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Special issue on scalable web services and architecture
With the rapid growth of the Internet, web services are becoming an increasingly important class of driving applications for scalable computer systems. Due to the popularity of many Internet applications, the load on Internet servers (web servers, proxy/caching servers, firewalls, etc.) is rapidly increasing. The next generation of Web services should support a very high rate of requests with varying needs imposing a big challenge for the networking infrastructure and the server environments. Since the network bandwidth increases faster than the server capacity, the server could be the next bottleneck of Web services. The efficient execution of Web applications will need to employ parallelism into the Application layer, and overall, into the Web server: (1) Intra-server parallelism, i.e. parallel execution of the web server tasks (e.g. a task or a thread for each HTTP request); (2) Inter-server parallelism, i.e. concurrent execution of different web servers. Cluster computing, a cost-effective technique to connect many small-scale computers to build a large-scale parallel computer, is the first step to build more powerful, interconnected, high performance computing systems. In particular, clusterbased distributed servers are being deployed by more and more popular web sites for scalable and highly available services. Major areas of research and development today include: caching and dynamic content delivering of scalable web servers to security solutions of computational grid. Topic areas covered include, scalability of distributed servers; web server traffic characterization; scheduling and load balancing on distributed servers; distributed server monitoring, fault tolerance, and management; caching, data replication, and concurrency control; security mechanism and policies for distributed servers. This special issue contains seven papers that deal with many of those issues. The purpose was to report both theoretical and practical solutions to some of the problems, and to identify new areas of research. In the first paper, A New Consistency Algorithm for Dynamic Documents in Content Distribution Networks, Fei develops a new strategy to maintain data consistency and integrity of dynamic documents in Content Distribution Networks (CDN). Compared to traditional propagation and invalidation approach to maintain the consistency of data at replicas with the original copy at the server, author proposed a hybrid approach that
20588758
Cluster computing
Cluster computing can be described as a fusion of the fields of parallel, high-performance, distributed, and high-availability computing. Cluster computing has become a hot topic of research among academic and industry community including system designers, network developers, language designers, standardizing forums, algorithm developers, graduate students and faculties. The use of clusters as computing platform is not just limited to scientific and engineering applications; there are many business applications that can benefit from the use of clusters. There are many exciting areas of development in cluster computing with new ideas as well as hybrids of old ones being deployed for production as well as research systems. The aim of this special issue is to bring together original and latest work from both academia and industry on various issues related to cluster computing. This research, and development, is being done in many areas but there are a few that are of special interest. The first one is, with no doubt, the network. Clusters are based on the communication between nodes and designing fast and low latency networks is a must for clusters to become the configuration of the future. Plenty of work being done in this are in
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Shedding light on stereoscopic segmentation
We propose a variational algorithm to jointly estimate the shape, albedo, and light configuration of a Lambertian scene from a collection of images taken from different vantage points. Our work can be thought of as extending classical multi-view stereo to cases where point correspondence cannot be established, or extending classical shape from shading to the case of multiple views with unknown light sources. We show that a first naive formalization of this problem yields algorithms that are numerically unstable, no matter how close the initialization is to the true geometry. We then propose a computational scheme to overcome this problem, resulting in provably stable algorithms that converge to (local) minima of the cost functional. Although we restrict our attention to Lambertian objects with uniform albedo, extensions of our framework are conceivable.
14241332
Visual tracking in the presence of motion blur
We consider the problem of visual tracking of regions of interest in a sequence of motion blurred images. Traditional methods couple tracking with deblurring in order to correctly account for the effects of motion blur. Such coupling is usually appropriate, but computationally wasteful when visual tracking is the lone objective. Instead of deblurring images, we propose to match regions by blurring them. The matching score for two image regions is governed by a cost function that only involves the region deformation parameters and two motion blur vectors. We present an efficient algorithm to minimize the proposed cost function and demonstrate it on sequences of real blurred images.
2282922
Estimation of 3D Surface Shape and Smooth Radiance from 2D Images: A Level Set Approach
We cast the problem of shape reconstruction of a scene as the global region segmentation of a collection of calibrated images. We assume that the scene is composed of a number of smooth surfaces and a background, both of which support smooth Lambertian radiance functions. We formulate the problem in a variational framework, where the solution (both the shape and radiance of the scene) is a minimizer of a global cost functional which combines a geometric prior on shape, a smoothness prior on radiance and a data fitness score. We estimate the shape and radiance via an alternating minimization: The radiance is computed as the solutions of partial differential equations defined on the surface and the background. The shape is estimated using a gradient descent flow, which is implemented using the level set method. Our algorithm works for scenes with smooth radiances as well as fine homogeneous textures, which are known challenges to traditional stereo algorithms based on local correspondence.
9201508
Structure from Motion Causally Integrated Over Time
We describe an algorithm for reconstructing three-dimensional structure and motion causally, in real time from monocular sequences of images. We prove that the algorithm is minimal and stable, in the sense that the estimation error remains bounded with probability one throughout a sequence of arbitrary length. We discuss a scheme for handling occlusions (point features appearing and disappearing) and drift in the scale factor. These issues are crucial for the algorithm to operate in real time on real scenes. We describe in detail the implementation of the algorithm, which runs on a personal computer and has been made available to the community. We report the performance of our implementation on a few representative long sequences of real and synthetic images. The algorithm, which has been tested extensively over the course of the past few years, exhibits honest performance when the scene contains at least 20-40 points with high contrast, when the relative motion is "slow" compared to the sampling frequency of the frame grabber (30 Hz), and the lens aperture is "large enough" (typically more than 30/spl deg/ of visual field).
7863218
A semi-direct approach to structure from motion
The problem of structure from motion is often decomposed into two steps: feature correspondence and three-dimensional reconstruction. This separation often causes gross errors when establishing correspondence fails. Therefore, we advocate the necessity to integrate visual information not only in time (i.e. across different views), but also in space, by matching regions – rather than points – using explicit photometric deformation models. We present an algorithm that integrates image-feature tracking and three-dimensional motion estimation into a closed loop, while detecting and rejecting outlier regions that do not fit the model. Due to occlusions and the causal nature of our algorithm, a drift in the estimates accumulates over time. We describe a method to perform global registration of local estimates of motion and structure by matching the appearance of feature regions stored over long time periods. We use image intensities to construct a score function that takes into account changes in brightness and contrast. Our algorithm is recursive and suitable for real-time implementation.