14199867
Peer-to-peer architecture for content-based music retrieval on acoustic data
In traditional peer-to-peer search networks, operations focus on properly labeled files such as music or video, and the actual search is often limited to text tags. The explosive growth of available multimedia documents in recent years calls for more flexible search capabilities, namely search by content. Most content-based search algorithms are computationally intensive, making them inappropriate for a peer-to-peer environment. In this paper, we discuss a content-based music retrieval algorithm that can be decomposed and parallelized efficiently. We present a peer-to-peer architecture for such a system that makes use of spare resources among subscribers, with protocols that dynamically redistribute load in order to maximize throughput and minimize inconvenience to subscribers. Our framework can be extended beyond the music retrieval domain and adapted to other scenarios where resource pooling is desired, as long as the underlying algorithm satisfies certain conditions.
6654135
Finding interesting associations without support pruning
Association rule mining has heretofore relied on the condition of high support to do its work efficiently. In particular, the well-known a-priori algorithm is only effective when the only rules of interest are relationships that occur very frequently. However, there are a number of applications, such as data mining, identification of similar Web documents, clustering and collaborative filtering, where the rules of interest have comparatively few instances in the data. In these cases, we must look for highly correlated items, or possibly even causal relationships between infrequent items. We develop a family of algorithms for solving this problem, employing a combination of random sampling and hashing techniques. We provide an analysis of the algorithms developed and conduct experiments on real and synthetic data to obtain a comparative performance analysis.
13186184
Discovering event evolution graphs from newswires
In this paper, we propose an approach to automatically mine event evolution graphs from newswires on the Web. Event evolution graph is a directed graph in which the vertices and edges denote news events and the evolutions between events respectively, in a news affair. Our model utilizes the content similarity between events and incorporates temporal proximity and document distributional proximity as decaying functions. Our approach is effective in presenting the inside developments of news affairs along the timeline, which can facilitate users' information browsing tasks.
6731359
A performance-based grid intrusion detection system
Distributed denial-of-service (DDoS) and denial-of-service (DoS) are the most dreadful network threats in recent years. In this paper, we propose a grid-based IDS, called performance-based grid intrusion detection system (PGIDS), which exploits grid's abundant computing resources to detect enormous intrusion packets and improve the drawbacks of traditional IDSs which suffer from losing their detection effectiveness and capability when processing massive network traffic. For balancing detection load and accelerating the performance of allocating detection node (DN), we use exponential average to predict network traffic and then assign the collected actual traffic to the most suitable DN. In addition, score subtraction algorithm (SSA) and score addition algorithm (SAA) are deployed to update and reflect the current performance of a DN. PGIDS detects not only DoS/DDoS attacks but also logical attacks. Experimental results show that PGIDS is truly an outstanding system in detecting attacks.
40839198
A Recursive-Adjustment Co-allocation Scheme in Data Grid Environments
The co-allocation architecture was developed in order to enable parallel downloads of datasets from multiple servers. Several co-allocation strategies have been coupled and used to exploit rate differences among various client-server links and to address dynamic rate fluctuations by dividing files into multiple blocks of equal sizes. However, a major obstacle, the idle time of faster servers having to wait for the slowest server to deliver the final block, makes it important to reduce differences in finish time among replica servers. In this paper, we propose a dynamic co-allocation scheme, namely Recursive-Adjustment Co-Allocation scheme, to improve the performance of data transfer in Data Grids. Our approach reduces the idle time spent waiting for the slowest server and decreases data transfer completion time.
21318621
Design and implementation of a computational grid for bioinformatics
The popular technologies, Internet computing and grid technologies promise to change the way we tackle complex problems. They enable large-scale aggregation and sharing of computational, data and other resources across institutional boundaries. And harnessing these new technologies effectively transforms scientific disciplines ranging from high-energy physics to the life sciences. The computational analysis of biological sequences is a kind of computation driven science. Cause the biology data growing quickly and these databases are heterogeneous. We can use the grid system sharing and integrating the heterogeneous biology database. As we know, bioinformatics tools can speed up analysis the large-scale sequence data, especially about sequence alignment and analysis. The FASTA is a tool for aligning multiple protein or nucleotide sequences. These two bioinformatics software, which we used is a distributed and parallel version. The software uses a message-passing library called MPI (message passing interface) and runs on distributed workstation clusters as well as on traditional parallel computers. A grid computing environment is proposed and constructed on multiple Linux PC clusters by using globus toolkit (GT) and SUN grid engine (SGE). The experimental results and performances of the bioinformatics tool using on grid system are also presented.
10215892
Implementation and evaluation of a Java based computational grid for bioinformatics applications
In the present study, THUBioGrid, an experimental distributed computing application for bioinformatics (BioGrid) is proposed. THUBioGrid incorporates directory services (data and software), grid computing methods (security, authentication, data transport and remote jobs), and gene sequence/genomic data processing methods. It uses Java CoG Kit plus bioinformatics Java packages to perform various computational tasks. The performance of THUBioGrid has been tested by executing the FASTA and mpiBLAST programs for protein sequence alignment applications. Results demonstrate the speed-up effects with increasing number of processors used in the computations.