Local Bandwidth Research Articles

HCoP-B: A Hierarchical Care-of Prefix With BUT Scheme for Nested Mobile Networks

With current Internet Engineering Task Force (IETF) network mobility (NEMO) basic support (NBS) to manage mobility of a mobile network that moves as a whole, all communication to and from mobile network nodes (MNNs) inside the mobile network must go through multiple tunnels between upstream mobile routers and their home agents. This results in the nonoptimized route and increased packet delay between communication peers. Hence, numerous NEMO schemes such as reverse routing header (RRH), mobile IPv6 route optimization for NEMO (MIRON), and care-of prefix (CoP) have been proposed to solve it. Whenever the whole mobile network or its mobile subnet changes its points of network attachments, a large number of duplicate binding update messages are sent from the handoff mobile network to all connecting correspondent nodes on the Internet to establish a direct and optimized packet route between them, which raises the corresponding consumed Internet and local wireless network bandwidth and, in turn, increases the packet transmission delay. However, traditional NEMO schemes cannot solve this serious binding update storm problem. In this paper, we apply the hierarchical concept to the CoP scheme as the Hierarchical CoP (HCoP) scheme and then enhance the HCoP with a novel binding update tree (BUT) structure as the HCoP-B for efficient NEMO management of the nested mobile network. Compared with the traditional RRH, MIRON, and HCoP with intensive performance analyses and simulations, HCoP-B achieves the shortest handoff latency, the lowest number of duplicate binding update messages conveyed over the Internet, and the least amount of consumed Internet and local wireless network bandwidth for session initialization and route optimization of all connecting correspondent nodes at the expense of a small amount of extra binding caches in the BUT. We also discuss important issues about HCoP-B deployment, security, and mobility anchor point (MAP) location alternatives. Consequently, HCoP-B achieves the correspondent node (CN)'s route optimization and resolves the associated binding update storm problem simultaneously for the nested mobile network.

Performance enhancement of optical burst switched networks

Optical burst switching (OBS) is an optical switching paradigm which offers a good tradeoff between the traditional optical circuit switching (OCS) and optical packet switching (OPS) since it has the relatively easy implementation of the first and the efficient bandwidth utilization of the second. Hence, OBS is a promising technology for the next generation optical Internet. A buffer-less OBS network can be implemented using ordinary optical communication equipment without the need for either wavelength converters or optical memories. In an OBS network, burst-loss performance is a critical concern. In OBS, the data-burst transmission is delayed by an offset time (relative to its burst control packet (BCP), or header) and the burst follows its header without waiting for an acknowledgment for resource reservation. Thus, a burst may be lost at an intermediate node due to contention, which is generally resolved according to the local routing and bandwidth information. The routing table maintained in each OBS node is generally pre-computed and fixed to forward the data bursts. Such a static forwarding feature might have limited efficiency to resolve contentions. Moreover, a burst may be lost and the network may be congested when a network element (e.g., fiber link) fails. In this paper, an efficient integrated scheme based on dynamic routing and burst segmentation has been proposed to improve reliability of data transport and network load balancing in optical burst switched networks. Simulation results demonstrate that the proposed approach reduces effectively blocking probability and hence contention. Further, it provides end-to-end throughput performance also. Hence, it establishes an appropriate tradeoff between loss rate and end-to-end throughput.

Validity improvement of evolutionary topology optimization: procedure with element replaceable method

The aim of this paper is to enhance the validity of existing evolutionary topology optimization procedures. As this hard-killing scheme related to the element sensitivity values may lead to incorrect predictions of inefficient elements to be removed and the value of the objective function becomes sharply deteriorated during the iterations, a check position (CP) control is proposed to prevent the erroneous topology design generated by the rejection criteria of evolutionary methods. For this purpose, we introduce a sort of orthotropic cellular microstructure (OCM) element with moderate pseudodensity that acts as a compromising element between solid element and void OCM element. In this way, all inefficient elements removed previously are automatically replaced with the moderate OCM elements depending upon the deterioration of the objective function. Erroneously removed elements are then identified in the updated finite element model through a direct sensitivity computing of the moderate OCM elements and will be finally recovered by the bi-directional element replacement. Besides, detailed structures with checkerboard patterns are eliminated by controlling the local structural bandwidth with the so-called threshold method. Typical optimization examples of structural compliance and natural frequency that were difficult to tackle are solved by the proposed design procedure. Satisfactory numerical results are obtained.

Review of Data Management Mechanisms on Mobile DevicesÜberblick über Datenmanagementmechanismen auf mobilen Endgeräten

Abstract The design of data management for mobile applications is a non-trivial task. Even with today´s much more powerful devices, we must consider limited resources: size and persistence of the local data storage, limited bandwidth and reliability of connection for data transmissions to remote servers, and constraint energy consumption of the used algorithms. In this article we focus on client/server approaches. We classify existing techniques and support the designer of data management functionalities for mobile applications with a set of fundamental characteristics of replication, hoarding and caching solutions.

Strain localization band width evolution by electronic speckle pattern interferometry strain rate measurement

In this paper, electronic speckle pattern interferometry strain rate measurements are used to quantify the width of the strain localization band, which occurs when a sheet specimen is submitted to tension. It is shown that the width of this band decreases with increasing strain. Just before fracture, this measured width is about five times wider than the shear band and the initial sheet thickness.

Pan-Canadian Evaluation of Irreversible Compression Ratios (“Lossy” Compression) for Development of National Guidelines

New technological advancements including multislice CT scanners and functional MRI, have dramatically increased the size and number of digital images generated by medical imaging departments. Despite the fact that the cost of storage is dropping, the savings are largely surpassed by the increasing volume of data being generated. While local area network bandwidth within a hospital is adequate for timely access to imaging data, efficiently moving the data between institutions requires wide area network bandwidth, which has a limited availability at a national level. A solution to address those issues is the use of lossy compression as long as there is no loss of relevant information. The goal of this study was to determine levels at which lossy compression can be confidently used in diagnostic imaging applications. In order to provide a fair assessment of existing compression tools, we tested and compared the two most commonly adopted DISCOM compression algorithms: JPEG and JPEG-2000. We conducted an extensive pan-Canadian evaluation of lossy compression applied to seven anatomical areas and five modalities using two recognized techniques: objective methods or diagnostic accuracy and subjective assessment based on Just Noticeable Difference. By incorporating both diagnostic accuracy and subjective evaluation techniques, enabled us to define a range of compression for each modality and body part tested. The results of our study suggest that at low levels of compression, there was no significant difference between the performance of lossy JPEG and lossy JPEG 2000, and that they are both appropriate to use for reporting on medical images. At higher levels, lossy JPEG proved to be more effective than JPEG 2000 in some cases, mainly neuro CT. More evaluation is required to assess the effect of compression on thin slice CT. We provide a table of recommended compression ratios for each modality and anatomical area investigated, to be integrated in the Canadian Association of Radiologists standard for the use of lossy compression in medical imaging.

A new fault-management method using congestion-avoidance routing for optical burst-switched networks

Optical burst switching (OBS) has been proposed as a promising technique to support high-bandwidth, bursty data traffic in the next-generation optical Internet. This study investigates a new fault-management framework for an OBS network. In an OBS network, burst-loss performance is a critical concern. In OBS, the data-burst transmission is delayed by an offset time (relative to its burst control packet (BCP), or header), and the burst follows its header without waiting for an acknowledgment for resource reservation. Thus, a burst may be lost at an intermediate node due to contention, which is generally resolved according to the local routing and bandwidth information. The routing table maintained in each OBS node is generally pre-computed and fixed to forward the data bursts. Such a static forwarding feature might have limited efficiency to resolve contentions. Moreover, a burst may be lost and the network may be congested when a network element (e.g., fiber link) fails. Therefore, for reliable burst transport, we develop dynamic routing approaches for preplanned congestion avoidance. Our goal is to proactively avoid congestion during the route-computation process, and our approach employs wavelength-channel utilization, traffic distribution, and link-distance information in the proposed objective functions for routing. Two update mechanisms for maintaining a dynamic routing table are presented to accommodate bursty data traffic. Based on our routing mechanisms, we also propose a new congestion-avoidance-and-protection (CAP) approach, which employs a primary route and a group of backup routes for each node pair against failures and congestion. The performance of the proposed protection strategy using congestion-avoidance routing is demonstrated to be promising through illustrative numerical examples.

Guaranteeing hard real-time traffic with legitimately short deadlines with the timed token protocol

Synchronous bandwidth, defined as the maximum time a node is allowed to send its synchronous messages while holding the token, is a sensitive parameter for deadline guarantees of synchronous messages in any timed token network. In order to offer such guarantees, synchronous bandwidth has to be allocated carefully to each individual node. This paper studies the synchronous bandwidth allocated to those synchronous message streams whose deadlines are less than twice the Target Token Rotation Time (TTRT). A new approach for allocating synchronous bandwidth to such streams, which can be used with any previously published local synchronous bandwidth allocation (SBA) for guaranteeing a general synchronous message set with its minimum deadline ( D min) no less than 2 · TTRT, is proposed. The proposed scheme can be applied efficiently in practice to any general synchronous message set with D min > TTRT. Numerical examples are presented to demonstrate the enhanced performance of this new local scheme over any of the previously published local SBA schemes.

Dynamic Reuse Partitioning Within Cells Based on Local Channel and Arrival Rate Fluctuations

It is possible to improve the spectral efficiency of cellular systems by dynamically repartitioning the available bandwidth between different interfering and noninterfering subareas within and among sectors. Here, we investigate the problem of maximizing the expected system throughput in a two-sector area by dynamic bandwidth partitioning between two transmission modes: 1) reusing bandwidth in the low-interference area near either of the base stations and 2) using bandwidth for macrodiversity or single-base station transmission to avoid interference. Mode 2 is typically useful for giving users near the cell border higher bit rates. The suggested solution adapts the bandwidth partitioning to reflect local transmission capacities and bandwidth demands. Thus, it automatically decides on whether both transmission modes should be used and how much bandwidth should be used in each mode. The solution requires only limited knowledge of the future arrival rates and channel qualities and uses probability theory to find a robust bandwidth partitioning. Finally, we discuss access control and when to switch a user between the transmission modes to achieve high spectral efficiency and some minimum average quality of service.

A Bootstrap Local Bandwidth Selector for Additive Models

This article proposes a bootstrap local bandwidth selector for estimating nonparametric additive models. The selector is derived from a bootstrap approximation of the conditional mean squared error, based on a wild bootstrap resampling scheme applied to the estimated residuals. The selector is computed exactly (without involving Monte Carlo approximations) and in practice can be evaluated for many additive estimation methods, including backfitting (bivariate), marginal integration, and mixed methods. We study the consistency of the bootstrap approximation and also carry out an empirical simulation study to explore the performance of the proposed selector in comparison with others. The graphical tool SiZer Map enables us to make meaningful comparisons between local and global selectors.

Convergence de l'estimateur à noyau des k plus proches voisins en régression fonctionnelle non-paramétrique

This note focuses on the k nearest neighbor method when one regresses a real random variable on a functional random variable (i.e. valued in an infinite-dimensional space). More precisely, we consider a kernel estimator of the regression based on a local bandwidth using exactly the k nearest neighbors. Although it is frequently used in functional data analysis, this method has not given any theoretical result so far. The aim of this Note is to show the pointwise almost-complete convergence of the k nearest neighbor kernel estimator in nonparametric functional regression. To cite this article: F. Burba et al., C. R. Acad. Sci. Paris, Ser. I 346 (2008).

Rodeo: Sparse, greedy nonparametric regression

We present a greedy method for simultaneously performing local bandwidth selection and variable selection in nonparametric regression. The method starts with a local linear estimator with large bandwidths, and incrementally decreases the bandwidth of variables for which the gradient of the estimator with respect to bandwidth is large. The method¯called rodeo (regularization of derivative expectation operator)¯conducts a sequence of hypothesis tests to threshold derivatives, and is easy to implement. Under certain assumptions on the regression function and sampling density, it is shown that the rodeo applied to local linear smoothing avoids the curse of dimensionality, achieving near optimal minimax rates of convergence in the number of relevant variables, as if these variables were isolated in advance.

Local smoothing regression with functional data

Kernel estimates of a regression operator are investigated when the explanatory variable is of functional type. The bandwidths are locally chosen by a data-driven method based on the minimization of a functional version of a cross-validated criterion. A short asymptotic theoretical support is provided and the main body of this paper is devoted to various finite sample size applications. In particular, it is shown through some simulations, that a local bandwidth choice enables to capture some underlying heterogeneous structures in the functional dataset. As a consequence, the estimation of the relationship between a functional variable and a scalar response, and hence the prediction, can be significantly improved by using local smoothing parameter selection rather than global one. This is also confirmed from a chemometrical real functional dataset. These improvements are much more important than in standard finite dimensional setting.

Novel method for the efficient individualization of binaural audio signals

A novel coding technique suitable for the transmission of binaural audio signals with concurrent multiple sound sources is proposed in this paper. Existing algorithms typically suffer from audible artefacts, poor localization, or excessive bandwidth. Especially with conventional intrasource coding methods, bandwidth is dependent on the number of sources and becomes greater as the number of sources increases. The proposed binaural transformation (BX) encoder synthesizes binaural signals using generic HRTFs and transmits them to the decoder along with side information. The bandwidth of the side information is independent of the number of sources. Using locally stored HRTFs matching those of the listener, the decoder turns the generic binaural signals into personalized ones. We present two types of BX codec: type A and type B. Psychoacoustic experiments based on Recommendation ITU‐R BS.1116‐1 were used to compare signals processed by these codecs with the corresponding unprocessed signals. For a variety of source materials (speech, vocals, guitars, and percussion) we show that high mean opinion scores are achievable using the type A codec when its parameters are set appropriately.

A variable bandwidth selector in multivariate kernel density estimation

Based on a random sample of size n from an unknown d-dimensional density f, the problem of selecting the variable (or adaptive) bandwidth in kernel estimation of f is investigated. The common strategy is to express the variable bandwidth at each observation as the product of a local bandwidth factor and a global smoothing parameter. For selecting the local bandwidth factor a method based on cluster analysis is proposed. This method is direct and intuitively appealing. For selecting the global smoothing parameter a method that is an adaptation of the frequency domain approach of selecting the fixed bandwidth in Wu and Tsai [2004. Root n bandwidths selectors in multivariate kernel density estimation. Probab. Theory Related Fields 129, 537–558] is used. For d = 1 and 2, extensive simulation studies have been done to compare the performance of our selector with the selectors of Abramson [1982. On bandwidth variation in kernel estimates—a square root law. Ann. Statist. 10, 1217–1223] and Sain and Scott [1996. On locally adaptive density estimation. J. Amer. Statist. Assoc. 91, 1525–1534] and Sain [2002. Multivariate locally adaptive density estimation. Comput. Statist. Data Anal. 39, 165–186], and the excellent performance of our selector at practical sample sizes is clearly demonstrated.

Tree-assisted gossiping for overlay video distribution

Given its readily deployable nature and broad applications for digital entertainment, video streaming through overlay networks has received much attention recently. While a tree topology is often advocated due to its scalability, it suffers from discontinuous playback under highly dynamic network environments. For on-demand streaming, the asynchronicity among client requests further aggravates the problem. On the other hand, gossip protocols using random message dissemination, though robust, fail to meet the real-time constraints for streaming applications. In this paper, we propose TAG, a Tree-Assisted Gossip protocol that addresses the above issues. TAG adopts a tree structure with time indexing to accommodate asynchronous requests, and an efficient pull-based gossip algorithm to mitigate the impact of network dynamicity. It seamlessly integrates these two approaches and realizes their best features, namely, low delay with a regular tree topology, and robust delivery with smart switching among multiple paths, thus making effective use of the available bandwidth in the network. We evaluate the performance of TAG under various settings, and the results demonstrate that it is quite robust in the presence of local and global bandwidth fluctuations. As compared to pure tree-based overlay VOD system, it achieves much lower and stable segment missing rates, even under highly dynamic network conditions.

Asymptotic fluctuations of mutagrams

Abrupt changes in sequential data, known as change-points, can be detected by fitting differences of one-sided kernel estimators. The detection depends on both a bandwidth and a threshold, where we declare a change-point whenever the differences of the one-sided kernel estimators exceed the threshold. The joint behavior of the difference of one-sided kernel estimators and scale can be graphically represented in a mutagram [Müller, H.G., Wai, N., 2004. Change trees and mutagrams for the visualization of local changes in sequence data. J. Comput. Statist. Graph. 13, 571–585.]. Here we study the fluctuations of the mutagram values in dependency on different bandwidth choices, corresponding to scale. Study of these fluctuations is related to the SiZer approach of Chaudhuri and Marron [2000. Scale space view of curve estimation. Ann. Statist. 28, 408–428.]. We explore the asymptotic properties and convergence of a local bandwidth process for differences of one-sided kernel estimators. These processes are shown to be tight with a Gaussian limit process that represents the asymptotic fluctuations of mutagrams. These fluctuations are illustrated with a sequence of vertical ocean shear data.

Bandwidth Selection in Local Polynomial Regression Using Eigenvalues

SummaryLocal polynomial regression is commonly used for estimating regression functions. In practice, however, with rough functions or sparse data, a poor choice of bandwidth can lead to unstable estimates of the function or its derivatives. We derive a new expression for the leading term of the bias by using the eigenvalues of the weighted design matrix where the bias depends on the arrangement of the X-values in the bandwidth window. We then use this result to determine a local data-driven bandwidth selection method and to provide a diagnostic for poor bandwidths that are chosen by using other methods. We show that our data-driven bandwidth is asymptotically equivalent to the optimal local bandwidth and that it performs well for relatively small samples when compared with other methods. In addition, we provide simulation results for first-derivative estimation. We illustrate its performance with data from Mars Global Surveyor.

Properties of the plasma channel in liquid discharges inferred from cathode local temperature measurements

The properties of the plasma channel at the cathode surface in a liquid discharge have been studied by means of temperature measurements and heat transfer numerical analysis. The studied discharge (current: 5 A; duration: 100μs; gap: 10μm) is typical of electrical discharge machining (EDM) in the semifinishing operation. The temperature information is obtained from two independent experiments: (1) microthermocouples patterned on the cathode, close to the discharge have been used to record the temperature variation caused by a single discharge with a high local resolution and large bandwidth; (2) the geometry of the resolidified layer, which gives the maximum extension of the melting point temperature isotherm, has been measured. These temperature data have then been compared to numerical simulation using inverse calculations allowing the experimental determination of two fundamental quantities of the discharge cathode interaction: (1) the power fraction transferred from the discharge to the sample, which was found to be close to 10% and (2) the exponent n of the power law expansion of the plasma channel rplasma∝tn, which is n=0.2. The validity of the present analysis relies on the fact that the experimental temperature information is obtained for different values of the parameter rplasma∕t02, where t02 is the characteristic time of the experiment.

Local spatial modeling of white-tailed deer distribution

Complex spatial heterogeneity of ecological systems is difficult to capture and interpret using global models alone. For this reason, recent attention has been paid to local spatial modeling techniques. We used one local modeling approach, geographically weighted regression (GWR), to investigate the effects of local spatial heterogeneity on multivariate relationships of white-tailed deer distribution using land cover patch metrics and climate factors. The results of these analyses quantify differences in the contributions of model parameters to estimates of deer density over space. A GWR model with local kernel bandwidth was compared to a GWR model with global kernel bandwidth and an ordinary least-squares regression (OLS) model with the same parameters to evaluate their relative abilities in modeling deer distributions. The results indicated that the GWR models predicted deer density better than the traditional ordinary least-squares model and also provided useful information regarding local environmental processes affecting deer distribution. GWR model comparisons showed that the local kernel bandwidth GWR model was more realistic than the global kernel bandwidth GWR model, as the latter exaggerated local spatial variation. The parameter estimates and model statistics (e.g., model R 2) of the GWR models were mapped using geographic information systems (GIS) to illustrate local spatial variation in the regression relationship and to identify causes of large-scale model misspecifications and low estimation efficiencies.