5072535
A Workflow-based Computational Resource Broker with Information Monitoring in Grids
As grid computing becomes a reality, a resource broker is needed to manage and monitor available resources. This work presents a workflow-based computational resource broker whose main function is to match available resources with user requests and consider network information status during matchmaking. The resource broker provides a uniform interface for accessing available and the appropriate resources via user credentials. We utilize the NWS tool to monitor the network-related information and resources status. Also, we constructed a grid platform using Globus Toolkit that integrates the distributed resources of five universities in Taichung, Taiwan, where the resource broker is developed. As a result, the proposed broker provides secure and updated information about available resources and serves as a link to the diverse systems available in the grid
12707268
A Peer-to-Peer Based Framework of InterLibrary Cooperation for Digital Libraries
Traditionally, interlibrary cooperation is an important interaction between libraries. Nevertheless, the emerging digital library architecture has not explicitly supported this requirement. In this paper, we proposed an interlibrary cooperation framework for digital libraries using P2P technology. An application of this framework to Faculty Publication Sharing System was presented. Besides, a reputation model based on data mining is utilized to provide libraries with incentives to join this framework
15261618
A Jobs Allocation Strategy for Multiple DRBL Diskless Linux Clusters with Condor Schedulers
In this paper, we construct four DRBL-based diskless Linux PC clusters and install Globus Toolkit and Condor scheduler on the master node of each cluster. All diskless clusters can be merged into a powerful computing environment. To utilize the computing power, we propose a jobs allocation strategy for application execution. We use HPL to conduct some performance evaluations and analyze those data to form a formula for jobs allocation. The information server will calculate the value of computing power based on our formula and find the most appropriate cluster to execute the job. It can make our large computing environment that can execute the jobs in a more efficient way
5823907
Building an e-learning platform by access grid and data grid technologies
Due to overall popularity of the Internet, e-learning has become a hot method of learning in recent years. Through the Internet, learners can freely absorb new knowledge without the restriction of time and place. Many companies have adopted e-learning to train their employees. The e-learning system can make an enterprise more competitive by increasing the knowledge of its employees. As we know, e-learning has become one of the most potential e-commerce businesses. At present, most e-learning environment architectures are in consideration of a single computer or server as its erecting foundation. As soon as its workload increases, the software and hardware need to be updated or renewed; this is a big burden to a company with insufficient budget. Thus, in this research we employ a kind of grid computing technology, called "access grid", to integrate the idle computer resources in an enterprise into an e-learning platform for substituting the purchase of costly high-level server and equipment. The access grid supports group-to-group communication via high-speed networking over the Internet. It provides high quality audio and real-time video interactive interface for e-learning users. All the hardware cost is reasonable so that companies or academies can easily set up their own access grid node. By using access grid technologies, enterprises can integrate their training materials into knowledge repository such as "data grid" as the e-learning VOD platform so that the knowledge can be shared and published more flexibly and widely.
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.
60294203
A Parallel Loop Self-Scheduling on Extremely Heterogeneous PC Clusters
Cluster computers are a viable and less expensive alternative to symmetric multiprocessor systems. However, a serious difficulty in concurrent programming of a cluster computer system is how to deal with scheduling and load balancing of such a system which may consist of heterogeneous computers Self-scheduling schemes suitable for parallel loops with independent iterations on heterogeneous computer clusters have been designed in the past These schemes, such as FSS, GSS and TSS, can achieve load balancing in SMP, even in a moderate heterogeneous environment, but are not suitable in extremely heterogeneous environments. In this paper, we propose a heuristic approach to solve parallel loop scheduling problems on an extremely heterogeneous PC cluster environment.
10473585
Metadata design for Chinese medicine digital library using XML
The development of Chinese medicine has been growing rapidly and is beginning to draw significant attention globally. In Hong Kong in particular, the government has targeted Chinese medicine as one of its major future developments. A system for registering Chinese medical practitioners is being set up and a Chinese medicine port for medical manufacturing and research is being investigated. Although it has drawn significant attention, information about Chinese medicine is not yet widely available on the Internet, and searching for such information is extremely difficult. In this paper, we present an XML metadata design for Chinese medicine. The system encompasses a register server, information servers, a search engine and client programs that have been developed to browse and search the XML documents that are available in distributed Chinese medicine digital libraries.
5563875
Intelligent agents for retrieving chinese Web financial news
As the popularity of World Wide Web increases, many newspapers expand their services by providing news information on the Web in order to be competitive and increase benefit. The Web provides real time dissemination of financial news to investors. However, most investors find it difficult to search for the financial information of interest from the huge Web information space. Most of the commercial search engines are not user friendly and do not provide any tailor-made intelligent agents to search for relevant Web documents on behalf of users. Users have to exert a lot of effort to submit an appropriate query to obtain the information they want. Intelligent agents that learn user preferences and monitor the postings of Web information providers are desired. In this paper, we present an intelligent agent that utilizes user profiles and user feedback to search for the Chinese Web financial news articles on behalf of users. A Chinese indexing component is developed to index the continuously fetched Chinese financial news articles. User profiles capture the basic knowledge of user preferences based on the sources of news articles, the regions of the news reported, categories of industries related, the listed companies, and user specified keywords. User feedback captures the semantics of the user rated news articles. The search engine will rank the top 20 news articles that users are most interested in based on these inputs. Experiments were conducted to measure the performance of the agents based on the inputs from user profile and user feedback.
13803760
A bandwidth-based polling scheme for QoS support in Bluetooth
A flexible bandwidth management scheme namely Bandwidth-based Polling (BBP) for Bluetooth is proposed. A framing structure of time is defined in BBP, and the master allocates proper number of slots for each active slave in a frame. BBP allows the master to poll a slave more than once to achieve high flexibility for bandwidth allocation. The calculation of the polling time as well as the payload type for a slave is according to the bandwidth requirement of the slave and the limit of the frame size controlled by the master. Extension of BBP for supporting slaves with the SCO link and slaves without bandwidth requirement (best-effort slaves) is also proposed. Simulation results have shown the efficiency and fairness of BBP in bandwidth management. The flexibility of bandwidth allocation depends on the maximum polling time preset by BBP. A larger maximum polling time makes the higher flexibility of bandwidth allocation at the expense of a longer latency before reaching the equilibrium state. Analysis of the impact of the maximum polling time on bandwidth allocation is also presented in the paper.
14357839
Clustering-training for Data Stream Mining
Mining data streams has attracted much attention recently. Labeled samples needed by most current stream classification methods are more difficult and expensive to obtain than unlabeled ones. This paper proposed a semi-supervised learning algorithm - clustering-training to utilize the unlabeled samples. It uses clustering to select confidently unlabeled samples, and uses them to re-train the classifier incrementally. Experiments on synthetic and real data set showed the effectiveness of the proposed algorithm
18290708
Searching the peer-to-peer networks: The community and their queries
Peer-to-Peer (P2P) networks provide a new distributed computing paradigm on the Internet for file sharing. The decentralized nature of P2P networks fosters cooperative and non-cooperative behaviors in sharing resources. Searching is a major component of P2P file sharing. Several studies have been reported on the nature of queries of World Wide Web (WWW) search engines, but studies on queries of P2P networks have not been reported yet. In this report, we present our study on the Gnutella network, a decentralized and unstructured P2P network. We found that the majority of Gnutella users are located in the United States. Most queries are repeated. This may be because the hosts of the target files connect or disconnect from the network any time, so clients resubmit their queries. Queries are also forwarded from peers to peers. Findings are compared with the data from two other studies of Web queries. The length of queries in the Gnutella network is longer than those reported in the studies of WWW search engines. Queries with the highest frequency are mostly related to the names of movies, songs, artists, singers, and directors. Terms with the highest frequency are related to file formats, entertainment, and sexuality. This study is important for the future design of applications, architecture, and services of P2P networks.