By Stanislaw Ambroszkiewicz, Jerzy Brzeziński, Wojciech Cellary, Adam Grzech, Krzysztof Zieliński
This booklet offers complicated software program improvement instruments for development, deployment and governance of carrier orientated structure (SOA) purposes. Novel technical innovations and paradigms, formulated throughout the learn degree and through improvement of such instruments are awarded and illustrated through sensible utilization examples. accordingly this ebook can be of curiosity not just to theoreticians but additionally to engineers who take care of real-life difficulties. also, every one bankruptcy includes an summary of comparable paintings, permitting comparability of the proposed innovations with exiting options in numerous components of the SOA improvement approach. This makes the e-book fascinating additionally for college students and scientists who examine comparable concerns.
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Extra resources for Advanced SOA Tools and Applications
In , a service selection was proposed in a way that maximizes user satisfaction expressed as utility functions over QoS attributes. However, this approach assumes that all service parameters are constant. g. g. response time of service or throughput of service data transfer). For this case, we propose request control with a dynamic estimation of values of parameters characterizing network service instances. We distinguish two separate cases for considered approaches to request control: 44 A.
Semantic composition or GraphFold algorithm ) can be used. Another approach is to use pre-defined mapping rules and a reasoning engine to find the best possible mapping conforming to the non-functional requirements. The last composition stage is an optimization stage. The task performed at this point consists in finding such a version of the atomic ICT service available within the system: that non-functional requirements for the entire composite service are met. Additionally, certain composite service optimization tasks may be performed at this stage.
There are several known approaches to QoS optimization such as graph-based methods and mathematical programming (integer programming, stochastic programming). g. genetic algorithms. The result of service composition is a composite service execution graph, which is, similarly to functionalities graph, a DAG, but its nodes are constituted not by functionalities but by services stored in the repositories. In fact, the composite service execution graph should have the same structure as the functionalities graph, and its nodes should contain services with the functionality described in the corresponding nodes of the functionality graph.