Bandwidth Estimates Research Articles

Bandwidth Estimation From Multiple Level-Crossings of Stochastic Signals

Motivated by a broad range of potential applications in event-driven signal processing inference, we examine a class of spectral moments estimators derived from multiple level-crossings of a stationary Gaussian stochastic signal as well as non-Gaussian signals being monotone transformations of the Gaussian signal. The established spectral moments estimators are used to obtain estimates of the stochastic signal bandwidth. Both the mean-squared bandwidth and the absolute bandwidth are taken into account. Also the notion of the power bandwidth is introduced and its estimation is examined. We prove that the proposed estimates are consistent as the length of the observed time interval is increasing. The accuracy of the proposed bandwidth estimation methods from multiple level-crossings is assessed in simulation studies.

On the optimal estimation of probability measures in weak and strong topologies

Given random samples drawn i.i.d. from a probability measure $\mathbb{P}$ (defined on say, $\mathbb{R}^d$), it is well-known that the empirical estimator is an optimal estimator of $\mathbb{P}$ in weak topology but not even a consistent estimator of its density (if it exists) in the strong topology (induced by the total variation distance). On the other hand, various popular density estimators such as kernel and wavelet density estimators are optimal in the strong topology in the sense of achieving the minimax rate over all estimators for a Sobolev ball of densities. Recently, it has been shown in a series of papers by Gin\'{e} and Nickl that these density estimators on $\mathbb{R}$ that are optimal in strong topology are also optimal in $\|\cdot\|_{\mathcal{F}}$ for certain choices of $\mathcal{F}$ such that $\|\cdot\|_{\mathcal{F}}$ metrizes the weak topology, where $\|\mathbb{P}\|_{\mathcal{F}}:=\sup\{\int f\,\mathrm{d}\mathbb{P}: f\in\mathcal{F}\}$. In this paper, we investigate this problem of optimal estimation in weak and strong topologies by choosing $\mathcal{F}$ to be a unit ball in a reproducing kernel Hilbert space (say $\mathcal{F}_H$ defined over $\mathbb{R}^d$), where this choice is both of theoretical and computational interest. Under some mild conditions on the reproducing kernel, we show that $\|\cdot\|_{\mathcal{F}_H}$ metrizes the weak topology and the kernel density estimator (with $L^1$ optimal bandwidth) estimates $\mathbb{P}$ at dimension independent optimal rate of $n^{-1/2}$ in $\|\cdot\|_{\mathcal{F}_H}$ along with providing a uniform central limit theorem for the kernel density estimator.

IRate: Initial Video Bitrate Selection System for HTTP Streaming

Many HTTP streaming video systems have been developed and widely deployed in recent years. Previous efforts were mainly spent on improving the caching of videos or proposing mid-stream measurement methods to update the best bitrate. However, since the video length is often short, the mid-stream measurement may not even converge to the best bitrate due to insufficient bandwidth estimates. On the other hand, because of diversified Web infrastructure, estimating the actual network quality at the pre-stream stage is increasingly challenging for video service providers. In this paper, we propose IRate, which enables video service providers to proactively profile clients’ streaming performance by carrying out pre-stream measurement in the Content Delivery Network (CDN). With the measurement results, the video stream can start at the best video quality at the onset of streaming. This is especially beneficial to short video clips, which are very popular in the Internet today. IRate is composed of a probe kit and a quality oracle. The probe kit utilizes the pre-stream time window (e.g., user’s think time and pre-roll advertisement) for measuring network quality by running a lightweight measurement script on the Web page to induce probe packets from the IRate middlebox on the server side. With the measurement results, the quality oracle estimates the clients’ streaming performance by determining the highest initial bitrate with a pre-trained decision tree. Our testbed results show that IRate is able to achieve 80% accuracy in determining the bitrate within 10s. By having a better estimate of the best initial bitrate, the buffering time and rebuffering events are significantly reduced in HTTP streaming. Furthermore, the stability and the efficiency in dynamic adaptive streaming over HTTP streaming are also improved by about 40% and 36%, respectively. Our user quality of experience (QoE) experiment further validates that IRate can improve the QoE by more than 6% and the perceived quality of initial quality by 24% in the actual Internet environment.

TCP-Gvegas with prediction and adaptation in multi-hop ad hoc networks

TCP Vegas performance can be improved since its rate-based congestion control mechanism could proactively avoid possible congestion and packet losses in multi-hop ad hoc networks. Nevertheless, Vegas cannot make full advantage of available bandwidth to transmit packets since incorrect bandwidth estimates may occur due to frequent topology changes caused by node mobility. This paper proposes an improved TCP Vegas based on the grey prediction theory, named TCP-Gvegas, for multi-hop ad hoc networks, which has the capability of prediction and self-adaption, as well as three enhanced aspects in the phase of congestion avoidance. The lower layers' parameters are considered in the throughput model to improve the accuracy of theoretical throughput. The prediction of future throughput based on grey prediction is used to promote the online control. The optimal exploration method based on Q-Learning and Round Trip Time quantizer are applied to search for the more reasonable changing size of congestion window. Besides, the convergence analysis of grey prediction by using the Lyapunov's second method proves that a shorter input data length of prediction implies a faster convergence rate. The simulation results show that the TCP-Gvegas achieves a substantially higher throughput and lower delay than Vegas in multi-hop ad hoc networks.

Fourier-Based Feature Extraction for Classification of EEG Signals Using EEG Rhythms

In this paper, we propose a method for the analysis and classification of electroencephalogram (EEG) signals using EEG rhythms. The EEG rhythms capture the nonlinear complex dynamic behavior of the brain system and the nonstationary nature of the EEG signals. This method analyzes common frequency components in multichannel EEG recordings, using the filter bank signal processing. The mean frequency (MF) and RMS bandwidth of the signal are estimated by applying Fourier-transform-based filter bank processing on the EEG rhythms, which we refer intrinsic band functions, inherently present in the EEG signals. The MF and RMS bandwidth estimates, for the different classes (e.g., ictal and seizure-free, open eyes and closed eyes, inter-ictal and ictal, healthy volunteers and epileptic patients, inter-ictal epileptogenic and opposite to epileptogenic zone) of EEG recordings, are statistically different and hence used to distinguish and classify the two classes of signals using a least-squares support vector machine classifier. Experimental results, with 100 % classification accuracy, on a real-world EEG signals database analysis illustrate the effectiveness of the proposed method for EEG signal classification.

Cache'n DASH

HTTP-based video streaming services have been dominating the global IP traffic over the last few years. Caching of video content reduces the load on the content servers. In the case of Dynamic Adaptive Streaming over HTTP (DASH), for every video the server needs to host multiple representations of the same video file. These individual representations are further broken down into smaller segments. Hence, for each video the server needs to host thousands of segments out of which, the client downloads a subset of the segments. Also, depending on the network conditions, the adaptation scheme used at the client-end might request a different set of video segments (varying in bitrate) for the same video. The caching of DASH videos presents unique challenges. In order to optimize the cache hits and minimize the misses for DASH video streaming services we propose an Adaptation Aware Cache (AAC) framework to determine the segments that are to be prefetched and retained in the cache. In the current scheme, we use bandwidth estimates at the cache server and the knowledge of the rate adaptation scheme used by the client to estimate the next segment requests, thus improving the prefetching at the cache.

Relation between measures of psychoacoustic abilities and masking release for unprocessed, envelope, and temporal fine-structure speech in listeners with normal and impaired hearing

Léger et al. [J. Acoust. Soc. Am. 135, 2160, 2014] studied masking release in normal-hearing and hearing-impaired listeners using unprocessed speech and speech processed to convey envelope (ENV) or temporal fine-structure (TFS) cues. Consonant identification scores in speech-shaped background noise (continuous and square-wave interrupted at a rate of 10 Hz) indicated a substantial masking release (MR, better performance in the interrupted noise) for all speech types for normal-hearing listeners but only for the TFS speech in most hearing-impaired listeners. The current study was concerned with relating consonant identification scores and masking release to SRTs for sentences in both types of noise as well as to measurements of basic psychoacoustic abilities. These measures included absolute pure-tone detection thresholds, estimates of auditory bandwidth using a notched-noise procedure, and estimates of cochlear compression obtained using a forward-masking paradigm. For both unprocessed and ENV speech, intelligibility scores and MR were correlated with absolute thresholds and auditory bandwidths in the mid-frequency region (but not at a lower frequency). These correlations were less strong for TFS speech intelligibility and did not predict MR. Cochlear compression was not related to speech intelligibility when controlling for the effect of absolute thresholds. [Work supported by NIH R01 DC000117.]

Statistical properties of linear prediction analysis underlying the challenge of formant bandwidth estimation.

Formant bandwidth estimation is often observed to be more challenging than the estimation of formant center frequencies due to the presence of multiple glottal pulses within a period and short closed-phase durations. This study explores inherently different statistical properties between linear prediction (LP)-based estimates of formant frequencies and their corresponding bandwidths that may be explained in part by the statistical bounds on the variances of estimated LP coefficients. A theoretical analysis of the Cramér-Rao bounds on LP estimator variance indicates that the accuracy of bandwidth estimation is approximately twice as low as that of center frequency estimation. Monte Carlo simulations of all-pole vowels with stochastic and mixed-source excitation demonstrate that the distributions of estimated LP coefficients exhibit expectedly different variances for each coefficient. Transforming the LP coefficients to formant parameters results in variances of bandwidth estimates being typically larger than the variances of respective center frequency estimates, depending on vowel type and fundamental frequency. These results provide additional evidence underlying the challenge of formant bandwidth estimation due to inherent statistical properties of LP-based speech analysis.

Adaptive Multistreaming Over Network Via SCTP

The idea of this paper is related to the transmission of streaming media passed through a stream control transmission protocol (SCTP). This paper evaluates the performance of the SCTP with adaptive streams. This is done by adding new methods for setting the number of streams, that can be applied to an SCTP and that can utilize new, characteristic of SCTP features. A SCTP sender adaptively enables or disables multistreaming based on comparison between the estimates of available bandwidth and current congestion window size. It is desired to improve goodput under congestion. to evaluate the effect of communication through computer simulation using the INET framework for simulation tools OMNet++.This software will be setup under windows O.S, and finally will compare the variation between the proposed method and SCTP using normal streams.

Population receptive field estimates of human auditory cortex

Here we describe a method for measuring tonotopic maps and estimating bandwidth for voxels in human primary auditory cortex (PAC) using a modification of the population Receptive Field (pRF) model, developed for retinotopic mapping in visual cortex by Dumoulin and Wandell (2008). The pRF method reliably estimates tonotopic maps in the presence of acoustic scanner noise, and has two advantages over phase-encoding techniques. First, the stimulus design is flexible and need not be a frequency progression, thereby reducing biases due to habituation, expectation, and estimation artifacts, as well as reducing the effects of spatio-temporal BOLD nonlinearities. Second, the pRF method can provide estimates of bandwidth as a function of frequency. We find that bandwidth estimates are narrower for voxels within the PAC than in surrounding auditory responsive regions (non-PAC).

The Interreg IV Italia-Austria "SeismoSAT" project: connecting seismic data centers via satellite

Abstract. Since 2002 OGS (Istituto Nazionale di Oceanografia e di Geofisica Sperimentale) in Udine (Italy), the Zentralanstalt für Meteorologie und Geodynamik (ZAMG) in Vienna (Austria), and the Agencija Republike Slovenije za Okolje (ARSO) in Ljubljana (Slovenia) are using the Antelope software suite as the main tool for collecting, analyzing, archiving and exchanging seismic data in real time, initially in the framework of the EU Interreg IIIA project "Trans-national seismological networks in the South-Eastern Alps" (Bragato et al., 2004, 2010). The data exchange has proved to be effective and very useful in case of seismic events near the borders between Italy, Austria and Slovenia, where the poor single national seismic networks coverage precluded a correct localization, while the usage of common data from the integrated networks improves considerably the overall reliability of real time seismic monitoring of the area (Fig. 1). At the moment the data exchange between the seismic data centers relies on their internet connections: this however is not an ideal condition for civil protection purposes, since the reliability of standard internet connections is poor. For this reason in 2012 the Protezione Civile della Provincia Autonoma di Bolzano in Bolzano (PCBZ, Italy), OGS, ZAMG subsidiary in Tirol (ZAMG Tirol) and ARSO joined in the Interreg IV Italia-Austria Project "SeismoSAT" (Progetto SeismoSAT, 2012) aimed in connecting the seismic data centers in real time via satellite. ARSO does not belong to the Interreg Italia-Austria region: for this reason ARSO joined the SeismoSAT project as an "associated partner", which, according to Interreg rules can not be funded. ARSO participation in the project is therefore at the beginning limited in benefiting only indirectly from improvement in the robustness of the data exchange between the other data centers, while eventually fully taking part in the project if other sources of funding will be available. The project is in a preliminary phase: the general schema of the project, including first data bandwidth estimates and a possible architecture are here illustrated.

Performance Study of an Admission Controller for Wireless Networks

Determining if there is enough bandwidth to allow admit a new flow into a wireless network is a complex task. To solve this problem, various methods have been proposed for estimating bandwidth. We study through simulations the performance of a new algorithm that has theoretical guarantees to correctly determine the available bandwidth without disturbing other flows that are currently being served. Specifically, we studied how the selection of the algorithm parameters affect its speed of convergence and accuracy of the estimates of available bandwidth. The results confirm the theoretical results and are used to determine the best parameters for rapid convergence with minimal estimation error.

Stochastic Bandwidth Estimation in Networks With Random Service

Numerous methods for available bandwidth estimation have been developed for wireline networks, and their effectiveness is well-documented. However, most methods fail to predict bandwidth availability reliably in a wireless setting. It is accepted that the increased variability of wireless channel conditions makes bandwidth estimation more difficult. However, a (satisfactory) explanation why these methods are failing is missing. This paper seeks to provide insights into the problem of bandwidth estimation in wireless networks or, more broadly, in networks with random service. We express bandwidth availability in terms of bounding functions with a defined violation probability. Exploiting properties of a stochastic min-plus linear system theory, the task of bandwidth estimation is formulated as inferring an unknown bounding function from measurements of probing traffic. We present derivations showing that simply using the expected value of the available bandwidth in networks with random service leads to a systematic overestimation of the traffic departures. Furthermore, we show that in a multihop setting with random service at each node, available bandwidth estimates requires observations over (in principle infinitely) long time periods. We propose a new estimation method for random service that is based on iterative constant-rate probes that take advantage of statistical methods. We show how our estimation method can be realized to achieve both good accuracy and confidence levels. We evaluate our method for wired single-and multihop networks, as well as for wireless networks.

BEST-AP: Non-intrusive estimation of available bandwidth and its application for dynamic access point selection

The coverage area of Access Points (APs) in Wireless Local Area Networks (WLANs) often overlaps considerably. Hence, a station can potentially associate with many APs. In traditional IEEE 802.11 systems, the station associates to the AP with the strongest signal. This strategy may result in load imbalance between APs and thus low overall network throughput. This paper proposes a new mechanism for selecting the “best” AP based on a novel available bandwidth estimation scheme. The available bandwidth provided by an AP depends mainly on the signal quality and the load on the wireless channel. Based on measurements we first analyze how those factors vary stochastically over time and motivate why a frequent estimation of available bandwidth is necessary. We then develop BEST-AP, a system for Bandwidth ESTimation of Access Points, which uses regular data traffic to estimate the available bandwidth from all APs in reach in a non-intrusive way, even if they are on a different channel. Based on OpenFlow, BEST-AP allows the station to be associated with multiple APs simultaneously and to switch between APs with low overhead. Using the available bandwidth estimates, the system exploits the “best” AP for longer duration while probing the less good APs for shorter durations to update the bandwidth estimations. The evaluation in a WLAN testbed shows that with background load created from real WLAN traces, the dynamic selection of APs improves the throughput of a station by around 81%, compared to a static selection. When the station is mobile, the throughput increases by 176% on average.

Inconsistent channel bandwidth estimates suggest winner-take-all nonlinearity in second-order vision

The processing of texture patterns has been characterized by a model that postulates a first-stage linear filter to highlight a component texture, a pointwise rectification stage to convert contrast for the highlighted texture into mean response strength, followed by a second-stage linear filter to detect the texture-defined pattern. We estimated the spatial-frequency bandwidth of the second-stage filter mediating orientation discrimination of orientation-modulated second-order gratings by measuring threshold elevation in the presence of filtered noise added to the modulation signal. This experiment yielded no evidence for frequency tuning. A second experiment, in which subjects had to detect similar second-order gratings while judging their modulation frequency, produced bandwidth estimates of 1–1.5 octaves, similar to estimated bandwidths of first-order channels. We propose that an additional dominant-response-selection nonlinearity can account for these apparently contradictory results.

Rapid measurement of auditory filter shape in mice using the auditory brainstem response and notched noise

The notched noise method is an effective procedure for measuring frequency resolution and auditory filter shapes in both human and animal models of hearing. Briefly, auditory filter shape and bandwidth estimates are derived from masked thresholds for tones presented in noise containing widening spectral notches. As the spectral notch widens, increasingly less of the noise falls within the auditory filter and the tone becomes more detectible until the notch width exceeds the filter bandwidth. Behavioral procedures have been used for the derivation of notched noise auditory filter shapes in mice; however, the time and effort needed to train and test animals on these tasks renders a constraint on the widespread application of this testing method. As an alternative procedure, we combined relatively non-invasive auditory brainstem response (ABR) measurements and the notched noise method to estimate auditory filters in normal-hearing mice at center frequencies of 8, 11.2, and 16 kHz. A complete set of simultaneous masked thresholds for a particular tone frequency were obtained in about an hour. ABR-derived filter bandwidths broadened with increasing frequency, consistent with previous studies. The ABR notched noise procedure provides a fast alternative to estimating frequency selectivity in mice that is well-suited to high through-put or time-sensitive screening.

Optimal and Heuristic Application-Aware Oblivious Routing

Conventional oblivious routing algorithms do not take into account resource requirements (e.g., bandwidth, latency) of various flows in a given application. As they are not aware of flow demands that are specific to the application, network resources can be poorly utilized and cause serious local congestion. Also, flows, or packets, may share virtual channels in an undetermined way; the effects of head-of-line blocking may result in throughput degradation. In this paper, we present a framework for application-aware routing that assures deadlock freedom under one or more virtual channels by forcing routes to conform to an acyclic channel dependence graph. In addition, we present methods to statically and efficiently allocate virtual channels to flows or packets, under oblivious routing, when there are two or more virtual channels per link. Using the application-aware routing framework, we develop and evaluate a bandwidth-sensitive oblivious routing scheme that statically determines routes considering an application's communication characteristics. Given bandwidth estimates for flows, we present a mixed integer-linear programming (MILP) approach and a heuristic approach for producing deadlock-free routes that minimize maximum channel load. Our framework can be used to produce application-aware routes that target the minimization of latency, number of flows through a link, bandwidth, or any combination thereof. Our results show that it is possible to achieve better performance than traditional deterministic and oblivious routing schemes on popular synthetic benchmarks using our bandwidth-sensitive approach. We also show that, when oblivious routing is used and there are more flows than virtual channels per link, the static assignment of virtual channels to flows can help mitigate the effects of head-of-line blocking, which may impede packets that are dynamically competing for virtual channels. We experimentally explore the performance tradeoffs of static and dynamic virtual channel allocation on bandwidth-sensitive and traditional oblivious routing methods.

Application of Log Periodic Dipole Antenna (LPDA) in Monitoring Solar Burst at Low Region Frequencies Region

The Sun is considered as one of the strongest radio sources and observation in radio region can provide information on structures throughout the solar atmosphere. In radio wavelengths, we could possible to investigate high quality images within an arc second resolution at different layers of the solar atmosphere. Solar monitoring in this wavelength makes various demands on the used antennas. Therefore, Logarithmic Periodic dipole Antenna (LPDA) was constructed for monitoring Sun in the range of (45−870) MHz to precisely match the environmental requirements. Our work focuses on preparation and performance of the antenna. Observation results of the site will also be highlighted. From the analysis, we found that the signal to noise ratio is 3.9 dB. We also make an effort analyze a y-factor of a data by select a range of frequency from 220 MHz till 250 MHz due to this range consists burst. By constructing and understanding the principle of the log dipole periodic antenna and then connect it to the CALLISTO spectrometer as receiver, some solar activities observations such as solar flares and Coronal Mass Ejections (CMEs) can be done. In conclusion, the log-periodic dipole antenna (LPDA) is remains the simplest antenna with reliable bandwidth and gain estimates. solar activities

Up, down and around the stack

Broadband characterization has recently attracted much attention from the research community and the general public. Given this interest and the important business and policy implications of residential Internet service characterization, recent years have brought a variety of approaches to profiling Internet services, ranging from Web-based platforms to dedicated infrastructure inside home networks. We have previously argued that network-intensive applications provide an almost ideal vantage point for broadband service characterization at sufficient scale, nearly continuously and from end users. While we have shown that the approach is indeed effective at characterization and can enable performance comparisons between service providers and geographic regions, a key unanswered question is how well the performance characteristics captured by these network-intensive applications can predict the overall user experience with other applications. In this paper, using BitTorrent as an example network-intensive application, we present initial results that demonstrate how to obtain estimates of bandwidth and latency of a network connection by leveraging passive monitoring and limited active measurements from network intensive applications. We then analyze user experienced web performance under a variety of network conditions and show how estimated metrics from this network intensive application can serve as good web performance predictors.

Real-time bandwidth measurements over mobile connections

The first study that investigates the characteristics of received probe packets and the reliability of bandwidth estimates when actively measuring the available bandwidth over radio interfaces in mobile communication networks is presented. Knowledge of available bandwidth is very useful in various contexts, e.g. in network management and adaptive streaming applications. Bandwidth measuring tools have so far primarily been designed for and evaluated in wired networks. However, such tools should also be examined in wireless networks since the use of, e.g., mobile broadband is rapidly increasing. The properties of wired and wireless links differ substantially, which affect the performance of the tools. We have made active-probing experiments over a high-speed downlink shared channel, which is used for High-Speed Downlink Packet Access (HSDPA) in the mobile communication technology UMTS, and over a forward traffic channel in CDMA2000 1xEV-DO. Both experiments were performed over commercial networks. They show that one cannot always expect uniform per-packet processing over the radio channel in mobile networks, which is expected by many probing tools. This reduces the reliability of the available-bandwidth estimates, however we suggest how this can be handled. Finally, the mobile-network measurements are compared to experiments performed in an IEEE 802.11 wireless LAN, where the radio channel does not create the same packet-processing behaviour. We also discuss the possibility of using the probe traffic for the purpose of identifying the communication technology at the bottleneck of the network path, assumed this is a wireless broadband link, by mapping specifications of standardised communication technologies to observed probe-traffic characteristics. Copyright © 2011 John Wiley & Sons, Ltd.