20,458 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
Evaluation method of the innovation project global efficiency
A complete system of indexes to evaluate the global efficiency of a new product development project must approach at least the following perspectives: the financial performances of the project; the project's value; the technical performances of the project; the efficiency of research and development activities of the project; the capacity of fitting in the estimated cost and duration of activities; the degree of integration between the R&D and production activities; the degree of integration between the R&D and marketing activities. Therefore, in this paper is drawn up a method for new product development projects evaluation, based on those seven perspectives.innovation project, evaluation method, value, financial performances
Online coherency identification and stability condition for large interconnected power systems using an unsupervised data mining technique
Identification of coherent generators and the determination of the stability system condition in large interconnected power system is one of the key steps to carry out different control system strategies to avoid a partial or complete blackout of a power system. However, the oscillatory trends, the larger amount data available and the non-linear dynamic behaviour of the frequency measurements often mislead the appropriate knowledge of the actual coherent groups, making wide-area coherency monitoring a challenging task. This paper presents a novel online unsupervised data mining technique to identify coherent groups, to detect the power system disturbance event and determine status stability condition of the system. The innovative part of the proposed approach resides on combining traditional plain algorithms such as singular value decomposition (SVD) and K -means for clustering together with new concept based on clustering slopes. The proposed combination provides an added value to other applications relying on similar algorithms available in the literature. To validate the effectiveness of the proposed method, two case studies are presented, where data is extracted from the large and comprehensive initial dynamic model of ENTSO-E and the results compared to other alternative methods available in the literature
A secure data outsourcing scheme based on Asmuth – Bloom secret sharing
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Data outsourcing is an emerging paradigm for data management in which a database is provided as a service by third-party service providers. One of the major benefits of offering database as a service is to provide organisations, which are unable to purchase expensive hardware and software to host their databases, with efficient data storage accessible online at a cheap rate. Despite that, several issues of data confidentiality, integrity, availability and efficient indexing of users’ queries at the server side have to be addressed in the data outsourcing paradigm. Service providers have to guarantee that their clients’ data are secured against internal (insider) and external attacks. This paper briefly analyses the existing indexing schemes in data outsourcing and highlights their advantages and disadvantages. Then, this paper proposes a secure data outsourcing scheme based on Asmuth–Bloom secret sharing which tries to address the issues in data outsourcing such as data confidentiality, availability and order preservation for efficient indexing
Confidentiality-Preserving Publish/Subscribe: A Survey
Publish/subscribe (pub/sub) is an attractive communication paradigm for
large-scale distributed applications running across multiple administrative
domains. Pub/sub allows event-based information dissemination based on
constraints on the nature of the data rather than on pre-established
communication channels. It is a natural fit for deployment in untrusted
environments such as public clouds linking applications across multiple sites.
However, pub/sub in untrusted environments lead to major confidentiality
concerns stemming from the content-centric nature of the communications. This
survey classifies and analyzes different approaches to confidentiality
preservation for pub/sub, from applications of trust and access control models
to novel encryption techniques. It provides an overview of the current
challenges posed by confidentiality concerns and points to future research
directions in this promising field
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