2,713 research outputs found
An Integrated Semantic Web Service Discovery and Composition Framework
In this paper we present a theoretical analysis of graph-based service
composition in terms of its dependency with service discovery. Driven by this
analysis we define a composition framework by means of integration with
fine-grained I/O service discovery that enables the generation of a graph-based
composition which contains the set of services that are semantically relevant
for an input-output request. The proposed framework also includes an optimal
composition search algorithm to extract the best composition from the graph
minimising the length and the number of services, and different graph
optimisations to improve the scalability of the system. A practical
implementation used for the empirical analysis is also provided. This analysis
proves the scalability and flexibility of our proposal and provides insights on
how integrated composition systems can be designed in order to achieve good
performance in real scenarios for the Web.Comment: Accepted to appear in IEEE Transactions on Services Computing 201
ENORM: A Framework For Edge NOde Resource Management
Current computing techniques using the cloud as a centralised server will
become untenable as billions of devices get connected to the Internet. This
raises the need for fog computing, which leverages computing at the edge of the
network on nodes, such as routers, base stations and switches, along with the
cloud. However, to realise fog computing the challenge of managing edge nodes
will need to be addressed. This paper is motivated to address the resource
management challenge. We develop the first framework to manage edge nodes,
namely the Edge NOde Resource Management (ENORM) framework. Mechanisms for
provisioning and auto-scaling edge node resources are proposed. The feasibility
of the framework is demonstrated on a PokeMon Go-like online game use-case. The
benefits of using ENORM are observed by reduced application latency between 20%
- 80% and reduced data transfer and communication frequency between the edge
node and the cloud by up to 95\%. These results highlight the potential of fog
computing for improving the quality of service and experience.Comment: 14 pages; accepted to IEEE Transactions on Services Computing on 12
September 201
Robust execution of service workflows using redundancy and advance reservations
In this paper, we develop a novel algorithm that allows service consumers to execute business processes (or workflows) of interdependent services in a dependable manner within tight time-constraints. In particular, we consider large inter-organisational service-oriented systems, where services are offered by external organisations that demand financial remuneration and where their use has to be negotiated in advance using explicit service-level agreements (as is common in Grids and cloud computing). Here, different providers often offer the same type of service at varying levels of quality and price. Furthermore, some providers may be less trustworthy than others, possibly failing to meet their agreements. To control this unreliability and ensure end-to-end dependability while maximising the profit obtained from completing a business process, our algorithm automatically selects the most suitable providers. Moreover, unlike existing work, it reasons about the dependability properties of a workflow, and it controls these by using service redundancy for critical tasks and by planning for contingencies. Finally, our algorithm reserves services for only parts of its workflow at any time, in order to retain flexibility when failures occur. We show empirically that our algorithm consistently outperforms existing approaches, achieving up to a 35-fold increase in profit and successfully completing most workflows, even when the majority of providers fail
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