1211146
Multi-hop probing asymptotics in available bandwidth estimation: stochastic analysis
This paper analyzes the asymptotic behavior of packet-train probing over a multi-hop network path P carrying arbitrarily routed bursty cross-traffic flows. We examine the statistical mean of the packet-train output dispersions and its relationship to the input dispersion. We call this relationship the response curve of path P. We show that the real response curve Z is tightly lower-bounded by its multi-hop fluid counterpart F, obtained when every cross-traffic flow on P is hypothetically replaced with a constant-rate fluid flow of the same average intensity and routing pattern. The real curve Z asymptotically approaches its fluid counterpart F as probing packet size or packet train length increases. Most existing measurement techniques are based upon the single-hop fluid curve S associated with the bottleneck link in P. We note that the curve S coincides with F in a certain large-dispersion input range, but falls below F in the remaining small-dispersion input ranges. As an implication of these findings, we show that bursty cross-traffic in multi-hop paths causes negative bias (asymptotic underestimation) to most existing techniques. This bias can be mitigated by reducing the deviation of Z from S using large packet size or long packet-trains. However, the bias is not completely removable for the techniques that use the portion of S that falls below F.
353647
On Estimating Tight-Link Bandwidth Characteristics over Multi-Hop Paths
In this paper, we explore multi-hop bandwidth estimation assuming arbitrary cross-traffic at each node and develop a new probing method called Envelope that can asymptotically estimate not only the available bandwidth but also the raw capacity of the tight link. Envelope is based on a multi-link recursive extension of unbiased single-hop estimators proposed in the past (e.g., [14]) and a variation of the packet-cartouche technique [6]. Through extensive simulations, we evaluate Envelope in various network settings and cross-traffic conditions and find that it can measure tight-link bandwidth characteristics with accuracy that significantly surpasses that of the existing methods. We also find that Envelope can measure non-tight links in certain path and cross-traffic configurations.
8305231
Packet-pair bandwidth estimation: stochastic analysis of a single congested node
We examine the problem of estimating the capacity of bottleneck links and available bandwidth of end-to-end paths under non-negligible cross-traffic conditions. We present a simple stochastic analysis of the problem in the context of a single congested node and derive several results that allow the construction of asymptotically-accurate bandwidth estimators. We first develop a generic queuing model of an Internet router and solve the estimation problem assuming renewal cross-traffic at the bottleneck link. Noticing that the renewal assumption on Internet flows is too strong, we investigate an alternative filtering solution that asymptotically converges to the desired values of the bottleneck capacity and available bandwidth under arbitrary (including non-stationary) cross-traffic. This is one of the first methods that simultaneously estimates both types of bandwidth and is provably accurate. We finish the paper by discussing the impossibility of a similar estimator for paths with two or more congested routers.
40113853
A Framework for Modelling Short, High-Dimensional Multivariate Time Series: Preliminary Results in Virus Gene Expression Data Analysis
Short, high-dimensional Multivariate Time Series (MTS) data are common in many fields such as medicine, finance and science, and any advance in modelling this kind of data would be beneficial. Nowhere is this more true than functional genomics where effective ways of analysing gene expression data are urgently needed. Progress in this area could help obtain a "global" view of biological processes, and ultimately lead to a great improvement in the quality of human life. We present a computational framework for modelling this type of data, and report preliminary experimental results of applying this framework to the analysis of gene expression data in the virology domain. The framework contains a threestep modelling strategy: correlation search, variable grouping, and short MTS modelling. Novel research is involved in each step which has been individually tested on different real-world datasets in engineering and medicine. This is the first attempt to integrate all these components into a coherent computational framework, and test the framework on a very challenging application area, which has produced promising results.
2304584
Directional histogram model for three-dimensional shape similarity
In this paper, we propose a novel shape representation we call directional histogram model (DHM). It captures the shape variation of an object and is invariant to scaling and rigid transforms. The DHM is computed by first extracting a directional distribution of thickness histogram signatures, which are translation invariant. We show how the extraction of the thickness histogram distribution can be accelerated using conventional graphics hardware. Orientation invariance is achieved by computing the spherical harmonic transform of this distribution. Extensive experiments show that the DHM is capable of high discrimination power and is robust to noise.
8133100
Geometry-assisted statistical modeling for face mosaicing
The modeling of facial appearance has many applications. This paper proposes an approach to generating a statistical face model based on video mosaicing. Unlike traditional video mosaicing, we use the geometry of a face to improve the mosaicing result. Given a face sequence, each frame is unwrapped onto certain portion of the surface of a sphere, as determined by spherical projection and the minimization procedure using the Levenberg-Marquardt algorithm. A statistical model containing a mean image and a number of eigenimages, instead of only one image template, is used to represent the face mosaic. Good experimental results have been observed.
3266821
A Least Biased Fuzzy Clustering Method
A new operational definition of cluster is proposed, and a fuzzy clustering algorithm with minimal biases is formulated by making use of the maximum entropy principle to maximize the entropy of the centroids with respect to the data points (clustering entropy). The authors make no assumptions on the number of clusters or their initial positions. For each value of an adimensional scale parameter /spl beta/', the clustering algorithm makes each data point iterate towards one of the cluster's centroids, so that both hard and fuzzy partitions are obtained. Since the clustering algorithm can make a multiscale analysis of the given data set one can obtain both hierarchy and partitioning type clustering. The relative stability with respect to /spl beta/' of each cluster structure is defined as the measurement of cluster validity. The authors determine the specific value of /spl beta/' which corresponds to the optimal positions of cluster centroids by minimizing the entropy of the data points with respect to the centroids (clustered entropy). Examples are given to show how this least biased method succeeds in getting perceptually correct clustering results. >
1984219
Incorporation of input glitches into power macromodeling
Previous research on power macromodeling has always assumed glitch-free input signals. However, in an actual operating environment, the input signals of a circuit can contain glitches, which are generated by the previous stage of circuitry. In this paper, we investigate the impact of input glitches on the power dissipation of a circuit. Specifically, we show that the frequency and average duration of input glitches are two important factors affecting the overall power consumption. Input glitches can also increase output glitching by a surprisingly large amount. We present a simple yet effective analytical power macromodeling approach incorporating the effects of input glitching. In experiments with ISCAS-85 benchmark circuits, the average error of the proposed technique is 4.44%.