scholarly journals On-demand attribute-based service discovery for mobile WSANs

2011 ◽  
Author(s):  
Klaas Thoelen ◽  
Sam Michiels ◽  
Wouter Joosen
Keyword(s):  
Service Discovery ◽  
On Demand

Cloud Architecture for Dynamic Service Composition

2012 ◽  
Vol 4 (2) ◽  
pp. 17-31 ◽  
Author(s):  
Jiehan Zhou ◽  
Kumaripaba Athukorala ◽  
Ekaterina Gilman ◽  
Jukka Riekki ◽  
Mika Ylianttila
Keyword(s):  
Service Composition ◽  
Service Discovery ◽  
Service Computing ◽  
Cloud Architecture ◽  
On Demand ◽  
Dynamic Service Composition ◽  
Pervasive Service ◽  
Computing Environments ◽  
Computational Resources ◽  
Demand Service

Service composition provides value-adding services through composing basic Web services, which may be provided by various organizations. Cloud computing presents an efficient managerial, on-demand, and scalable way to integrate computational resources (hardware, platform, and software). However, existing Cloud architecture lacks the layer of middleware to enable dynamic service composition. To enable and accelerate on-demand service composition, the authors explore the paradigm of dynamic service composition in the Cloud for Pervasive Service Computing environments and propose a Cloud-based Middleware for Dynamic Service Composition (CM4SC). In this approach, the authors introduce the CM4SC ‘Composition as a Service’ middleware layer into conventional Cloud architecture to allow automatic composition planning, service discovery and service composition. The authors implement the CM4SC middleware prototype utilizing Windows Azure Cloud platform. The prototype demonstrates the feasibility of CM4SC for accelerating dynamic service composition and that the CM4SC middleware-accelerated Cloud architecture offers a novel way for realizing dynamic service composition.

Research on Merging Cluster Algorithm for QoS-Oriented Supply and Demand

2011 ◽  
Vol 121-126 ◽  
pp. 4625-4629
Author(s):  
Xiu Zhen Feng ◽  
Gao Feng Wu
Keyword(s):  
Web Services ◽  
Service Discovery ◽  
Cluster Algorithm ◽  
Supply And Demand ◽  
Agglomerative Clustering ◽  
On Demand ◽  
Large Numbers ◽  
Fcm Clustering ◽  
Key Issues ◽  
Qos Requirement

Discovering service-on-demand for large numbers of functionality-similar web services is one of the key issues in service discovery study. To find out the proper service among the functionality-similar web services, a merging cluster algorithm regarding QoS-oriented supply and demand is proposed in this paper. To meet the target, FCM clustering is adopted for agglomerative clustering between the user’s QoS requirement information and the QoS information from Web Service resources. Then, the sequence could be determined by similarity computation with the same clustering. Lastly, the numerical example is presented to illustrate that the service-on-demand can be discovered efficiently and effectively.

Psychology 101, on demand

2008 ◽  
Author(s):  
Jamie Chamberlin
Keyword(s):  
On Demand
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