3,934 research outputs found
Toward Self-Organising Service Communities
This paper discusses a framework in which catalog service communities are built, linked for interaction, and constantly monitored and adapted over time. A catalog service community (represented as a peer node in a peer-to-peer network) in our system can be viewed as domain specific data integration mediators representing the domain knowledge and the registry information. The query routing among communities is performed to identify a set of data sources that are relevant to answering a given query. The system monitors the interactions between the communities to discover patterns that may lead to restructuring of the network (e.g., irrelevant peers removed, new relationships created, etc.)
Distributed top-k aggregation queries at large
Top-k query processing is a fundamental building block for efficient ranking in a large number of applications. Efficiency is a central issue, especially for distributed settings, when the data is spread across different nodes in a network. This paper introduces novel optimization methods for top-k aggregation queries in such distributed environments. The optimizations can be applied to all algorithms that fall into the frameworks of the prior TPUT and KLEE methods. The optimizations address three degrees of freedom: 1) hierarchically grouping input lists into top-k operator trees and optimizing the tree structure, 2) computing data-adaptive scan depths for different input sources, and 3) data-adaptive sampling of a small subset of input sources in scenarios with hundreds or thousands of query-relevant network nodes. All optimizations are based on a statistical cost model that utilizes local synopses, e.g., in the form of histograms, efficiently computed convolutions, and estimators based on order statistics. The paper presents comprehensive experiments, with three different real-life datasets and using the ns-2 network simulator for a packet-level simulation of a large Internet-style network
Hypermedia-based discovery for source selection using low-cost linked data interfaces
Evaluating federated Linked Data queries requires consulting multiple sources on the Web. Before a client can execute queries, it must discover data sources, and determine which ones are relevant. Federated query execution research focuses on the actual execution, while data source discovery is often marginally discussed-even though it has a strong impact on selecting sources that contribute to the query results. Therefore, the authors introduce a discovery approach for Linked Data interfaces based on hypermedia links and controls, and apply it to federated query execution with Triple Pattern Fragments. In addition, the authors identify quantitative metrics to evaluate this discovery approach. This article describes generic evaluation measures and results for their concrete approach. With low-cost data summaries as seed, interfaces to eight large real-world datasets can discover each other within 7 minutes. Hypermedia-based client-side querying shows a promising gain of up to 50% in execution time, but demands algorithms that visit a higher number of interfaces to improve result completeness
Exploiting peer group concept for adaptive and highly available services
This paper presents a prototype for redundant, highly available and fault
tolerant peer to peer framework for data management. Peer to peer computing is
gaining importance due to its flexible organization, lack of central authority,
distribution of functionality to participating nodes and ability to utilize
unused computational resources. Emergence of GRID computing has provided much
needed infrastructure and administrative domain for peer to peer computing. The
components of this framework exploit peer group concept to scope service and
information search, arrange services and information in a coherent manner,
provide selective redundancy and ensure availability in face of failure and
high load conditions. A prototype system has been implemented using JXTA peer
to peer technology and XML is used for service description and interfaces,
allowing peers to communicate with services implemented in various platforms
including web services and JINI services. It utilizes code mobility to achieve
role interchange among services and ensure dynamic group membership. Security
is ensured by using Public Key Infrastructure (PKI) to implement group level
security policies for membership and service access.Comment: The Paper Consists of 5 pages, 6 figures submitted in Computing in
High Energy and Nuclear Physics, 24-28 March 2003 La Jolla California. CHEP0
A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing
Data Grids have been adopted as the platform for scientific communities that
need to share, access, transport, process and manage large data collections
distributed worldwide. They combine high-end computing technologies with
high-performance networking and wide-area storage management techniques. In
this paper, we discuss the key concepts behind Data Grids and compare them with
other data sharing and distribution paradigms such as content delivery
networks, peer-to-peer networks and distributed databases. We then provide
comprehensive taxonomies that cover various aspects of architecture, data
transportation, data replication and resource allocation and scheduling.
Finally, we map the proposed taxonomy to various Data Grid systems not only to
validate the taxonomy but also to identify areas for future exploration.
Through this taxonomy, we aim to categorise existing systems to better
understand their goals and their methodology. This would help evaluate their
applicability for solving similar problems. This taxonomy also provides a "gap
analysis" of this area through which researchers can potentially identify new
issues for investigation. Finally, we hope that the proposed taxonomy and
mapping also helps to provide an easy way for new practitioners to understand
this complex area of research.Comment: 46 pages, 16 figures, Technical Repor
Spitzer data at the NASA/IPAC Infrared Science Archive (IRSA)
The NASA/IPAC Infrared Science Archive (IRSA) curates and serves science
data sets from NASA’s infrared and submillimeter projects and missions,
including IRAS, 2MASS, MSX, SWAS, ISO, IRTS and from the Spitzer Space
Telescope. All Spitzer data can be accessed from IRSA’s Spitzer mission page
at: http://irsa.ipac.caltech.edu/Missions/spitzer.html
Spitzer Legacy Enhanced Products along with ancillary data are delivered
in six month intervals starting from Fall 2004, until Fall 2006. IRSA continually
ingests the Spitzer data and the ancillary data, and these data are made
accessible through IRSA’s query engines. Legacy products for the C2D, FEPS,
GLIMPSE, GOODS, SINGS and SWIRE projects are accessible through a common
interface http://irsa.ipac.caltech.edu/applications/Atlas. This
engine returns the spatial footprints of observations and provides access to all
flavors of released data sets, including, where appropriate, previews of image
mosaics, 3-color image mosaics and spectra
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