8,672 research outputs found
Formal Aspects of Grid Brokering
Coordination in distributed environments, like Grids, involves selecting the
most appropriate services, resources or compositions to carry out the planned
activities. Such functionalities appear at various levels of the infrastructure
and in various means forming a blurry domain, where it is hard to see how the
participating components are related and what their relevant properties are. In
this paper we focus on a subset of these problems: resource brokering in Grid
middleware. This paper aims at establishing a semantical model for brokering
and related activities by defining brokering agents at three levels of the Grid
middleware for resource, host and broker selection. The main contribution of
this paper is the definition and decomposition of different brokering
components in Grids by providing a formal model using Abstract State Machines
QoS-Aware Middleware for Web Services Composition
The paradigmatic shift from a Web of manual interactions to a Web of programmatic interactions driven by Web services is creating unprecedented opportunities for the formation of online Business-to-Business (B2B) collaborations. In particular, the creation of value-added services by composition of existing ones is gaining a significant momentum. Since many available Web services provide overlapping or identical functionality, albeit with different Quality of Service (QoS), a choice needs to be made to determine which services are to participate in a given composite service. This paper presents a middleware platform which addresses the issue of selecting Web services for the purpose of their composition in a way that maximizes user satisfaction expressed as utility functions over QoS attributes, while satisfying the constraints set by the user and by the structure of the composite service. Two selection approaches are described and compared: one based on local (task-level) selection of services and the other based on global allocation of tasks to services using integer programming
Semantic verification of Behavior Conformance
This paper introduces a formal yet practical method to verify whether the behavior design of a distributed application conforms to the behavior design of the enterprise in which the application is embedded. The method allows both enterprise architects and application architects to talk about designs in their own terms, and introduces a common set of terms as the linking pin between enterprise and application designs. The formal semantics of these common terms allows us to verify the conformance between an enterprise and its applications formally and automatically
NLSC: Unrestricted Natural Language-based Service Composition through Sentence Embeddings
Current approaches for service composition (assemblies of atomic services)
require developers to use: (a) domain-specific semantics to formalize services
that restrict the vocabulary for their descriptions, and (b) translation
mechanisms for service retrieval to convert unstructured user requests to
strongly-typed semantic representations. In our work, we argue that effort to
developing service descriptions, request translations, and matching mechanisms
could be reduced using unrestricted natural language; allowing both: (1)
end-users to intuitively express their needs using natural language, and (2)
service developers to develop services without relying on syntactic/semantic
description languages. Although there are some natural language-based service
composition approaches, they restrict service retrieval to syntactic/semantic
matching. With recent developments in Machine learning and Natural Language
Processing, we motivate the use of Sentence Embeddings by leveraging richer
semantic representations of sentences for service description, matching and
retrieval. Experimental results show that service composition development
effort may be reduced by more than 44\% while keeping a high precision/recall
when matching high-level user requests with low-level service method
invocations.Comment: This paper will appear on SCC'19 (IEEE International Conference on
Services Computing) on July 1
- âŠ