Carmela Comito

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The Grid is an integrated infrastructure for coordinated resource sharing and problem solving in distributed environments. The effective and efficient use of stored data and its transformation into information and knowledge will be a main driver in Grid evolution. The use of ontologies to describe Grid resources will simplify and structure the systematic(More)
Bioinformatics is as a bridge between life science and computer science: computer algorithms are needed to face complexity of biological processes. Bioinformatics applications manage complex biological data stored into distributed and often heterogeneous databases and require large computing power. We discuss requirements of such applications and present(More)
Bioinformatics can be considered as a bridge between life science and computer science. Biology requires high and large computing power to performance biological applications and to access huge number of distributed and (often) heterogeneous databases. Computer scientists and database communities have expertises in high performance algorithms computation(More)
Venous thromboembolism (VTE) is a major cause of maternal morbidity and mortality during pregnancy or early after delivery, remaining a diagnostic and therapeutic challenge in both states. The absolute incidence of pregnancy-associated VTE has been reported as 1 in 1,000 to 1 in 2,000 deliveries. With 5–6 million new births computed in Europe in 2010, the(More)
Data Grids provide transparent access to heterogeneous and autonomous data resources. The main contribution of this paper is the presentation of a data sharing system that (i) is tailored to data grids, (ii) supports well established and widely spread relational DBMSs, and (iii) adopts a hybrid architecture by relying on a peer model for query reformulation(More)
XML is emerging as the “universal” language for semistructured data description/exchange, and new issues regarding the management of XML data, both in terms of performance and usability, are becoming critical. The application of knowledge-based synthesization and compression methods (i.e. derivation of synthetic views and lossless/lossy approximation of(More)
In this paper we present an Energy-Aware Scheduling strategy that assigns computational tasks over a network of mobile devices optimizing the energy usage. The main design principle of our scheduler is to find a task allocation that prolongs network lifetime by balancing the energy load among the devices. We have evaluated the scheduler using a prototype of(More)