6163740
SEP: a space efficient pipelining technique for managing disk buffers in multimedia servers
We present techniques for managing disks as a buffer for the tertiary storage of multimedia servers. A unified disk space is used to not only cache frequently referenced objects, but also to provide staging buffers for playing back objects. A new staging technique and three buffer replacement policies are investigated. The simulation results indicate that the staging method is very efficient, and each of the replacement policies offers significant additional improvement. Some of the performance issues are also analyzed analytically. The mathematical model provides guidelines for good multimedia systems design using the proposed techniques.
9138036
Earthworm: a network memory management technique for large-scale distributed multimedia applications
The two main operating constraints of today's multimedia servers are the I/O bandwidth and communication bandwidth limitations. Both of these problems are addressed in this paper using a novel technique called Earthworm. In this scheme, the network memory is used as a huge cache for buffering multimedia data. Dramatic reduction in the demand on the I/O bandwidth, therefore, can be achieved. This scheme also chains display stations to allow them to forward video streams. This strategy eliminates the congestion at the communication port of the server. Removing this bottleneck allows our technique to operate on the vast aggregate bandwidth of the WAN rather than being constrained by the very limited local bandwidth available to the server. A unique feature of the Earthworm approach is that every display station using the server attempts to make some contribution to the caching space and communication bandwidth. The arrival of a new request, therefore, can be seen as a contributor, rather than just a burden to the server. This characteristic ensures the scalability of our design to support very large multimedia applications.
7304743
Proxy ecology - cooperative proxies with artificial life
In this paper, we propose a novel P2P cooperative proxy cache system using an individual-based model. We borrow the idea from an ecological system as well as economic systems to manage the cooperative proxies through data and information exchange among individual proxies. The data flow among proxy nodes creates artificial life for the cooperative proxies. The proxy servers with artificial life can automatically configure themselves into a virtual proxy graph. The aggregate effect of caching actions by individual peer proxies automatically distributes the Web document closer to the clients and balances the workload. Our simulation results show that the proposed proxy caching scheme tremendously improves the system performance. In addition, the individual-based design model ensures the simplicity and scalability of the cache system.
54104798
Data allocation algorithms for distributed video servers
14997765
2PSM: an efficient framework for searching video information in a limited-bandwidth environment
Abstract. We present a novel technique, called 2-Phase Service Model, for streaming videos to home users in a limited-bandwidth environment. This scheme first delivers some number of non-adjacent data fragments to the client in Phase 1. The missing fragments are then transmitted in Phase 2 as the client is playing back the video. This approach offers many benefits. The isochronous bandwidth required for Phase 2 can be controlled within the capability of the transport medium. The data fragments received during Phase 1 can be used to provide an excellent preview of the video. They can also be used to facilitate VCR-style operations such as fast-forward and fast-reverse. Systems designed based on this method are less expensive because the fast-forward and fast-reverse versions of the video files are no longer needed. Eliminating these files also improves system performance because mapping between the regular files and their fast-forward and fast-reverse versions is no longer part of the VCR operations. Furthermore, since each client machine handles its own VCR-style interaction, this technique is very scalable. We provide simulation results to show that 2-Phase Service Model is able to handle VCR functions efficiently. We also implement a video player called {\em FRVplayer}. With this prototype, we are able to judge that the visual quality of the previews and VCR-style operations is excellent. These features are essential to many important applications. We discuss the application of FRVplayer in the design of a video management system, called VideoCenter. This system is intended for Internet applications such as digital video libraries.
42282919
Exploring Local Community Structures in Large Networks
In this paper, we extend the concept of degree from single vertex to sub-graph, and present a formal definition of module/community in a network based on this extension. A new locally optimized algorithm is designed to find the module for a given source vertex in a network. Our analysis shows that the complexity of this algorithm is O(K2d), where K is the number of vertices to be explored in the sub-graph and d is the average degree of the vertices in the sub-graph. Based on this algorithm, we implement a JAVA tool, MoNet, for exploring local community structures in large networks. Using this tool to analyze a co-purchase network from Amazon shows that there are local community structures in this network. Further analyses on these local community structures demonstrate that media items are much easier to form compact local modules than book items do, indicating that recommending digital media items to customers based on co-purchasing information in the online store will be more efficient than recommending books.
7760234
Automated Discovery of Active Motifs in Three Dimensional Molecules
In this paper we present a method for discovering approximately common motifs (also known as active motifs) in three dimensional (3D) molecules. Each node in a molecule is represented by a 3D point in the Euclidean Space and each edge is represented by an undirected line segment connecting two nodes in the molecule. Motifs are rigid substructures which may occur in a molecule after allowing for an arbitrary number of rotations and translations as well as a small number (specified by the user) of node insert/delete operations in the motifs or the molecule. (We call this "approximate occurrence.") The proposed method combines the geometric hashing technique and block detection algorithms for undirected graphs. To demonstrate the utility of our algorithms, we discuss their applications to classifying three families of molecules pertaining to antibacterial sulfa drugs, anti-anxiety agents (benzodiazepines) and antiadrenergic agents (β receptors). Experimental results indicate the good performance of our algorithms and the high quality of the discovered motife.
8287323
A recurrent neural network for solving linear projection equations
Linear projection equations arise in many optimization problems and have important applications in science and engineering. In this paper, we present a recurrent neural network for solving linear projection equations in real time. The proposed neural network has two layers and is amenable to parallel implementation with simple hardware. In the theoretical aspect, we prove that the proposed neural network can converge globally to the solution set of the problem when the matrix involved in the problem is positive semidefinite and can converge exponentially to a unique solution when the matrix is positive definite. In addition, we analyze the stability of the related dynamic system in detail. As an application, we show that the proposed neural network can be used directly to solve linear and convex quadratic programming problems and linear complementary problems with positive semidefinite matrices. The validity and transient behavior of the neural network are demonstrated by using three numerical examples.
18821545
Multiperiodicity and Exponential Attractivity Evoked by Periodic External Inputs in Delayed Cellular Neural Networks
We show that an n-neuron cellular neural network with time-varying delay can have 2n periodic orbits located in saturation regions and these periodic orbits are locally exponentially attractive. In addition, we give some conditions for ascertaining periodic orbits to be locally or globally exponentially attractive and allow them to locate in any designated region. As a special case of exponential periodicity, exponential stability of delayed cellular neural networks is also characterized. These conditions improve and extend the existing results in the literature. To illustrate and compare the results, simulation results are discussed in three numerical examples.
1365809
New techniques for extracting features from protein sequences
In this paper we propose new techniques to extract features from protein sequences. We then use the features as inputs for a Bayesian neural network (BNN) and apply the BNN to classifying protein sequences obtained from the PIR (Protein Information Resource) database maintained at the National Biomedical Research Foundation. To evaluate the performance of the proposed approach, we compare it with other protein classifiers built based on sequence alignment and machine learning methods. Experimental results show the high precision of the proposed classifier and the complementarity of the bioinformatics tools studied in the paper.
39453122
Xml Clustering And Retrieval Through Principal Component Analysis
XML is increasingly important in data exchange and information management. A great deal of efforts have been spent in developing efficient techniques for storing, querying, indexing and accessing XML documents. In this paper we propose a new approach to clustering XML data. In contrast to previous work, which focused on documents defined by different DTDs, the proposed method works for documents with the same DTD. Our approach is to extract features from documents, modeled by ordered labeled trees, and transform the documents to vectors in a high-dimensional Euclidean space based on the occurrences of the features in the documents. We then reduce the dimensionality of the vectors by principal component analysis (PCA) and cluster the vectors in the reduced dimensional space. The PCA enables one to identify vectors with co-occurrent features, thereby enhancing the accuracy of the clustering. We also discuss an extension of our techniques to XML retrieval. Experimental results based on documents obtained from Wisconsin's XML data bank show the effectiveness and good performance of the proposed techniques.