wearable sensor data from an individual's life. I show through quantitative experiments that clustering, classification, and prediction is feasible on a data set of this nature. I give methods and results for determining the similarity between memories recorded at different moments in time, which allow me to associate almost every moment of an individual's life to another similar moment. I present models that accurately and automatically classify the sensor data into location and activity.(cont.) Finally, I show how to use the redundancies in an individual's life to predict his actions from his past behavior.by Brian Patrick Clarkson.Ph.D

Advanced Occupancy Measurement Using Sensor Fusion

With roughly about half of the energy used in buildings attributed to Heating, Ventilation, and Air conditioning (HVAC) systems, there is clearly great potential for energy saving through improved building operations. Accurate knowledge of localised and real-time occupancy numbers can have compelling control applications for HVAC systems. However, existing technologies applied for building occupancy measurements are limited, such that a precise and reliable occupant count is difficult to obtain. For example, passive infrared (PIR) sensors commonly used for occupancy sensing in lighting control applications cannot differentiate between occupants grouped together, video sensing is often limited by privacy concerns, atmospheric gas sensors (such as CO2 sensors) may be affected by the presence of electromagnetic (EMI) interference, and may not show clear links between occupancy and sensor values. Past studies have indicated the need for a heterogeneous multi-sensory fusion approach for occupancy detection to address the short-comings of existing occupancy detection systems. The aim of this research is to develop an advanced instrumentation strategy to monitor occupancy levels in non-domestic buildings, whilst facilitating the lowering of energy use and also maintaining an acceptable indoor climate. Accordingly, a novel multi-sensor based approach for occupancy detection in open-plan office spaces is proposed. The approach combined information from various low-cost and non-intrusive indoor environmental sensors, with the aim to merge advantages of various sensors, whilst minimising their weaknesses. The proposed approach offered the potential for explicit information indicating occupancy levels to be captured. The proposed occupancy monitoring strategy has two main components; hardware system implementation and data processing. The hardware system implementation included a custom made sound sensor and refinement of CO2 sensors for EMI mitigation. Two test beds were designed and implemented for supporting the research studies, including proof-of-concept, and experimental studies. Data processing was carried out in several stages with the ultimate goal being to detect occupancy levels. Firstly, interested features were extracted from all sensory data collected, and then a symmetrical uncertainty analysis was applied to determine the predictive strength of individual sensor features. Thirdly, a candidate features subset was determined using a genetic based search. Finally, a back-propagation neural network model was adopted to fuse candidate multi-sensory features for estimation of occupancy levels. Several test cases were implemented to demonstrate and evaluate the effectiveness and feasibility of the proposed occupancy detection approach. Results have shown the potential of the proposed heterogeneous multi-sensor fusion based approach as an advanced strategy for the development of reliable occupancy detection systems in open-plan office buildings, which can be capable of facilitating improved control of building services. In summary, the proposed approach has the potential to: (1) Detect occupancy levels with an accuracy reaching 84.59% during occupied instances (2) capable of maintaining average occupancy detection accuracy of 61.01%, in the event of sensor failure or drop-off (such as CO2 sensors drop-off), (3) capable of utilising just sound and motion sensors for occupancy levels monitoring in a naturally ventilated space, (4) capable of facilitating potential daily energy savings reaching 53%, if implemented for occupancy-driven ventilation control

Potential markets for advanced satellite communications

This report identifies trends in the volume and type of traffic offered to the U.S. domestic communications infrastructure and extrapolates these trends through the year 2011. To describe how telecommunications service providers are adapting to the identified trends, this report assesses the status, plans, and capacity of the domestic communications infrastructure. Cable, satellite, and radio components of the infrastructure are examined separately. The report also assesses the following major applications making use of the infrastructure: (1) Broadband services, including Broadband Integrated Services Digital Network (BISDN), Switched Multimegabit Data Service (SMDS), and frame relay; (2) mobile services, including voice, location, and paging; (3) Very Small Aperture Terminals (VSAT), including mesh VSAT; and (4) Direct Broadcast Satellite (DBS) for audio and video. The report associates satellite implementation of specific applications with market segments appropriate to their features and capabilities. The volume and dollar value of these market segments are estimated. For the satellite applications able to address the needs of significant market segments, the report also examines the potential of each satellite-based application to capture business from alternative technologies

Choreographing the extended agent : performance graphics for dance theater

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2005.Includes bibliographical references (v. 2, leaves 448-458).The marriage of dance and interactive image has been a persistent dream over the past decades, but reality has fallen far short of potential for both technical and conceptual reasons. This thesis proposes a new approach to the problem and lays out the theoretical, technical and aesthetic framework for the innovative art form of digitally augmented human movement. I will use as example works a series of installations, digital projections and compositions each of which contains a choreographic component - either through collaboration with a choreographer directly or by the creation of artworks that automatically organize and understand purely virtual movement. These works lead up to two unprecedented collaborations with two of the greatest choreographers working today; new pieces that combine dance and interactive projected light using real-time motion capture live on stage. The existing field of"dance technology" is one with many problems. This is a domain with many practitioners, few techniques and almost no theory; a field that is generating "experimental" productions with every passing week, has literally hundreds of citable pieces and no canonical works; a field that is oddly disconnected from modern dance's history, pulled between the practical realities of the body and those of computer art, and has no influence on the prevailing digital art paradigms that it consumes.(cont.) This thesis will seek to address each of these problems: by providing techniques and a basis for "practical theory"; by building artworks with resources and people that have never previously been brought together, in theaters and in front of audiences previously inaccessible to the field; and by proving through demonstration that a profitable and important dialogue between digital art and the pioneers of modern dance can in fact occur. The methodological perspective of this thesis is that of biologically inspired, agent-based artificial intelligence, taken to a high degree of technical depth. The representations, algorithms and techniques behind such agent architectures are extended and pushed into new territory for both interactive art and artificial intelligence. In particular, this thesis ill focus on the control structures and the rendering of the extended agents' bodies, the tools for creating complex agent-based artworks in intense collaborative situations, and the creation of agent structures that can span live image and interactive sound production. Each of these parts becomes an element of what it means to "choreograph" an extended agent for live performance.Marc Downie.Ph.D

What is the role of emotions on football fans in affecting online video virality? (Case study of Salford City FC)

Viral video marketing is an expensive process and there is limited scholarly research about what makes video content go viral. A few online communities such as football clubs are keen to explore video virality to engage their audiences. One such club is the Salford City Football Club (FC) who have sponsored this research. Consequently, this study aims to identify the key factors that drive the virality of online video content. To answer the research questions the STEPPS model by Jonah Berger, the Social Sharing of Emotions Theory (SSET), the Social Identity Theory (SIT) and Theory of Planned Behaviour (TPB) were some of the dominant models and theories in understanding the constructs of online video virality. A predominant variable that the STEPPS and SSET highlighted is emotional response from the video viewer, and thus, was primarily used as the theoretical basis for this work. The primary data in this thesis comprised 60 respondents, of which were 32 football fans and 28 non-football fans. The Facial expression recognition software (Noldus 6.0) was used in combination with an online self-reporting web questionnaire to understand the emotions associated with the propensity to share content. In conjunction with emotions the thesis also investigated the role of groups (I.e. football fans and non-football fans) by analysing their effect on sharing which depicted variations on how both sets of groups respond to viral video and non-viral video stimuli. Subsequently, the following are the original contributions to knowledge: 1)The research made theoretical advancements by examining specific emotions, arousal intensity and fan group dynamic using facial expression analysis on viral video stimuli. The results from the thesis indicate that certain emotions are intrinsically viral and have a higher intention to share. The research indicated that fan group dynamics also have a direct role to play into the extent a video is shared and should be considered as an important variable. The research explored the existence of triggers which are specific events of importance that highlight the exact phase a video is most likely to be shared.2)The research made a methodological advancement in virality studies by developing a unique method for predicting online videos in real time using emotional viewing patterns. Related studies in virality prediction uses statistical algorithms to predict virality, this research took a different approach using the emotionality elicited from viewers obtained from facial expression analysis data. 3) The research made methodological advancements in understanding which method is more concurrent for measuring users’ emotions when watching a video stimulus by comparing facial expression analysis data with self-report. The thesis concludes facial expression analysis is a more robust approach for measuring emotions however not for subjective norms like the “intention to share”

Electrodance as a "being-together": New forms of mediatization in the communication of youth styles

Aquesta tesi s'emmarca en un interès per explorar com els estils i les cultures juvenils són produïts culturalment en un marc de comunicació digital en xarxa com l'actual. Amb aquest objectiu, pren com a objecte d'estudi l'electro dance, un estil de ball jove nascut als suburbis parisencs cap al 2006 i disseminat en anys posteriors globalment, l'aparició i desenvolupament del qual arriba amb la darrera onada de mitjans i plataformes digitals. La tesi proposa, des dels plans teòric i empíric, una anàlisi de les pràctiques quotidianes dels electrodancers que configuren una manera d'«estar tots plegats», i dedica atenció especial a les que fan un ús intensiu dels mitjans digitals recents. Conceptes com mediatization, interface, comunicació broadcast enfront de network integren un marc d'interpretació des del qual s'observa com nocions habituals com les de públic i privat, producció i consum, local i global o interacció cara a cara i tecnològicament mitjançada assoleixen una nova articulació en els nostres dies i esdevenen expressió d'un entorn de comunicació global massiva en constant transformació.Esta tesis se enmarca un interés por explorar cómo los estilos y las culturas juveniles son producidos culturalmente en un marco de comunicación digital en red como el actual. Para ello, toma como objeto de estudio el electro dance, un estilo de baile juvenil nacido en los suburbios parisinos hacia el 2006 y diseminado en años posteriores globamente, cuya aparición y desarrollo se da de la mano de la última ola de medios y plataformas digitales. La tesis propone, desde los planos teórico y empírico, un análisis de las prácticas cotidianas de los electrodancers que dan sentido a una forma de «estar juntos» y dedica especial atención a las que se apoyan intensivamente en el uso de medios digitales recientes. Conceptos como mediatization, interface, comunicación broadcast frente a network conforman un marco de interpretación desde el cual se observa cómo nociones habituales como las de público y privado, producción y consumo, local y global o interacción cara a cara y tecnológicamente mediada adquieren una articulación distintiva en nuestros días y son expresión de un entorno de comunicación masiva global en constante transformación.This thesis focuses on the study of what is known as ElectroDance youth style - i.e. a dance and sound style which began to blossom within Parisian clubs and affluent suburbs in 2006, spreading quickly across the globe in subsequent years. The aim is to explore the way youth cultures and styles are culturally produced under the conditions of the current global network communication environment. The thesis theoretically and empirically analyses electrodancers' everyday practices, paying special attention to those based on an intensive use of new media, that create a sense togetherness among the youth. Concepts such as mediatization, interface and broadcast versus network communication build an interpretative framework which allows a way to look at which of the traditional notions (public and private, production and consumption, global and local, or technologically-mediated and face-to-face interaction) manifest themselves differently nowadays, acquiring thus a new expression at a time when global mass-communication is in constant transformation