Bandwidth Estimation Research Articles

Application of fast singular spectrum decomposition method based on order statistic filter in rolling bearing fault diagnosis

Singular spectrum decomposition (SSD) is a new adaptive signal processing method for nonlinear and non-stationary signals. By constructing a trajectory matrix and adaptively selecting the embedding dimensions, the method divides non-stationary signals into several single-component signals successively from high frequency to low frequency. However, in the process of component reconstruction, bandwidth estimation and determining sizable trends by building a Gaussian function superposition spectral model are extremely complicated. Moreover, the parameter setting requires too much manual intervention and lacks theoretical support. Hence, aimed at nonlinear and non-stationary vibration signals of rolling bearings, a novel method of fault feature extraction based on the order statistic filter (OSF) for fast SSD (FSSD) is proposed. The FSSD method adopts the envelope method of OSFs to divide the spectrum and determine the sizable trend to improve the process. The proposed method is applied to bearing fault diagnosis. The analysis results of simulation signals and bearing experimental signals show that the new method can decompose signals quickly, effectively and accurately, and the mode mixing and time-consuming problems are refined.

Impact of Modern Virtualization Methods on Timing Precision and Performance of High-Speed Applications

The presented work is a result of extended research and analysis on timing methods precision, their efficiency in different virtual environments and the impact of timing precision on the performance of high-speed networks applications. We investigated how timer hardware is shared among heavily CPU- and I/O-bound tasks on a virtualized OS as well as on bare OS. By replacing the invoked timing methods within a well-known application for estimation of available path bandwidth, we provide the analysis of their impact on estimation accuracy. We show that timer overhead and precision are crucial for high-performance network applications, and low-precision timing methods usage, e.g., the delays and overheads issued by virtualization result in the degradation of the virtual environment. Furthermore, in this paper, we provide confirmation that, by using the methods we intentionally developed for both precise timing operations and AvB estimation, it is possible to overcome the inefficiency of standard time-related operations and overhead that comes with the virtualization. The impacts of negative virtualization factors were investigated in five different environments to define the most optimal virtual environment for high-speed network applications.

On the truncation of time frequency distributions to improve the computational performance in the estimation of fundamental parameters of a Doppler ultrasound blood flow signal

Accurate estimation of mean velocity and bandwidth of a Doppler Ultrasound blood flow signal, is essential to evaluate the success of a coronary artery graft surgery. The estimation accuracy and efficiency obtained depends on the spectral method used and some fundamental parameters such as frequency resolution and window length. However, some suitable methods are very complex and as a consequence computationally very intensive which could not be appropriate for real-time applications. This paper presents a series of studies using time frequency distributions to estimate mean frequency and RMS bandwidth, introducing a truncation index in the context of measuring blood flow in arteries. Results show that truncating a number of terms in the generalized auto-correlation function would introduce errors that, if carefully chosen, will not be significant. Furthermore, besides the reduction on calculating an important number of terms, the method offers the alternative of increasing the spectral resolution at no extra computational cost, both important elements to be considered in real-time applications.

Feature identification using acoustic signature of Ocean Researcher III (ORIII) of Taiwan

Feature identification using acoustic signature of Ocean Researcher III (ORIII) of Taiwan

QoS Routing Based on Available Bandwidth for Mobile Ad hoc Network

Mobile Ad-hoc network is a self configuring wireless network. It does not have any fixed infrastructure. Mobile node can leave and join the network. Therefore network topology changes any time. In Manet hosts can work as a router and forwards data from initiator to receiver. Since wireless channel is shared and topology is dynamic, providing quality of service (QoS) is a challenging task. QoS routing can find optimal routes that supports QoS requirement based on the received information during route discovery process. If QoS requirement cannot be supported, the admission control mechanism reject incoming request. Bandwidth estimation is a technique to determine available data rate on a route in the network. The term bandwidth means data rate not the physical bandwidth in hertz. QoS routing is required because most of the real time applications depend on the network’s condition. QoS in terms of bandwidth ensures transmission of real time data. In this paper a new bandwidth estimation method EAB (enhanced available bandwidth) is proposed. The performance of EAB-AODV is compared with AODV. The performance of EAB-AODV is better than AODV in terms of bandwidth.

RAACM: Resource Allocation for Admission Control in MANET

As wireless mobile network becomes widespread, the demand for user application is higher and the services provided by the wired application is expected to be available in the wireless medium. Therefore, the users of these applications will expect the same quality of service (QoS) obtained in wired network. Providing a reliable QoS in wireless medium, especially mobile ad-hoc network (MANET), is quite challenging and remains an ongoing research trend. The key issue of MANET lies around the ability to accurately predict the needed and available resources to avoid interference with ongoing traffic. An essential solution to the issues posed by MANET is the introduction of an admission control component for a guaranteed QoS. Admission control helps to control the usage of resources when an additional service is requested. For an admission decision to be made for a new flow, the expected bandwidth consumption must be correctly predicted prior to admission, notwithstanding the fact that wireless medium is shared and nodes contends among themselves to access the medium. The novelty of this research work is the proposed resource allocation for admission control in MANET (RAACM) solution which is an admission control scheme that estimates the available bandwidth needed within a network using a robust and accurate resource estimation technique. Furthermore, the various factors that must be considered for an effective estimation were highlighted and simulations were carried out. Results obtained show that our proposed scheme for MANET outperforms existing state-of-the-art approaches for admission control with bandwidth estimation. Part of this success is associated with its assumption about the idle channel period, which prevents the overestimation and underestimation of the existing bandwidth measurement. RAACM considers the dependency of two adjacent node idle channel occupancy by differentiating the networks BUSY state from the SENSE BUSY state and the IDLE state caused by an empty queue to give a better estimation.

Available Bandwidth Estimation for Adaptive Video Streaming in Mobile Ad Hoc

We propose in this paper an algorithm for available bandwidth estimation in mobile ad hoc networks and its integration into a conventional routing protocol like AODV for improving the rate-adaptive video streaming. We have introduced in our approach a local estimation of the available bandwidth as well as a prediction of the consumed bandwidth. This information allows video application to adjust its transmission rate avoiding network congestion. We conducted a performance evaluation of our solution through simulation experiments using two network scenarios. In the simulation study, transmission of video streams encoded with the H.264/MPEG-4 advanced video coding standard was evaluated. The results reveal performance improvements in terms of packet loss, delay and PSNR.

Energy-efficient optimal task offloading in cloud networked multi-robot systems

Task offloading plays a critical role in cloud networked multi-robot systems for leveraging computation support from cloud infrastructure and benefiting greatly from the well-developed cloud network facilities. However, considering the delay constraint, the extra costs of data transmission and remote computation, it is not trivial to make optimized offloading decisions. In particular, task offloading for robots is more complex due to their on-demand mobility and network connectivity that significantly influence the robot–cloud communication links. Moreover, for multi-robot systems, a suitable balance of workload between local network (robot–robot) and global cloud (robot–cloud) is also required, so as to attain proper utilization of resources. Therefore, it is essential to establish more comprehensive offloading schemes for modeling systems that can handle these higher level of complications. With that view, this paper aims to develop a novel multi-layer decision-making scheme for task offloading which jointly considers the following four aspects: (i) selection of task for offloading, (ii) selection of robot to offload a task, (iii) selection of location to offload/perform task, (iv) selection of access point for offloaded task. An integrated framework for cloud networked multi-robot systems is presented to enable our task offloading scheme where the primary robot can aid from additional local robots to improve the offloading process. In particular, we consider a warehouse scenario with 36 cell workspace where a 40 node taskflow is motivated from a “parcel sorting and distribution” application, to be completed by the primary robot. The offloading decision for each task is formulated as part of a joint optimization problem and it is solved by developing a multi-layer genetic algorithm scheme that takes into account motion, network connectivity and local sharing for its offloading decisions. We evaluate the results of the scheme via comparison with two validated benchmarks. The outcome highlights a significant improvement in overall system performance due to joint involvement of motion (path planning), connectivity (bandwidth estimation) and robot–robot communication (local offloading) that facilitates energy-efficient offloading to cloud, faster completion of tasks and better utilization of available resources.

Machine learning for measurement-based bandwidth estimation

The dispersion that arises when packets traverse a network carries information that can reveal relevant network characteristics. Using a fluid-flow model of a bottleneck link with first-in first-out multiplexing, accepted probing tools measure the packet dispersion to estimate the available bandwidth, i.e., the residual capacity that is left over by other traffic. Difficulties arise, however, if the dispersion is distorted compared to the model, e.g., by non-fluid traffic, multiple bottlenecks, clustering of packets due to interrupt coalescing, and inaccurate time-stamping in general. It is recognized that modeling these effects is cumbersome if not intractable. This motivates us to explore the use of machine learning in bandwidth estimation. We train a neural network using vectors of the packet dispersion that is characteristic of the available bandwidth. Our testing results reveal that even a shallow neural network identifies the available bandwidth with high precision. We also apply the neural network under a variety of notoriously difficult conditions that have not been included in the training, such as randomly generated networks with the multiple bottleneck links and heavy cross traffic burstiness. Compared to two state-of-the-art model-based techniques as well as a recent machine learning-based technique (Yin et al., 2016), our neural network approach shows improved performance. Further, our neural network can effectively control the estimation procedure in an iterative implementation. We also evaluate our method with other supervised machine learning techniques.

Efficient Bandwidth Estimation in 2D Filtered Backprojection Reconstruction.

A generalized cross-validation approach to estimate the reconstruction filter bandwidth in 2D filtered backprojection is presented. The method writes the reconstruction equation in equivalent backprojected filtering form, derives results on eigendecomposition of symmetric 2D circulant matrices, and applies them to make bandwidth estimation a computationally efficient operation within the context of standard backprojected filtering reconstruction. Performance evaluations on a range of simulated emission tomography experiments give promising results. The superior performance holds at both low and high total expected counts, pointing to the method's applicability even in weak signal-to-noise-ratio situations. The approach also applies to the more general class of elliptically symmetric filters, with the reconstructed estimate's performance often better than even that obtained with the true optimal radially symmetric filter.

Measuring bandwidth and buffer occupancy to improve the QoE of HTTP adaptive streaming

Live and on-demand video streaming service systems consume significant portion of Internet traffic all over the world. HTTP adaptive streaming is becoming the de-facto standard for adaptive video streaming solutions. Conventional estimation scheme for bandwidth estimation is not appropriate to estimate the bandwidth when multiple clients compete for a common bottleneck link, due to the ON–OFF traffic pattern. They overestimate the network bandwidth which leads to degradation of quality of experience by unnecessary changes in video quality, average video quality and unfairness of video quality. In this paper, we proposed receiver-side bandwidth-measured method to achieve a better quality of experience in multiple-client scenario. The proposed method estimates the obtainable network bandwidth based on the buffer status and segment throughput. The video buffer model is associated with three thresholds (i.e., one for initial start-up and two for operating thresholds). NS-3 network simulator has been deployed to measure the performance of HTTP adaptive streaming. Simulation outputs reflect that the proposed method enhances the quality of experience than conventional methods.

Special Issue on Recent Trends and Future of Fog and Edge Computing, Services and Enabling Technologies

Special Issue on Recent Trends and Future of Fog and Edge Computing, Services and Enabling Technologies

Analytical Available Bandwidth Estimation in Wireless Ad-hoc Networks Considering Mobility in 3-Dimensional Space

Estimation of available bandwidth for ad hoc networks has always been open and active challenge for the researchers. A lot of literature is proposed in the last 20 years to evaluate the residual bandwidth. The main objective of the work being admission of new flow in the network with the constraint that any existing current transmission is not affected. One of the prime factors affecting the estimation process is the collision among packets. These collisions trigger the backoff algorithm that leads to wastage of the usable bandwidth. Although a lot of state of art solutions were proposed, but they suffer from various flaws and shortcoming. Other factor contributing to the inaccuracy in existing solution is the mobility of nodes. Node mobility leads to instability of links leading to data losses and delay which impact the bandwidth. The current paper proposes an analytical approach named Analytical Available Bandwidth Estimation Including Mobility (AABWM) to estimate ABW on a link. The major contributions of the proposed work are: i) it uses mathematical models based on renewal theory to calculate the collision probability of data packets which makes the process simple and accurate, ii) consideration of mobility under 3-D space to predict the link failure and provides an accurate admission control. Extensive simulations in NS-2 are carried out to compare the performance of the proposed model against the existing solutions.

Opportunistic Routing with Available Bandwidth Assurance for High Dynamic UAV Swarms

The reconstruction of routing schemes constitutes an important quality of service (QoS) support for UAV swarms to keep their applications and services stable and active. In this paper, we develop a forwarding distance and available bandwidth (AB) estimation based opportunistic routing (FD-ABOR) protocol for high dynamic UAV swarms. We first improve the AB estimation algorithm for multi-hop UAV ad hoc networks by taking full account of the disparity between the sending and receiving ability and reconsidering the bandwidth consumption induced by hidden nodes. Secondly, we propose the scheme that the sender broadcast the RTS frame piggybacked with available bandwidth information for route request. Based on available bandwidth and forwarding distance, neighbour node decides it to be the candidate forwarder and computes the forwarding priority, then competes with each other to forward data packets. The simulation results show that our method outperforms AODV and DSR in terms of throughput and packet delivery ratio.

High frame rate doppler ultrasound bandwidth imaging for flow instability mapping.

PurposeFlow instability has been shown to contribute to the risk of future cardiovascular and cerebrovascular events. Nonetheless, it is challenging to noninvasively detect and identify flow instability in blood vessels. Here, we present a new framework called Doppler ultrasound bandwidth imaging (DUBI) that uses high‐frame‐rate ultrasound and Doppler bandwidth analysis principles to assess flow instability within an image view.MethodsDoppler ultrasound bandwidth imaging seeks to estimate the instantaneous Doppler bandwidth based on autoregressive modeling at every pixel position of data frames acquired from high‐frame‐rate plane wave pulsing. This new framework is founded upon the principle that flow instability naturally gives rise to a wide range of flow velocities over a sample volume, and such velocity range in turn yields a larger Doppler bandwidth estimate. The ability for DUBI to map unstable flow was first tested over a range of fluid flow conditions (ranging from laminar to turbulent) with a nozzle‐flow phantom. As a further demonstration, DUBI was applied to assess flow instability in healthy and stenosed carotid bifurcation phantoms.ResultsNozzle‐flow phantom results showed that DUBI can effectively detect and visualize the difference in Doppler bandwidth magnitude (increased from 2.1 to 5.2 kHz) at stable and unstable flow regions in an image view. Receiver operating characteristic analysis also showed that DUBI can achieve optimal sensitivity and specificity of 0.72 and 0.83, respectively. In the carotid phantom experiments, differences were observed in the spatiotemporal dynamics of Doppler bandwidth over a cardiac cycle. Specifically, as the degree of stenosis increased (from 50% to 75%), DUBI showed an increase in Doppler bandwidth magnitude from 1.4 kHz in the healthy bifurcation to 7.7 kHz at the jet tail located downstream from a 75% stenosis site, thereby indicating flow perturbation in the stenosed bifurcations.Conclusion DUBI can detect unstable flow. This new technique can provide useful hemodynamic information that may aid clinical diagnosis of atherosclerosis.

Characterization of machine tools and measurement system for micromilling

Technological progress has led to increased demand for small components with tiny features, which cannot be achieved through conventional machining. Industrial application of processes based on microcutting is limited by some issues concerning the geometrical scale. The process performance is significantly affected by milling machine, tool holder, tool, workpiece material microstructure, workpiece fixtures, and process parameters. At present, an ultimate micromachining assessment procedure is not available. This study aims to propose and conduct an experiment on a testing procedure for micromilling. The set up to be implemented and the output to be considered are defined and described. Three major stages are identified: estimation of the effective bandwidth of the load cell–tool holder system, the milling machine natural frequency measurement, and micromilling test execution. The entire procedure is performed, and its robustness is demonstrated.

A −40‐dB EVM 20‐MHz subsampling multistandard receiver architecture with dynamic carrier detection, bandwidth estimation, and EVM optimization

SummaryIn this work, a reconfigurable multistandard subsampling receiver with dynamic carrier frequency detection and system‐level EVM optimizations is proposed. Ideal software defined radio (SDR) receivers promise complete flexibility at the expense of high‐performance analog‐to‐digital converters (ADCs) that are challenging to implement in current technologies for low‐power applications. This scenario leads to the research of digital intensive sampling receivers with discrete‐time signal processing (DTSP) implemented in analog domain. This approach makes it feasible to move channel selection filtering and dynamic gain adaptability from analog to digital domain. The proposed receiver employs subsampling down‐conversion along with subband filters to dynamically detect the carrier frequency of the incoming signal, estimate its bandwidth, and identify if the signal is present in one of the target standard bands. This carrier detection provides a unique capability to reconfigure the receiver dynamically. Additionally, in this work, system‐level EVM optimization is proposed considering frequency synthesizer phase noise, IQ mismatch, sampling frequency selection and block‐level gain, noise, and nonlinearity. The RF front end of the proposed receiver is modeled in Verilog‐AMS whereas the digital signal processing is implemented in Simulink‐Matlab. The complete receiver has been verified to detect and process three different bands belonging to three different standards (GSM, UMTS, and WLAN) with the carrier frequency ranging from 0.9 to 2.5 GHz. Test signals with 4‐QAM modulation, maximum bandwidth of 20 MHz, and input‐dynamic range from –109 to –20 dBm is utilized to demonstrate the receiver performance including an EVM of –40 dB.

XMAS: An Efficient Mobile Adaptive Streaming Scheme Based on Traffic Shaping

Adaptive video streaming can provide adequate Quality of Experience by dynamically adjusting video rates in responding to fluctuating service conditions. However, adaptive video streaming shows dismal performances in wireless networks where several players share a wireless bottleneck link. This paper proposes a novel video rate selection scheme called XMAS for efficient video streaming in wireless networks. XMAS consists of two components: an available bandwidth estimation part and a video rate selection part. To redress the problem of inaccurate bandwidth estimation due to peculiar on-off transmission patterns of mobile video streaming, we devised a novel client-based traffic shaping scheme that effectively throttles server's packet transmission. Equipped with accurate bandwidth estimates, XMAS determines target transmission rates considering playback buffer levels. We implemented XMAS on Linux and performed rigorous experiments to analyze its behavior and performance. Our performance results showed that XMAS achieves up to 20% increase in average video rates while reducing rebuffer rates significantly.

A mesh objective continuum damage model for quasi-brittle crack modelling and finite element implementation

In the framework of continuum damage mechanics, a computational model for quasi-brittle crack modelling is proposed. The proposed model has significant mesh-objectivity and accuracy advantages over existing methods for modeling quasi-brittle crack. These stem from the combination of the local crack tracking algorithm, the new calculation of crack bandwidth and the non-local treatment regarding strain field. Resorting to the implementation of local crack tracking algorithm, it is desirable that the spurious dependence of conventional continuum damage mechanics-based model on mesh bias can be effectively addressed. The new estimation of the real-time crack bandwidth can be not only depending on the element size and pattern, but also on the physical crack path within each consolidate cracked element. Thus, the energy dissipation during crack propagation can be characterized in a more accurate, physically based manner. The non-local averaging regarding the strain field in the course of failure evolution is carried out within an elliptical domain, the configuration of which is related to finite element and crack trajectory obtained by the local crack track algorithm. With this combined technique, it is expected that a more accurate crack evolution course can be achieved numerically, which allows engineers to adopt relatively coarse unstructured discretizations without sacrificing solution accuracy. By numerical examples, the proposed model, empowered by the combined techniques, demonstrates significant improvements in the prediction of crack propagating of quasi-brittle materials. This model may provide engineers a more reliable tool in practical application of computational material failure.

A Three-Stage Progressive Transmission Scheme for Virtual Environments Over Lossy Networks

The rapid development of Virtual Environments (VEs) gives rise to its prominent performance in a myriad of multimedia applications. Accompanied by this is the increasingly massive data used for ascending user's visual experience. Recently, 3D streaming makes it viable to put VEs into real-time use through progressive transmission. Nonetheless, downloading VEs over inevitable lossy networks still remains a major bottleneck that urgently needs to be solved. In this paper, we propose a three-stage progressive transmission scheme for VEs over lossy networks, which aims to minimize distortion even when encountering poor network condition. The first stage is the Pre-coding Stage that offers the most feasible transmission scheme for subsequent transmission, in this stage we combine the advanced interest management algorithm and our proposed scene distortion estimation algorithm to bring up a scene update strategy which takes the user's visual features, quality of the scene and bandwidth estimation into account, so as to determine the download priority comprehensively. In the following Transmitting Stage, we apply Transmission Control Protocol (TCP) to make sure that we convey the essential information. More importantly, we adopt expanding window fountain (EWF) codes to provide an unequal error protection (UEP) for data with different importance. Eventually in the third After-process Stage, we employ a geometry prediction algorithm for the scenario with packet loss. The final results of our experiments show that the three-stage scheme can offer preeminent visual experience especially when it comes to a relatively inferior network condition.