16103436
Web-Based Parallel Simulation of AGVs Using Java and JINI
The vision of Computational Grids promises an exciting future for the distributed simulation community. In this project we make a small but practical step toward the grand vision of distributed simulation by using certain prevailing Internet technologies to enable access of simulation services anytime and anywhere. Specifically, this project focuses on accessing distributed simulation of AGVs (Automated Guided Vehicle) in container port operations through the World Wide Web. The objectives are to explore and address relevant issues, evaluate various approaches, demonstrate a workable version. We initially construct the AGV simulation system in an indirect communication model and identify its merits and demerits. Then, we explore the use of JINI technology for an efficient and robust direct communication architecture.
2945218
On querying geospatial and georeferenced metadata resources in G-Portal
G-Portal is a Web portal system providing a range of digital library services to access geospatial and georeferenced resources on the Web. Among them are the storage and query subsystems that provide a central repository of metadata resources organized under different projects. In G-Portal, all metadata resources are represented in XML (Extensible Markup Language) and they are compliant to some resource schemas defined by their creators. The resource schemas are extended versions of a basic resource schema making it easy to accommodate all kinds of metadata resources while maintaining the portability of resource data. To support queries over the geospatial and georeferenced metadata resources, a XQuery-like query language known as RQL (Resource Query Language) has been designed. We present the RQL language features and provide some experimental findings about the storage design and query evaluation strategies for RQL, queries.
34215309
Jini-enabled high performance computing
The vision of computational grids promises an exciting future for high performance computing (HPC). In the project presented we make a small but practical step toward the grand vision of pervasive HPC by using some of the prevailing Internet technologies to enable access of HPC anytime and anywhere. Specifically, the project focuses on HPC that could be accessed by using the World Wide Web. We have conducted experiments based on engineering/scientific applications. Examples include simulations of automated guided vehicles (hereafter AGVs for short) in container port operations, N-body and molecular simulations. We initially build systems based on an ad-hoc approach, whose merits and demerits are identified. Then, we employ Jini technology to reconstruct the system architecture and present a more efficient and robust model. Performance studies are also presented. The objectives are to explore and address relevant issues, evaluate various approaches, demonstrate a workable version and conduct experiments with actual Web-enabled applications. The result is that now we are able to partially realize the dream of using the HPCs anytime and anywhere through devices such as a wireless/mobile computer, as long as they are armed with a common Web browser.
12742605
An Automated Algorithm for Extracting Website Skeleton
The huge amount of information available on the Web has attracted many research efforts into developing wrappers that extract data from webpages. However, as most of the systems for generating wrappers focus on extracting data at page-level, data extraction at site-level remains a manual or semi-automatic process. In this paper, we study the problem of extracting website skeleton, i.e. extracting the underlying hyperlink structure that is used to organize the content pages in a given website. We propose an automated algorithm, called the Sew algorithm, to discover the skeleton of a website. Given a page, the algorithm examines hyperlinks in groups and identifies the navigation links that point to pages in the next level in the website structure. The entire skeleton is then constructed by recursively fetching pages pointed by the discovered links and analyzing these pages using the same process. Our experiments on real life websites show that the algorithm achieves a high recall with moderate precision.
3761715
A multicommodity flow model for distributed stream processing
The rapid development of computer technology has enabled streaming applications to emerge from many areas of the IT industry. A fundamental problem in such stream processing systems is how to best utilize the available resources so that the overall system performance is optimized. In most real time systems, applications are often running in a decentralized, distributed environment. At any given time, no server has the global information about all the servers in the system. It is thus desirable to have distributed solutions capable of adapting to or absorbing local changes in production rates and in network conditions. This paper addresses the fundamental resource allocation question in the distributed stream processing setting. Specifically, we consider a generic model for stream processing systems. Each stream is required to complete a series of tasks to become finished product. Each server is responsible for a subset of the processing tasks for possibly a subset of the streams. All servers have finite computing resources and all communication links have finite available bandwidth. We consider the resource allocation problem so as to maximize the total throughput of the system. Our problem can be described as a generalization of the traditional multicommodity flow problem [1]. Traditional multicommodity flow problem looks for the best way to use of the link capacities to deliver the maximum throughput for the flows in the whole network. In our problem, in addition to the link bandwidth constraints, we also have processing power constraints for each server. Furthermore, we allow flow shrinkage or expansion so as to model operations such
12952126
Long range dependence and heavy tail distributions
3758350
An Analytical Approach to the Performance Evaluation of Master-Slave Computational Models
Abstract Many stochastic models and analysis techniques have been proposed in the literature during the last two decades for the performance evaluation of parallel and distributed systems. However, few of them are directly applicable to practical systems which are generally too complex. In this paper, we analyze performances of the master–slave computational model, one of the most commonly used models in parallel and distributed computations. We propose a hybrid analytical approach by using techniques from the theories of both stochastic task graphs and queueing networks. We apply this method to the analysis of a computational chemistry application running on a Transputer based system. The proposed method turns out to be not only very efficient in time for large systems but also very accurate compared to measuring.
2458786
High Performance Embedded Route Lookup Coprocessor for Network Processors
Embedded Route Lookup Coprocessors (RLCs) are attractive for their potential in building high-performance Network Processors. But compared with conventional lookup schemes, it always imposes more severe restrictions on table size and power consumption, which poses challenge in the state of art. In this paper, we propose a novel lookup mechanism, Compounded CAM with Optimized Bitmap Compression (CCAM-OBC), which employs different lookup methods for prefixes of different length ranges, so as to combine the benefits of CAMs and bitmap compressed tries. With this scheme, table size, power consumption and update complexity are all well optimized while very high lookup throughput is achieved, which makes it a perfect solution to embedded RLC. For a real-life 130K-prefix route table, the implemented prototype performs more than 100 Million Packets Per Second (MPPS) with only 24KB TCAM, 48KB BCAM and 251KB SRAM. Furthermore, each update needs only 2 memory accesses averagely.
15783652
Low bit-rate video streaming for face-to-face teleconference
Face-to-face video teleconferencing is very important for real time communication. Current teleconferencing applications use standard video codecs, such as MPEG 1/2/4, for the compression of face video. Either a high bandwidth is required for high quality video transmission, or the transmitted face video is blurred at low bitrates. We present a system for real-time coding of face video at low bit-rate. There are two main contributions. First, we improve the technique of long term memory prediction by selecting frames into the database in an optimal way. A new frame is selected into the database only when it is significantly different from those frames which are already in the database. In this way, the database can cover a wider range of images. Second, we incorporate prior knowledge about faces into the long term memory prediction framework. The prior knowledge includes: (1) facial motions are repetitive such that most of them can be reconstructed from multiple reference frames; (2) different components of the face and the background can tolerate different levels of error because of different perceptual importance. Experiments show that, at similar PSNR, the proposed system works much faster and achieves better visual quality than the standard H.264/JVT codec.