Dynamic Buffer Management for Multimedia Services in Beyond 3G Wireless Networks

This paper investigates a dynamic buffer man-agement scheme for QoS control of multimedia services in be-yond 3G wireless systems. The scheme is studied in the context of the state-of-the-art 3.5G system i.e. the High Speed Downlink Packet Access (HSDPA) which enhances 3G UMTS to support high-speed packet switched services. Unlike earlier systems, UMTS-evolved systems from HSDPA and beyond incorporate mechanisms such as packet scheduling and HARQ in the base station necessitating data buffering at the air interface. This introduces a potential bottleneck to end-to-end communication. Hence, buffer management at the air interface is crucial for end-to-end QoS support of multimedia services with multi-plexed parallel diverse flows such as video and data in the same end-user session. The dynamic buffer management scheme for HSDPA multimedia sessions with aggregated real-time and non real-time flows is investigated via extensive HSDPA simulations. The impact of the scheme on end-to-end traffic performance is evaluated with an example multimedia session comprising a real-time streaming flow concurrent with TCP-based non real-time flow. Results demonstrate that the scheme can guar-antee the end-to-end QoS of the real-time streaming flow, whilst simultaneously protecting the non real-time flow from starva-tion resulting in improved end-to-end throughput performance

Dynamic Buffer Management for Multimedia Services in 3.5G Wireless Networks

This paper presents and investigates a dynamic
buffer management scheme for QoS control of multimedia
services in a 3.5G wireless system i.e. the High Speed Downlink
Packet Access (HSDPA). HSDPA was introduced to enhance
UMTS for high-speed packet switched services. With HSDPA,
packet scheduling and HARQ mechanisms in the base station
require data buffering at the air interface thus introducing a
potential bottleneck to end-to-end communication. Hence, for
multimedia services with multiplexed parallel diverse flows
such as video and data in the same end-user session, buffer
management schemes in the base station are essential to support
end-to-end QoS provision. We propose a dynamic buffer management
scheme for HSDPA multimedia sessions with aggregated real-time and non real-time flows in the paper. The end-to-end performance impact of the scheme is evaluated with an example multimedia session comprising a real-time streaming
flow concurrent with TCP-based non real-time flow via extensive HSDPA simulations. Results demonstrate that the scheme can guarantee the end-to-end QoS of the real-time streaming flow, whilst simultaneously protecting non real-time flow from starvation resulting in improved end-to-end throughput performance

A Dynamic Buffer Management Scheme for End-to-End QoS Enhancement of Multi-flow Services in HSDPA

End-user multi-flow services support is a crucial aspect of current and next generation mobile networks. This paper presents a dynamic buffer management strategy for HSDPA end-user multi-flow traffic with aggregated real-time and non-real-time flows. The scheme incorporates dynamic priority switching between the flows for transmission on the HSDPA radio channel. The end-to-end performance of the proposed strategy is investigated with an end-user multi-flow session of simultaneous VoIP and TCP-based downlink traffic using detailed HSDPA system-level simulations. Compared to an equivalent static buffer management scheme, the results show that end-to-end throughput performance gains in the non-real-time flow and better HSDPA channel utilization is attainable without compromising the real-time VoIP flow QoS constraints

Coordinated Design of Phase Measurement Unit and Power System Stabilisers in Large Scale Power System

This paper presents a case-study of a PMU application with PSS support in a real large scale Chinese power system to suppress inter-area oscillations. The paper uses PMU measured feedback signals from a PSS input signal for dynamic torque analysis (DTA). In the paper, a mathematical model of multi-machine power system is described, followed by formation of the residue and DTA indices. Simulations of the model are used with a large-scale power system model to demonstrate the role of PSS and the equivalence of DTA residue indices.

Measurement-based Method for Wind Farm Power System Oscillation Monitoring

The global increase in the penetration of renewable energy is pushing electrical power systems into uncharted territory, especially in terms of transient and dynamic stability. In particular, the greater penetration of wind generation in European power networks is, at times, displacing a significant capacity of conventional synchronous generation with fixed-speed induction generation and now more commonly, doubly-fed induction generators. The impact of such changes in the generation mix requires careful monitoring to assess the impact on transient and dynamic stability. This paper presents a measurement based method for the early detection of power system oscillations, with attention to mode damping, in order to raise alarms and develop strategies to actively improve power system dynamic stability and security. A method is developed based on wavelet transform and support vector data description (SVDD) to detect oscillation modes in wind farm output power, which may excite dynamic instabilities in the wider system. The wavelet transform is used as a filter to identify oscillations in different frequency bands, while SVDD is used to extract dominant features from different scales and generate an assessment boundary according to the extracted features. Poorly damped oscillations of a large magnitude or that are resonant can be alarmed to the system operator, to reduce the risk of system instability. Method evaluation is exemplified used real data from a chosen wind farm.

Novel chiral ionic liquids:physicochemical properties and investigation of the internal rotameric behaviour in the neat system

Optically active S-alkyl-N, N'-bis((S)-1-phenylethyl) thiouronium salts, abbreviated as (S)-[Cnpetu] Y (where Y is an anion; n = 1, 2, 3, 4, 6, 8, 10, 12 or 16), have been prepared and studied by a broad spectrum of analyses. This consists of density, viscosity, and conductivity determination, followed by a discussion of relevant correlations. Unusual trends depending on the S-alkyl chain length were documented for (S)-[Cnpetu][ NTf2] series (where [NTf2] = bis{(trifluoromethyl) sulfonyl} amide), including the viscosity decreasing with increasing chain length, and the conductivity showing a maximum between the S-butyl and the S-hexyl derivative. In addition, a hindered rotamerism of the thiouronium cation in dmso-d(6) solution was recognised by H-1 and C-13 NMR techniques. Thorough analysis of NMR spectra confirmed that the main contribution comes from rotation about the partial double C-S bond. For the first time, a neat thiouronium ionic liquid system has been subjected to quantitative analysis of hindered rotamerism by dynamic NMR coalescence studies, with estimated activation energy for rotation of 63.9 +/- 0.4 kJ mol(-1). Finally, the application of (S)-[C(n)petu] Y salts as chiral discriminating agents for carboxylates by 1H NMR spectroscopy was further investigated, demonstrating the influence of the S-alkyl chain length on chiral recognition; (S)-[C(2)petu][NTf2] ionic liquid with the mandelate anion gave the best results.

Improvement in clinical step and shoot intensity modulated radiation therapy delivery accuracy on an integrated linear accelerator control system

Purpose: The dose delivery accuracy of 30 clinical step and shoot intensity modulated radiation therapy plans was investigated using the single integrated multileaf collimator controller of the Varian Truebeam linear accelerator (linac) (Varian Medical Systems, Palo Alto, CA) and compared with the dose delivery accuracy on a previous generation Varian 2100CD C-Series linac.

Methods and Materials: Ten prostate, 10 prostate and pelvic node, and 10 head-and-neck cases were investigated in this study. Dose delivery accuracy on each linac was assessed using Farmer ionization chamber point dose measurements, 2-dimensional planar ionization chamber array measurements, and the corresponding Varian dynamic log files. Absolute point dose measurements, fluence delivery accuracy, leaf position accuracy, and the overshoot effect were assessed for each plan.

Results: Absolute point dose delivery accuracy increased by 1.5% on the Truebeam compared with the 2100CD linac. No improvement in fluence delivery accuracy between the linacs, at a gamma criterion of 3%/3 mm was measured using the 2-dimensional ionization chamber array, with median (interquartile range) gamma passing rates of 98.99% (97.70%-99.72%) and 99.28% (98.26%-99.75%) for the Truebeam and 2100CD linacs, respectively. Varian log files also showed no improvement in fluence delivery between the linacs at 3%/3 mm, with median gamma passing rates of 99.97% (99.93%-99.99%) and 99.98% (99.94%-100%) for the Truebeam and 2100CD linacs, respectively. However, log files revealed improved leaf position accuracy and fluence delivery at 1%/1 mm criterion on the Truebeam (99.87%; 99.78%-99.94%) compared with the 2100CD linac (97.87%; 91.93%-99.49%). The overshoot effect, characterized on the 2100CD linac, was not observed on the Truebeam.

Conclusions: The integrated multileaf collimator controller on the Varian Truebeam improves clinical treatment delivery accuracy of step and shoot intensity modulated radiation therapy fields compared with delivery on a Varian C-series linac. © 2014.

A drive-by inspection system via vehicle moving force identification

This paper presents a novel method to carry out monitoring of transport infrastructure such as pavements and bridges through the analysis of vehicle accelerations. An algorithm is developed for the identification of dynamic vehicle-bridge interaction forces using the vehicle response. Moving force identification theory is applied to a vehicle model in order to identify these dynamic forces between the vehicle and the road and/or bridge. A coupled half-car vehicle-bridge interaction model is used in theoretical simulations to test the effectiveness of the approach in identifying the forces. The potential of the method to identify the global bending stiffness of the bridge and to predict the pavement roughness is presented. The method is tested for a range of bridge spans using theoretical simulations and the influences of road roughness and signal noise on the accuracy of the results are investigated.

Weaving behavior into feature models for embedded system families

Product Line software Engineering depends on capturing the commonality and variability within a family of products, typically using feature modeling, and using this information to evolve a generic reference architecture for the family. For embedded systems, possible variability in hardware and operating system platforms is an added complication. The design process can be facilitated by first exploring the behavior associated with features. In this paper we outline a bidirectional feature modeling scheme that supports the capture of commonality and variability in the platform environment as well as within the required software. Additionally, 'behavior' associated with features can be included in the overall model. This is achieved by integrating the UCM path notation in a way that exploits UCM's static and dynamic stubs to capture behavioral variability and link it to the feature model structure. The resulting model is a richer source of information to support the architecture development process.

Dynamic identification of building structures: new strategies:Meccanica dei materiali e delle strutture

In this paper the evolution of a time domain dynamic identification technique based on a statistical moment approach is presented. This technique can be used in the case of structures under base random excitations in the linear state and in the non linear one. By applying Itoˆ stochastic calculus, special algebraic equations can be obtained depending on the statistical moments of the response of the system to be identified. Such equations can be used for the dynamic identification of the mechanical parameters and of the input. The above equations, differently from many techniques in the literature, show the possibility of obtaining the identification of the dissipation characteristics independently from the input. Through the paper the first formulation of this technique, applicable to non linear systems, based on the use of a restricted class of the potential models, is presented. Further a second formulation of the technique in object, applicable to each kind of linear systems and based on the use of a class of linear models, characterized by a mass proportional damping matrix, is described.

Microbiology of sugar-rich environments: Diversity, ecology and system constraints

Microbial habitats that contain an excess of carbohydrate in the form of sugar are widespread in the microbial biosphere. Depending on the type of sugar, prevailing water activity and other substances present, sugar-rich environments can be highly dynamic or relatively stable, osmotically stressful, and/or destabilizing for macromolecular systems, and can thereby strongly impact the microbial ecology. Here, we review the microbiology of different high-sugar habitats, including their microbial diversity and physicochemical parameters, which act to impact microbial community assembly and constrain the ecosystem. Saturated sugar beet juice and floral nectar are used as case studies to explore the differences between the microbial ecologies of low and higher water-activity habitats respectively. Nectar is a paradigm of an open, dynamic and biodiverse habitat populated by many microbial taxa, often yeasts and bacteria such as, amongst many others, Metschnikowia spp. and Acinetobacter spp., respectively. By contrast, thick juice is a relatively stable, species-poor habitat and is typically dominated by a single, xerotolerant bacterium (Tetragenococcus halophilus). A number of high-sugar habitats contain chaotropic solutes (e.g. ethyl acetate, phenols, ethanol, fructose and glycerol) and hydrophobic stressors (e.g. ethyl octanoate, hexane, octanol and isoamyl acetate), all of which can induce chaotropicity-mediated stresses that inhibit or prevent multiplication of microbes. Additionally, temperature, pH, nutrition, microbial dispersion and habitat history can determine or constrain the microbiology of high-sugar milieux. Findings are discussed in relation to a number of unanswered scientific questions.

Compiler and Runtime Support for Hybrid Static/Dynamic Scheduling

One of the outstanding issues in parallel computing is the selection of task granularity. This work proposes a solution to the task granularity problem by lowering the overhead of the task scheduler and as such supporting very fine-grain tasks. Using a combination of static (compile-time) scheduling and dynamic (run-time) scheduling, we aim to make scheduling decisions as fast as with static scheduling while retaining the dynamic load- balancing properties of fully dynamic scheduling. We present an example application and discuss the requirements on the compiler and runtime system to realize hybrid static/dynamic scheduling.

Blind Characterisation of Sensors with Second-Order Dynamic Response

Compensation for the dynamic response of a temperature sensor usually involves the estimation of its input on the basis of the measured output and model parameters. In the case of temperature measurement, the sensor dynamic response is strongly dependent on the measurement environment and fluid velocity. Estimation of time-varying sensor model parameters therefore requires continuous textit{in situ} identification. This can be achieved by employing two sensors with different dynamic properties, and exploiting structural redundancy to deduce the sensor models from the resulting data streams. Most existing approaches to this problem assume first-order sensor dynamics. In practice, however second-order models are more reflective of the dynamics of real temperature sensors, particularly when they are encased in a protective sheath. As such, this paper presents a novel difference equation approach to solving the blind identification problem for sensors with second-order models. The approach is based on estimating an auxiliary ARX model whose parameters are related to the desired sensor model parameters through a set of coupled non-linear algebraic equations. The ARX model can be estimated using conventional system identification techniques and the non-linear equations can be solved analytically to yield estimates of the sensor models. Simulation results are presented to demonstrate the efficiency of the proposed approach under various input and parameter conditions.

Non-convex dynamic economic/environmental dispatch with plug-in electric vehicle loads

Electric vehicles are a key prospect for future transportation. A large penetration of electric vehicles has the potential to reduce the global fossil fuel consumption and hence the greenhouse gas emissions and air pollution. However, the additional stochastic loads imposed by plug-in electric vehicles will possibly introduce significant changes to existing load profiles. In his paper, electric vehicles loads are integrated into an 5-unit system using a non-convex dynamic dispatch model. The actual infrastructure characteristics including valve-point effects, load balance constrains and transmission loss have been included in the model. Multiple load profiles are comparatively studied and compared in terms of economic and environmental impacts in order o identify patterns to charge properly. The study as expected shows ha off-peak charging is the best scenario with respect to using less fuels and producing less emissions.

A self-learning teaching-learning based optimization for dynamic economic/environmental dispatch considering multiple plug-in electric vehicle loads

Economic and environmental load dispatch aims to determine the amount of electricity generated from power plants to meet load demand while minimizing fossil fuel costs and air pollution emissions subject to operational and licensing requirements. These two scheduling problems are commonly formulated with non-smooth cost functions respectively considering various effects and constraints, such as the valve point effect, power balance and ramp rate limits. The expected increase in plug-in electric vehicles is likely to see a significant impact on the power system due to high charging power consumption and significant uncertainty in charging times. In this paper, multiple electric vehicle charging profiles are comparatively integrated into a 24-hour load demand in an economic and environment dispatch model. Self-learning teaching-learning based optimization (TLBO) is employed to solve the non-convex non-linear dispatch problems. Numerical results on well-known benchmark functions, as well as test systems with different scales of generation units show the significance of the new scheduling method.