scholarly journals On-Demand Service-Oriented Architecture and Standardization

2011 ◽  
Author(s):  
Fei He ◽  
Keqing He ◽  
Peng Liang ◽  
Jian Wang
Keyword(s):  
Service Oriented Architecture ◽  
On Demand ◽  
Service Oriented ◽  
Demand Service

Toward an on demand service-oriented architecture

2005 ◽  
Vol 44 (1) ◽  
pp. 81-107 ◽  
Author(s):  
C. H. Crawford ◽  
G. P. Bate ◽  
L. Cherbakov ◽  
K. Holley ◽  
C. Tsocanos
Keyword(s):  
Service Oriented Architecture ◽  
On Demand ◽  
Service Oriented ◽  
Demand Service

SCCS - A Supply Chian Collaboration Service

2011 ◽  
Vol 48-49 ◽  
pp. 1002-1005
Author(s):  
Hui Ping Lin ◽  
Xu Wei Zhu ◽  
Wei Ping Li ◽  
Li Liu ◽  
Zhao Hui Xie
Keyword(s):  
Supply Chain ◽  
Service Oriented Architecture ◽  
Low Cost ◽  
Supply Chain Performance ◽  
Supply Chain Collaboration ◽  
Business Partners ◽  
On Demand ◽  
Flexible Support ◽  
Business Application ◽  
Service Oriented

This paper presents a supply chain collaboration service (SCCS) in SaaS paradigm to support inter-organization interaction between business partners. SaaS is very attractive to enterprises because it offers low cost and flexible on-demand IT solution. The paper presents an extensible service oriented architecture that can integrate business application as a service into SCCS. In order to improve the supply chain performance, it provides flexible support for information sharing between business partners. The SCCS prototype has been developed.

Research on Knowledge Service Oriented Expert Management System

2014 ◽  
Vol 519-520 ◽  
pp. 1568-1571
Author(s):  
Su Yan Wu ◽  
Wen Bo Li
Keyword(s):  
Management System ◽  
Heterogeneous Data ◽  
Data Sources ◽  
Access To Information ◽  
Retrieval Method ◽  
Knowledge Service ◽  
On Demand ◽  
Heterogeneous Data Sources ◽  
Service Oriented ◽  
Demand Service

The distinctive characteristics of knowledge service oriented expert management system needs to have instant, on-demand service, accurate service, comprehensive services, and personalized service. In order to meet the requirements of the establishment of this system, this paper studied the construction of expert resources and expert retrieval services , and The crowdsourcing technology-based open expert body build, experts of different heterogeneous data sources access to information based expert body interaction semantics expert retrieval method

Envisioning the Paradigm of Service Oriented Hydrology Intelligence (SOHI)

2010 ◽  
pp. 172-198
Author(s):  
Pethuru Raj Chelliah
Keyword(s):  
Real Time ◽  
Business Intelligence ◽  
Information Technologies ◽  
Service Oriented Architecture ◽  
Knowledge Engineering ◽  
Reference Architecture ◽  
Data Intensive ◽  
Related Data ◽  
On Demand ◽  
Service Oriented

Hydrology is an increasingly data-intensive discipline and the key contribution of existing and emerging information technologies for the hydrology ecosystem is to smartly transform the water-specific data to information and to knowledge that can be easily picked up and used by various stakeholders and automated decision engines in order to forecast and forewarn the things to unfold. Attaining actionable and realistic insights in real-time dynamically out of both flowing as well as persisting data mountain is the primary goal for the aquatic industry. There are several promising technologies, processes, and products for facilitating this grand yet challenging objective. Business intelligence (BI) is the mainstream IT discipline representing a staggering variety of data transformation and synchronization, information extraction and knowledge engineering techniques. Another paradigm shift is the overwhelming adoption of service oriented architecture (SOA), which is a simplifying mechanism for effectively designing complex and mission-critical enterprise systems. Incidentally there is a cool convergence between the BI and SOA concepts. This is the stimulating foundation for the influential emergence of service oriented business intelligence (SOBI) paradigm, which is aptly recognized as the next-generation BI method. These improvisations deriving out of technological convergence and cluster calmly pervade to the ever-shining water industry too. That is, the bubbling synergy between service orientation and aquatic intelligence empowers the aquatic ecosystem significantly in extracting actionable insights from distributed and diverse data sources in real time through a host of robust and resilient infrastructures and practices. The realisable inputs and information being drawn from water-related data heap contribute enormously in achieving more with less and to guarantee enhanced safety and security for total human society. Especially as the green movement is taking shape across the globe, there is a definite push from different quarters on water and ecology professionals to contribute their mite immensely and immediately in permanently arresting the ecological degradation. In this chapter, we have set the context by incorporating some case studies that detail how SOA has been a tangible enabler of hydroinformatics. Further down, we have proceeded by explaining how SOA-sponsored integration concepts contribute towards integrating different data for creating unified and synchronized views and to put the solid and stimulating base for quickly deriving incisive and decisive insights in the form of hidden patterns, predictions, trends, associations, tips, etc. from the integrated and composite data. This enables real-time planning of appropriate countermeasures, tactics as well as strategies to put the derived in faster activation and actuation modes. Finally the idea is to close this chapter with an overview of how SOA celebrates in establishing adaptive, on-demand and versatile SOHI platforms. SOA is insisted as the chief technique for developing and deploying agile, adaptive, and on-demand hydrology intelligence platforms as a collection of interoperable, reusable, composable, and granular hydrology and technical services. The final section illustrates the reference architecture for the proposed SOHI platform.

scholarly journals An SOA-Based Model for the Integrated Provisioning of Cloud and Grid Resources

2012 ◽  
Vol 2012 ◽  
pp. 1-19
Author(s):  
Andrea Bosin
Keyword(s):  
High Performance ◽  
Service Oriented Architecture ◽  
On Demand ◽  
Computing Model ◽  
Networked Computing ◽  
Service Oriented ◽  
Computing Grid ◽  
Grid Resources ◽  
Performance Computing

In the last years, the availability and models of use of networked computing resources within reach of e-Science are rapidly changing and see the coexistence of many disparate paradigms: high-performance computing, grid, and recently cloud. Unfortunately, none of these paradigms is recognized as the ultimate solution, and a convergence of them all should be pursued. At the same time, recent works have proposed a number of models and tools to address the growing needs and expectations in the field of e-Science. In particular, they have shown the advantages and the feasibility of modeling e-Science environments and infrastructures according to the service-oriented architecture. In this paper, we suggest a model to promote the convergence and the integration of the different computing paradigms and infrastructures for the dynamic on-demand provisioning of resources from multiple providers as a cohesive aggregate, leveraging the service-oriented architecture. In addition, we propose a design aimed at endorsing a flexible, modular, workflow-based computing model for e-Science. The model is supplemented by a working prototype implementation together with a case study in the applicative domain of bioinformatics, which is used to validate the presented approach and to carry out some performance and scalability measurements.

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