9696681
Construct a grid computing environment for bioinformatics
Internet computing and grid technologies promise to change the way we tackle complex problems. They will enable large-scale aggregation and sharing of computational, data and other resources across institutional boundaries. And harnessing these new technologies effectively will transform 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. The FASTA is a tool for aligning multiple protein or nucleotide sequences. FASTA which we used is a distributed and parallel version. The software uses a message-passing library called MPl (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 in this paper.
12951016
A shareable e-learning platform using data grid technology
Over the past decade, speed in the transmission of knowledge is no longer the way it used to be. Due to this influence, conventional educational methodology has also followed this trend and has gone through a momentous transformation. An excellent example is e-learning which has achieved and broken through the restrictions of time and space. In recent years it has become one of the most popular teaching methods. SCORM (Sharable Course Object Reference Model) the most popular e-learning standard has been adapted from many differing e-learning platforms. Normally, courseware meeting SCORM standards is sharable with other e-learning platforms. Most e-learning platforms however are unable to share courseware directly on the Internet. With this in mind, we have employed one type of grid computing technology called "data grid" in order to achieve this. This technology allows the integration of different SCORM platforms into a huge e-learning environment.
7849532
A Peer-to-Peer Resource Sharing System with Data Grid Technology for Mobile Devices
Increases in mobile device processing power, storage capacity, and connectivity in recent years have led to a rapid rise in mobile device use. But mobile users face challenges in making connections with other users in order to share resources. To address this issue, we propose an architecture that uses peer-to-peer protocol to establish a resource sharing platform for mobile devices, combined with a data grid to help analyze and classify resources.
32464432
An Enhanced Parallel Loop Self-Scheduling Scheme for Cluster Environments
In this paper, a parallel loop self-scheduling scheme for heterogeneous PC cluster systems is proposed. Though the proposed scheme does allow users to choose parameters before the execution initialization phase, there are still weaknesses that motivate us to go further with new improvements in that scheme. For instance, a decision on a fixed and monotonous parameter can easily lead to invalid schedule by using previous input information. Thus, it is proposed in this paper a new scheme, where the scheduling parameter can be adjusted dynamically and fit into most widely available computer systems, in order to provide higher overall performance.
7749374
A Performance-Based Approach to Dynamic Workload Distribution for Master-Slave Applications on Grid Environments
Effective workload distribution techniques can significantly reduce the total completion time of a program on grid computing environments. In this paper, we propose a dynamic performance-based workload partition approach for master-slave types of applications on grids. Furthermore, we implement two types of applications and conduct the experimentations on our grid testbed. Experimental results showed that our method could execute more efficiently than traditional schemes.
5672930
An e-Learning Platform Based on Grid Architecture
The overall popularity of the Internet has helped e-learning become a hot method for learning in recent years. Over the Internet, learners can freely absorb new knowledge without restrictions on time or place. Many companies have adopted e-learning to train their employees. An e-learning system can make an enterprise more competitive by increasing the knowledge of its employees. E-learning has been shown to have impressive potential in e-commerce. At present, most e-learning environment architectures use single computers or servers as their structural foundations. As soon as their work loads increase, their software and hardware must be updated or renewed. This is a big burden on organizations that lack sufficient funds. Thus, in this study we employ a kind of Grid Computing technology, called the ”Data Grid” to integrate idle computer resources in enterprises into e-learning platforms, thus eliminating the need to purchase costly high-level servers and other equipment.
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.
17968973
Authoring Cases from Free-Text Maintenance Data
Automatically authoring or acquiring cases in the case-based reasoning (CBR) systems is recognized as a bottleneck issue that can determine whether a CBR system will be successful or not. In order to reduce human effort required for authoring the cases, we propose a framework for authoring the case from the unstructured, free-text, historic maintenance data by applying natural language processing technology. This paper provides an overview of the proposed framework, and outlines its implementation, an automated case creation system for the Integrated Diagnostic System. Some experimental results for testing the framework are also presented.
2577694
Efficient acoustic index for music retrieval with various degrees of similarity
Content-based music retrieval research has mostly focused on symbolic data rather than acoustical data. Given that there are no general-purpose transcription algorithms that can convert acoustical data into musical scores, new methods are needed to do music retrieval on acoustical data. In this paper, we review some existing methods on contentbased music retrieval, discuss different definitions of music similarity, and present a new framework to perform music indexing and retrieval. The framework is based on an earlier prototype we developed, with significant improvements.In our framework known as MACSIS, each audio file is broken down into small segments and converted into feature vectors. All vectors are stored in a high-dimensional indexing structure called LSH, a probabilistic indexing scheme that makes use of multiple hashing instances in parallel. At retrieval time, small segments of audio matches are retrieved from the index and pieced together using the Hough Transform technique, and results are used as the basis to rank candidate matches.
38023286
Distributed mobile tracking: a novel location management scheme for routing improvement in cellular IP networks
In this paper, a novel location management scheme, distributed mobile tracking (DMT), is proposed for routing improvement in Cellular IP networks. A mobile-tracking tree (MT-Tree) for each active mobile host is established by tracking the movement of the host in DMT. Two mechanisms, pruning process and growing process, are also proposed to improve DMT. Packet transmissions can follow the route on the MT-Tree instead of using the gateway route. Simulation results have shown that DMT has the advantages of shorter routing paths as well as load balance for wired links over the original gateway-based location management scheme. Moreover, three multicast protocols for Cellular IP are proposed: GBMP, GBMP-RO, and MTMP. In GBMP, the gateway is responsible for group management as well as multicast transmission. Multicast packets received by the base station are first forwarded to the gateway. The gateway then forwards the packets to each member of the group by multiple unicasting. GBMP-RO, a modified version of GBMP, adopts the idea of source routing for multicast transmissions. MTMP is mainly based on the MT-Tree routing scheme. However, if not all group members can be covered by MT-Tree routing, MTMP will instead adopt GBMP-RO for multicast transmission. Simulation results demonstrate that MTMP has the advantages over GBMP and GBMP-RO in terms of load balance in the Cellular IP network.
9754310
A Simulation-Based Procedure for Expert System Evaluation
It is well recognized that the evaluation of the knowledge-based system is very important and difficult in the development of expert systems in the domains such as aviation and navigation. To alleviate some of the difficulties, and to reduce the development cost, the authors proposed an evaluating procedure based on simulation. The proposed procedure was designed to validate the functionality and capability of an expert system that was developed to provide decision-making support in ship navigation. In this paper, the developed expert system for collision avoidance is first outlined, and the procedure to evaluate the developed expert system by using a simulation-based approach is presented in details. It is also concluded that the simulation-based procedure is feasible and effective for evaluating expert systems in a number of different domains.