Quality-driven resource utilization methods for video streaming in wireless communication networks

This research is focused on the optimisation of resource utilisation in wireless mobile networks with the consideration of the users’ experienced quality of video streaming services. The study specifically considers the new generation of mobile communication networks, i.e. 4G-LTE, as the main research context. The background study provides an overview of the main properties of the relevant technologies investigated. These include video streaming protocols and networks, video service quality assessment methods, the infrastructure and related functionalities of LTE, and resource allocation algorithms in mobile communication systems. A mathematical model based on an objective and no-reference quality assessment metric for video streaming, namely Pause Intensity, is developed in this work for the evaluation of the continuity of streaming services. The analytical model is verified by extensive simulation and subjective testing on the joint impairment effects of the pause duration and pause frequency. Various types of the video contents and different levels of the impairments have been used in the process of validation tests. It has been shown that Pause Intensity is closely correlated with the subjective quality measurement in terms of the Mean Opinion Score and this correlation property is content independent. Based on the Pause Intensity metric, an optimised resource allocation approach is proposed for the given user requirements, communication system specifications and network performances. This approach concerns both system efficiency and fairness when establishing appropriate resource allocation algorithms, together with the consideration of the correlation between the required and allocated data rates per user. Pause Intensity plays a key role here, representing the required level of Quality of Experience (QoE) to ensure the best balance between system efficiency and fairness. The 3GPP Long Term Evolution (LTE) system is used as the main application environment where the proposed research framework is examined and the results are compared with existing scheduling methods on the achievable fairness, efficiency and correlation. Adaptive video streaming technologies are also investigated and combined with our initiatives on determining the distribution of QoE performance across the network. The resulting scheduling process is controlled through the prioritization of users by considering their perceived quality for the services received. Meanwhile, a trade-off between fairness and efficiency is maintained through an online adjustment of the scheduler’s parameters. Furthermore, Pause Intensity is applied to act as a regulator to realise the rate adaptation function during the end user’s playback of the adaptive streaming service. The adaptive rates under various channel conditions and the shape of the QoE distribution amongst the users for different scheduling policies have been demonstrated in the context of LTE. Finally, the work for interworking between mobile communication system at the macro-cell level and the different deployments of WiFi technologies throughout the macro-cell is presented. A QoEdriven approach is proposed to analyse the offloading mechanism of the user’s data (e.g. video traffic) while the new rate distribution algorithm reshapes the network capacity across the macrocell. The scheduling policy derived is used to regulate the performance of the resource allocation across the fair-efficient spectrum. The associated offloading mechanism can properly control the number of the users within the coverages of the macro-cell base station and each of the WiFi access points involved. The performance of the non-seamless and user-controlled mobile traffic offloading (through the mobile WiFi devices) has been evaluated and compared with that of the standard operator-controlled WiFi hotspots.

Narrative pace control practices in the digital age:how do people consume television (tv) series?

Digital devices are profoundly changing the way individuals consume media entertainment, and in particular television (TV). Our research contributes to prior work on narrative processing by advancing a more comprehensive theorization of narrative pace when control is in the hands of story receivers as opposed to storytellers. Using the empirical context of TV series viewing we draw on in-depth interviews to uncover 1) consumer narrative pace control practices such as multi-episode viewing sometimes colloquially called “binge-watching” or replaying specific scenes, and 2) the factors that drive the adoption of such practices, including the countervailing forces of narrative satiation and need for closure, as well as curiosity and enjoyment of mystery.

Developing a new SVPWM control strategy for open-winding brushless doubly fed reluctance generators

In this paper, a new open-winding control strategy is proposed for a brushless doubly fed reluctance generator (BDFRG) used for stand-alone wind turbine or ship generators. The BDFRG is characterized with two windings on the stator: a power winding and a control winding. The control winding is fed with dual two-level three-phase converters, and a vector control scheme based on space vector pulsewidth modulation is designed. Compared with traditional three-level inverter systems, the dc-link voltage and the voltage rating of power devices in the proposed system are reduced by 50% while still greatly improving the reliability, redundancy, and fault tolerance of the proposed system by increasing the switching modes. Its performance is evaluated by simulation in MATLAB/Simulink and an experimental study on a 42-kW prototype machine.

Hybrid approaches to estimating freeway travel times using point traffic detector data

The accurate and reliable estimation of travel time based on point detector data is needed to support Intelligent Transportation System (ITS) applications. It has been found that the quality of travel time estimation is a function of the method used in the estimation and varies for different traffic conditions. In this study, two hybrid on-line travel time estimation models, and their corresponding off-line methods, were developed to achieve better estimation performance under various traffic conditions, including recurrent congestion and incidents. The first model combines the Mid-Point method, which is a speed-based method, with a traffic flow-based method. The second model integrates two speed-based methods: the Mid-Point method and the Minimum Speed method. In both models, the switch between travel time estimation methods is based on the congestion level and queue status automatically identified by clustering analysis. During incident conditions with rapidly changing queue lengths, shock wave analysis-based refinements are applied for on-line estimation to capture the fast queue propagation and recovery. Travel time estimates obtained from existing speed-based methods, traffic flow-based methods, and the models developed were tested using both simulation and real-world data. The results indicate that all tested methods performed at an acceptable level during periods of low congestion. However, their performances vary with an increase in congestion. Comparisons with other estimation methods also show that the developed hybrid models perform well in all cases. Further comparisons between the on-line and off-line travel time estimation methods reveal that off-line methods perform significantly better only during fast-changing congested conditions, such as during incidents. The impacts of major influential factors on the performance of travel time estimation, including data preprocessing procedures, detector errors, detector spacing, frequency of travel time updates to traveler information devices, travel time link length, and posted travel time range, were investigated in this study. The results show that these factors have more significant impacts on the estimation accuracy and reliability under congested conditions than during uncongested conditions. For the incident conditions, the estimation quality improves with the use of a short rolling period for data smoothing, more accurate detector data, and frequent travel time updates.

Optimizing storage and memory systems for energy and performance

Electrical energy is an essential resource for the modern world. Unfortunately, its price has almost doubled in the last decade. Furthermore, energy production is also currently one of the primary sources of pollution. These concerns are becoming more important in data-centers. As more computational power is required to serve hundreds of millions of users, bigger data-centers are becoming necessary. This results in higher electrical energy consumption. Of all the energy used in data-centers, including power distribution units, lights, and cooling, computer hardware consumes as much as 80%. Consequently, there is opportunity to make data-centers more energy efficient by designing systems with lower energy footprint. Consuming less energy is critical not only in data-centers. It is also important in mobile devices where battery-based energy is a scarce resource. Reducing the energy consumption of these devices will allow them to last longer and re-charge less frequently. Saving energy in computer systems is a challenging problem. Improving a system's energy efficiency usually comes at the cost of compromises in other areas such as performance or reliability. In the case of secondary storage, for example, spinning-down the disks to save energy can incur high latencies if they are accessed while in this state. The challenge is to be able to increase the energy efficiency while keeping the system as reliable and responsive as before. This thesis tackles the problem of improving energy efficiency in existing systems while reducing the impact on performance. First, we propose a new technique to achieve fine grained energy proportionality in multi-disk systems; Second, we design and implement an energy-efficient cache system using flash memory that increases disk idleness to save energy; Finally, we identify and explore solutions for the page fetch-before-update problem in caching systems that can: (a) control better I/O traffic to secondary storage and (b) provide critical performance improvement for energy efficient systems.

Development and verification of control and protection strategies in hybrid AC/DC power systems for smart grid applications

Modern power networks incorporate communications and information technology infrastructure into the electrical power system to create a smart grid in terms of control and operation. The smart grid enables real-time communication and control between consumers and utility companies allowing suppliers to optimize energy usage based on price preference and system technical issues. The smart grid design aims to provide overall power system monitoring, create protection and control strategies to maintain system performance, stability and security. This dissertation contributed to the development of a unique and novel smart grid test-bed laboratory with integrated monitoring, protection and control systems. This test-bed was used as a platform to test the smart grid operational ideas developed here. The implementation of this system in the real-time software creates an environment for studying, implementing and verifying novel control and protection schemes developed in this dissertation. Phasor measurement techniques were developed using the available Data Acquisition (DAQ) devices in order to monitor all points in the power system in real time. This provides a practical view of system parameter changes, system abnormal conditions and its stability and security information system. These developments provide valuable measurements for technical power system operators in the energy control centers. Phasor Measurement technology is an excellent solution for improving system planning, operation and energy trading in addition to enabling advanced applications in Wide Area Monitoring, Protection and Control (WAMPAC). Moreover, a virtual protection system was developed and implemented in the smart grid laboratory with integrated functionality for wide area applications. Experiments and procedures were developed in the system in order to detect the system abnormal conditions and apply proper remedies to heal the system. A design for DC microgrid was developed to integrate it to the AC system with appropriate control capability. This system represents realistic hybrid AC/DC microgrids connectivity to the AC side to study the use of such architecture in system operation to help remedy system abnormal conditions. In addition, this dissertation explored the challenges and feasibility of the implementation of real-time system analysis features in order to monitor the system security and stability measures. These indices are measured experimentally during the operation of the developed hybrid AC/DC microgrids. Furthermore, a real-time optimal power flow system was implemented to optimally manage the power sharing between AC generators and DC side resources. A study relating to real-time energy management algorithm in hybrid microgrids was performed to evaluate the effects of using energy storage resources and their use in mitigating heavy load impacts on system stability and operational security.

Incorporating variable peak -to -daily ratios in the equilibrium traffic assignment procedure of the Florida Standard Urban Transportation Modeling Structure (FSUTMS)

The standard highway assignment model in the Florida Standard Urban Transportation Modeling Structure (FSUTMS) is based on the equilibrium traffic assignment method. This method involves running several iterations of all-or-nothing capacity-restraint assignment with an adjustment of travel time to reflect delays encountered in the associated iteration. The iterative link time adjustment process is accomplished through the Bureau of Public Roads (BPR) volume-delay equation. Since FSUTMS' traffic assignment procedure outputs daily volumes, and the input capacities are given in hourly volumes, it is necessary to convert the hourly capacities to their daily equivalents when computing the volume-to-capacity ratios used in the BPR function. The conversion is accomplished by dividing the hourly capacity by a factor called the peak-to-daily ratio, or referred to as CONFAC in FSUTMS. The ratio is computed as the highest hourly volume of a day divided by the corresponding total daily volume. ^ While several studies have indicated that CONFAC is a decreasing function of the level of congestion, a constant value is used for each facility type in the current version of FSUTMS. This ignores the different congestion level associated with each roadway and is believed to be one of the culprits of traffic assignment errors. Traffic counts data from across the state of Florida were used to calibrate CONFACs as a function of a congestion measure using the weighted least squares method. The calibrated functions were then implemented in FSUTMS through a procedure that takes advantage of the iterative nature of FSUTMS' equilibrium assignment method. ^ The assignment results based on constant and variable CONFACs were then compared against the ground counts for three selected networks. It was found that the accuracy from the two assignments was not significantly different, that the hypothesized improvement in assignment results from the variable CONFAC model was not empirically evident. It was recognized that many other factors beyond the scope and control of this study could contribute to this finding. It was recommended that further studies focus on the use of the variable CONFAC model with recalibrated parameters for the BPR function and/or with other forms of volume-delay functions. ^

Background traffic modeling for large-scale network simulation

Network simulation is an indispensable tool for studying Internet-scale networks due to the heterogeneous structure, immense size and changing properties. It is crucial for network simulators to generate representative traffic, which is necessary for effectively evaluating next-generation network protocols and applications. With network simulation, we can make a distinction between foreground traffic, which is generated by the target applications the researchers intend to study and therefore must be simulated with high fidelity, and background traffic, which represents the network traffic that is generated by other applications and does not require significant accuracy. The background traffic has a significant impact on the foreground traffic, since it competes with the foreground traffic for network resources and therefore can drastically affect the behavior of the applications that produce the foreground traffic. This dissertation aims to provide a solution to meaningfully generate background traffic in three aspects. First is realism. Realistic traffic characterization plays an important role in determining the correct outcome of the simulation studies. This work starts from enhancing an existing fluid background traffic model by removing its two unrealistic assumptions. The improved model can correctly reflect the network conditions in the reverse direction of the data traffic and can reproduce the traffic burstiness observed from measurements. Second is scalability. The trade-off between accuracy and scalability is a constant theme in background traffic modeling. This work presents a fast rate-based TCP (RTCP) traffic model, which originally used analytical models to represent TCP congestion control behavior. This model outperforms other existing traffic models in that it can correctly capture the overall TCP behavior and achieve a speedup of more than two orders of magnitude over the corresponding packet-oriented simulation. Third is network-wide traffic generation. Regardless of how detailed or scalable the models are, they mainly focus on how to generate traffic on one single link, which cannot be extended easily to studies of more complicated network scenarios. This work presents a cluster-based spatio-temporal background traffic generation model that considers spatial and temporal traffic characteristics as well as their correlations. The resulting model can be used effectively for the evaluation work in network studies.

A Static Traffic Assignment Model Combined with an Artificial Neural Network Delay Model

As traffic congestion continues to worsen in large urban areas, solutions are urgently sought. However, transportation planning models, which estimate traffic volumes on transportation network links, are often unable to realistically consider travel time delays at intersections. Introducing signal controls in models often result in significant and unstable changes in network attributes, which, in turn, leads to instability of models. Ignoring the effect of delays at intersections makes the model output inaccurate and unable to predict travel time. To represent traffic conditions in a network more accurately, planning models should be capable of arriving at a network solution based on travel costs that are consistent with the intersection delays due to signal controls. This research attempts to achieve this goal by optimizing signal controls and estimating intersection delays accordingly, which are then used in traffic assignment. Simultaneous optimization of traffic routing and signal controls has not been accomplished in real-world applications of traffic assignment. To this end, a delay model dealing with five major types of intersections has been developed using artificial neural networks (ANNs). An ANN architecture consists of interconnecting artificial neurons. The architecture may either be used to gain an understanding of biological neural networks, or for solving artificial intelligence problems without necessarily creating a model of a real biological system. The ANN delay model has been trained using extensive simulations based on TRANSYT-7F signal optimizations. The delay estimates by the ANN delay model have percentage root-mean-squared errors (%RMSE) that are less than 25.6%, which is satisfactory for planning purposes. Larger prediction errors are typically associated with severely oversaturated conditions. A combined system has also been developed that includes the artificial neural network (ANN) delay estimating model and a user-equilibrium (UE) traffic assignment model. The combined system employs the Frank-Wolfe method to achieve a convergent solution. Because the ANN delay model provides no derivatives of the delay function, a Mesh Adaptive Direct Search (MADS) method is applied to assist in and expedite the iterative process of the Frank-Wolfe method. The performance of the combined system confirms that the convergence of the solution is achieved, although the global optimum may not be guaranteed.

Fabrication of a two-terminal super conducting device with a poled ferroelectric control layer

The discovery of High-Temperature Superconductors (HTSCs) has spurred the need for the fabrication of superconducting electronic devices able to match the performance of today's semiconductor devices. While there are several HTSCs in use today, YBaCuO7-x (YBCO) is the better characterized and more widely used material for small electronic applications. This thesis explores the fabrication of a Two-Terminal device with a superconductor and a painted on electrode as the terminals and a ferroelectric, BaTiO 3 (BTO), in between. The methods used to construct such a device and the challenges faced with the fabrication of a viable device will be examined. The ferroelectric layer of the devices that proved adequate for use were poled by the application of an electric field. Temperature Bias Poling used an applied field of 105V/cm at a temperature of approximately 135*C. High Potential Poling used an applied field of 106V/cm at room temperature (20*C). The devices were then tested for a change in their superconducting critical temperature, Tc. A shift of 1-2K in the Tc(onset) of YBCO was observed for Temperature Bias Poling and a shift of 2-6K for High Potential Poling. These are the first reported results of the field effect using BTO on YBCO. The mechanism involved in the shifting of Tc will be discussed along with possible applications.

Internet Protocol (IP) design and implementation for efficient mobility to devices in wireless networks

The purpose of this thesis was to develop an efficient routing protocol which would provide mobility support to the mobile devices roaming within a network. The routing protocol need to be compatible with the existing internet architecture. The routing protocol proposed here is based on the Mobile IP routing protocol and could solve some of the problems existing in current Mobile IP implementation e.g. ingress filtering problem. By implementing an efficient timeout mechanism and introducing Paging mechanism to the wireless network, the protocol minimizes the number of control messages sent over the network. The implementation of the system is primarily done on three components: 1) Mobile devices that need to gain access to the network, 2) Router which would be providing roaming support to the mobile devices and 3) Database server providing basic authentication services on the system. As a result, an efficient IP routing protocol is developed which would provide seamless mobility to the mobile devices on the network.

Controle de mobilidade infraestruturado e orientado à qualidade para maximização de admissões em sistemas WiNeMO: uma abordagem definida por software

The spread of wireless networks and growing proliferation of mobile devices require the development of mobility control mechanisms to support the different demands of traffic in different network conditions. A major obstacle to developing this kind of technology is the complexity involved in handling all the information about the large number of Moving Objects (MO), as well as the entire signaling overhead required to manage these procedures in the network. Despite several initiatives have been proposed by the scientific community to address this issue they have not proved to be effective since they depend on the particular request of the MO that is responsible for triggering the mobility process. Moreover, they are often only guided by wireless medium statistics, such as Received Signal Strength Indicator (RSSI) of the candidate Point of Attachment (PoA). Thus, this work seeks to develop, evaluate and validate a sophisticated communication infrastructure for Wireless Networking for Moving Objects (WiNeMO) systems by making use of the flexibility provided by the Software-Defined Networking (SDN) paradigm, where network functions are easily and efficiently deployed by integrating OpenFlow and IEEE 802.21 standards. For purposes of benchmarking, the analysis was conducted in the control and data planes aspects, which demonstrate that the proposal significantly outperforms typical IPbased SDN and QoS-enabled capabilities, by allowing the network to handle the multimedia traffic with optimal Quality of Service (QoS) transport and acceptable Quality of Experience (QoE) over time.

Air traffic controllers at work

Inscription: Verso: Gail Bassam (left) and Margaret Bellamy (right), air traffic controllers, Teterboro Airport, New Jersey.

Direct power control with common mode voltage elimination for open-winding brushless doubly-fed wind power generators

In this paper, a new open-winding control strategy is proposed for a brushless doubly-fed reluctance generator (BDFRG) applicable for wind turbines. The BDFRG control winding is fed via a dual two-level three-phase converter using a single dc bus. Direct power control based on maximum power point tracking with common mode voltage elimination is designed, which not only the active and reactive power is decoupled, but the reliability and redundancy are all improved greatly by increasing the switching modes of operation, while DC-link voltage and rating of power devices decreased by 50% comparing to the traditional three-level converter systems. Consequently its effectiveness is evaluated by simulation tests based on a 42-kW prototype generator.

AuxAg1-x alloy seeds: A way to control growth, morphology and defect formation in Ge nanowires

Germanium (Ge) nanowires are of current research interest for high speed nanoelectronic devices due to the lower band gap and high carrier mobility compatible with high K-dielectrics and larger excitonic Bohr radius ensuing a more pronounced quantum confinement effect [1-6]. A general way for the growth of Ge nanowires is to use liquid or a solid growth promoters in a bottom-up approach which allow control of the aspect ratio, diameter, and structure of 1D crystals via external parameters, such as precursor feedstock, temperature, operating pressure, precursor flow rate etc [3, 7-11]. The Solid-phase seeding is preferred for more control processing of the nanomaterials and potential suppression of the unintentional incorporation of high dopant concentrations in semiconductor nanowires and unrequired compositional tailing of the seed-nanowire interface [2, 5, 9, 12]. There are therefore distinct features of the solid phase seeding mechanism that potentially offer opportunities for the controlled processing of nanomaterials with new physical properties. A superior control over the growth kinetics of nanowires could be achieved by controlling the inherent growth constraints instead of external parameters which always account for instrumental inaccuracy. The high dopant concentrations in semiconductor nanowires can result from unintentional incorporation of atoms from the metal seed material, as described for the Al catalyzed VLS growth of Si nanowires [13] which can in turn be depressed by solid-phase seeding. In addition, the creation of very sharp interfaces between group IV semiconductor segments has been achieved by solid seeds [14], whereas the traditionally used liquid Au particles often leads to compositional tailing of the interface [15] . Korgel et al. also described the superior size retention of metal seeds in a SFSS nanowire growth process, when compared to a SFLS process using Au colloids [12]. Here in this work we have used silver and alloy seed particle with different compositions to manipulate the growth of nanowires in sub-eutectic regime. The solid seeding approach also gives an opportunity to influence the crystallinity of the nanowires independent of the substrate. Taking advantage of the readily formation of stacking faults in metal nanoparticles, lamellar twins in nanowires could be formed.