Composition of engineering web services with universal distributed data-flows framework based on ROA

Author(s):  
Kewei Duan ◽  
Julian Padget ◽  
H. Alicia Kim ◽  
Hiroshi Hosobe
2005 ◽  
Vol 19 (1) ◽  
pp. 25-42 ◽  
Author(s):  
David Liu ◽  
Jun Peng ◽  
Kincho H. Law ◽  
Gio Wiederhold ◽  
Ram D. Sriram

2016 ◽  
Vol 41 (1) ◽  
pp. 11-23
Author(s):  
Michael Takeo Magruder ◽  
Jeremy Pilcher

Michael Takeo Magruder, visual artist and researcher, discusses his digital and new media art and practice with Jeremy Pilcher, lawyer and academic, whose research engages with the intersection of art and law. Takeo's work asks viewers to question their relationship both to and within the real-time data flows generated by emerging technologies and the implications these have for archives. His art concerns the way institutions use such systems to create narratives that structure societies. This conversation discusses how Takeo's practice invites us, as individuals, to critically reflect on the implications of the stories that are both told to and about us by using gathered and distributed data.


2012 ◽  
Vol 3 (1) ◽  
pp. 41 ◽  
Author(s):  
A. Bergamasco ◽  
A. Benetazzo ◽  
S. Carniel ◽  
F.M. Falcieri ◽  
T. Minuzzo ◽  
...  

In order to monitor, describe and understand the marine environment, many research institutions are involved in the acquisition and distribution of ocean data, both from observations and models. Scientists from these institutions are spending too much time looking for, accessing, and reformatting data: they need better tools and procedures to make the science they do more efficient. The U.S. Integrated Ocean Observing System (US-IOOS) is working on making large amounts of distributed data usable in an easy and efficient way. It is essentially a network of scientists, technicians and technologies designed to acquire, collect and disseminate observational and modelled data resulting from coastal and oceanic marine regions investigations to researchers, stakeholders and policy makers. In order to be successful, this effort requires standard data protocols, web services and standards-based tools. Starting from the US-IOOS approach, which is being adopted throughout much of the oceanographic and meteorological sectors, we describe here the CNR-ISMAR Venice experience in the direction of setting up a national Italian IOOS framework using the THREDDS (THematic Real-time Environmental Distributed Data Services) Data Server (TDS), a middleware designed to fill the gap between data providers and data users. The TDS provides services that allow data users to find the data sets pertaining to their scientific needs, to access, to visualize and to use them in an easy way, without downloading files to the local workspace. In order to achieve this, it is necessary that the data providers make their data available in a standard form that the TDS understands, and with sufficient metadata to allow the data to be read and searched in a standard way. The core idea is then to utilize a Common Data Model (CDM), a unified conceptual model that describes different datatypes within each dataset. More specifically, Unidata (<a href="http://www.unidata.ucar.edu" target="_blank">www.unidata.ucar.edu</a>) has developed CDM specifications for many of the different kinds of data used by the scientific community, such as grids, profiles, time series, swath data. These datatypes are aligned the NetCDF Climate and Forecast (CF) Metadata Conventions and with Climate Science Modelling Language (CSML); CF-compliant NetCDF files and GRIB files can be read directly with no modification, while non compliant files can be modified to meet appropriate metadata requirements. Once standardized in the CDM, the TDS makes datasets available through a series of web services such as OPeNDAP or Open Geospatial Consortium Web Coverage Service (WCS), allowing the data users to easily obtain small subsets from large datasets, and to quickly visualize their content by using tools such as GODIVA2 or Integrated Data Viewer (IDV). In addition, an ISO metadata service is available through the TDS that can be harvested by catalogue broker services (e.g. GI-cat) to enable distributed search across federated data servers. Example of TDS datasets can be accessed at the CNR-ISMAR Venice site <a href="http://tds.ve.ismar.cnr.it:8080/thredds/catalog.html" target="_blank">http://tds.ve.ismar.cnr.it:8080/thredds/catalog.html</a>.


2021 ◽  
Author(s):  
Soheila Sadeghiram

<p>Service-oriented architecture (SOA) encourages the creation of modular applications involving Web services as the reusable components. Data-intensive Web services have emerged to manipulate and deal with the massive data emerged from technological advances and their various applications. Distributed Data-intensive Web Service Composition (DWSC) is a core of SOA, which includes the selection of data-intensive Web services from diverse locations on the network and composes them to accomplish a complicated task. As a fundamental challenge for service developers, service compositions must fulfil functional requirements and optimise Quality of Service (QoS), simultaneously. The QoS of a distributed DWSC is not only impacted by the QoS of component services and how the compositions are generated, but also by the locations of services and data transformation between services. However, existing works often neglect the impact of locations and data on service composition. The distributed DWSC has not been sufficiently studied in the literature. In this thesis, we first define the single-objective distributed DWSC that includes communication (e.g. bandwidth), Web service (execution time) and data (data cost) attributes. To this aim, we consider bandwidth information of communication links obtained using the location information of services. Based on the problem formulation, we then address the distributed DWSC problem by developing EC-based approaches. Those EC-based approaches are designed to incorporate domain-knowledge for effectively solving the distributed DWSC problem. Afterwards, we study the multi-objective distributed DWSC to satisfy different QoS requirements. In particular, the QoS-constrained distributed DWSC problem and user preferences are considered. For finding trade-off solutions for those problems, new Multi-objective Evolutionary Algorithms (MOEAs) are proposed based on the current Non-dominated Sorting Genetic Algorithm-II (NSGA-II). Furthermore, a new problem formulation for the dynamic distributed DWSC (D2−DWSC) problem with bandwidth fluctuations is proposed. An EC-based approach is developed to solve the D2-DWSC. Finally, extensive empirical evaluations are conducted that demonstrate the high performance of our proposed methods in finding composite services with good QoS.</p>


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