변수 추상화를 활용한 행위 기반 서비스 컴포지션
Behavior-level Service Composition by Variable Abstraction
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초록
The service composition based on Service-Oriented Architecture(SOA) can make us view various machines or its functionalities in the Web or Internet-of-Things environment as 'service', and efficiently create new value-added services that users want by compositing different services if there is no service to satisfy the client. The service composition problem with respect to behavioral descriptions deals with the automatic synthesis of a coordinator service that controls a set of services to reach a goal state. Despite its importance, however, solving the service composition problem with only partial observations remains to be doubly exponential in the number of variables in service descriptions, rendering any attempts to compute an exact solution for modest size impractical. Toward this challenge, in this paper, we propose novel approximation-based approaches using abstraction methods. We empirically validate that our proposals can solve realistic problems efficiently.
Abstract
The service composition based on Service-Oriented Architecture(SOA) can make us view various machines or its functionalities in the Web or Internet-of-Things environment as 'service', and efficiently create new value-added services that users want by compositing different services if there is no service to satisfy the client. The service composition problem with respect to behavioral descriptions deals with the automatic synthesis of a coordinator service that controls a set of services to reach a goal state. Despite its importance, however, solving the service composition problem with only partial observations remains to be doubly exponential in the number of variables in service descriptions, rendering any attempts to compute an exact solution for modest size impractical. Toward this challenge, in this paper, we propose novel approximation-based approaches using abstraction methods. We empirically validate that our proposals can solve realistic problems efficiently.
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