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Dive into the research topics where Andrea Clematis is active.

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Featured researches published by Andrea Clematis.


IEEE Computer | 1990

A system architecture for fault tolerance in concurrent software

Massimo Ancona; Gabriella Dodero; Vittoria Gianuzzi; Andrea Clematis; Eduardo B. Fernandez

A system architecture called the recovery metaprogram (RMP) is proposed. It separates the application from the recovery software, giving programmers a single environment that lets them use the most appropriate fault-tolerance scheme. To simplify the presentation of the RMP approach, it is assumed that the fault model is limited to faults originating in the application software, and that the hardware and kernel layers can mask their own faults from the RMP. Also, relationships between backward and forward error recovery are not considered. Some RMP examples are given, and a particular RMP implementation is described.<<ETX>>


Simulation Modelling Practice and Theory | 2013

Hybrid Clouds brokering: Business opportunities, QoS and energy-saving issues

Alfonso Quarati; Andrea Clematis; Antonella Galizia; Daniele D’Agostino

Abstract Hybrid Clouds couple the scalability offered by public Clouds with the greater control supplied by private ones. A (hybrid) Cloud broker acting as an intermediary between users and providers of public Cloud services, may support customers in the selection of the most suitable offers, optionally adding the provisioning of dedicated services with higher levels of quality. The paper presents a Cloud brokering algorithm delivering services with different level of non-functional requirements, to the private or public resources, on the basis of different scheduling criteria. With the objective of maximize user satisfaction and broker’s revenues, the algorithm pursues profit increases by reducing energy costs, through the adoption of energy saving mechanisms. A simulation model is used to evaluate performance in terms of broker’s revenue, user satisfaction and energy behavior of various allocation policies. Simulation results show that differences among policies depend on system loads and that the use of turn on and off techniques greatly improves energy savings at low and medium load rates.


International Journal of Geographic Information Systems | 1996

Parallel processing on heterogeneous networks for GIS applications

Andrea Clematis; Bianca Falcidieno; Michela Spagnuolo

Abstract The use of network-based parallel computing is gaining an increasing popularity for different reasons. Its exploitation depends on the availability of simple but effective methodologies to parallelize applications, and the availability of portable and efficient communication libraries to develop parallel programs. These two items are necessary to obtain performance advantages, and to ensure software portability and reusability. In this paper we present our experience in parallelizing, in a systematic way, a class of Geographical Information Systems applications. We discuss the use of two well-known communication libraries (PVM and Linda). Performance results are also reported.


Future Generation Computer Systems | 2010

Job-resource matchmaking on Grid through two-level benchmarking

Andrea Clematis; Angelo Corana; Daniele D'Agostino; Antonella Galizia; Alfonso Quarati

Grid environments must provide effective mechanisms able to select the most adequate resources satisfying application requirements. A description of applications and resources, grounded on a common and shared basis, is crucial to favour an effective pairing. A suitable criterion to match demand with supply is to characterize resources by means of their performance evaluated through the execution of low-level and application-specific benchmarks. We present GREEN, a distributed Matchmaker, based on a two-level benchmarking methodology. GREEN facilitates the ranking of Grid resources and the submission of jobs to the Grid, through the specification of both syntactic and performance requirements, independently of the underlying middleware and thus fostering Grid interoperability.


BioMed Research International | 2013

Cloud infrastructures for in silico drug discovery: economic and practical aspects.

Daniele D'Agostino; Andrea Clematis; Alfonso Quarati; Daniele Cesini; Federica Chiappori; Luciano Milanesi; Ivan Merelli

Cloud computing opens new perspectives for small-medium biotechnology laboratories that need to perform bioinformatics analysis in a flexible and effective way. This seems particularly true for hybrid clouds that couple the scalability offered by general-purpose public clouds with the greater control and ad hoc customizations supplied by the private ones. A hybrid cloud broker, acting as an intermediary between users and public providers, can support customers in the selection of the most suitable offers, optionally adding the provisioning of dedicated services with higher levels of quality. This paper analyses some economic and practical aspects of exploiting cloud computing in a real research scenario for the in silico drug discovery in terms of requirements, costs, and computational load based on the number of expected users. In particular, our work is aimed at supporting both the researchers and the cloud broker delivering an IaaS cloud infrastructure for biotechnology laboratories exposing different levels of nonfunctional requirements.


IEEE/ACM Transactions on Computational Biology and Bioinformatics | 2011

Image-Based Surface Matching Algorithm Oriented to Structural Biology

Ivan Merelli; Paolo Cozzi; Daniele D'Agostino; Andrea Clematis; Luciano Milanesi

Emerging technologies for structure matching based on surface descriptions have demonstrated their effectiveness in many research fields. In particular, they can be successfully applied to in silico studies of structural biology. Protein activities, in fact, are related to the external characteristics of these macromolecules and the ability to match surfaces can be important to infer information about their possible functions and interactions. In this work, we present a surface-matching algorithm, based on encoding the outer morphology of proteins in images of local description, which allows us to establish point-to-point correlations among macromolecular surfaces using image-processing functions. Discarding methods relying on biological analysis of atomic structures and expensive computational approaches based on energetic studies, this algorithm can successfully be used for macromolecular recognition by employing local surface features. Results demonstrate that the proposed algorithm can be employed both to identify surface similarities in context of macromolecular functional analysis and to screen possible protein interactions to predict pairing capability.


Computer Languages | 1993

Structuring conversation in operation/procedure oriented programming languages

Andrea Clematis; Vittoria Gianuzzi

Abstract The conversation scheme has been defined to design concurrent software which provides backward error recovery. Since presently no widespread programming language provides constructs for implementing conversations, we propose a methodology for structuring programs, following the conversation scheme. We analyze the use of conversation in languages which adopt the client-server model for processes interaction, pointing out solutions to problems arising from the use of operation and procedure oriented languages [1: Andrews and Schneider, ACM Comput. Surv. 15: 3–44; 1983], in which servers are implemented as remote procedures or monitors respectively. The features of a number of programming languages, which are the most suitable for structuring conversations are pointed out. The implementation of nested conversations is also discussed and finally, an industrial application in which our methodology has been profitably applied is presented.


Journal of Computational and Applied Mathematics | 2015

Scheduling strategies for enabling meteorological simulation on hybrid clouds

Alfonso Quarati; Emanuele Danovaro; Antonella Galizia; Andrea Clematis; Daniele D'Agostino; Antonio Parodi

The flexible and pay-as-you-go computing capabilities offered by Cloud infrastructures are very attractive for high-demanding e-Science applications like weather prediction simulators. For their ability to couple the scalability offered by public service provider with the greater control and customization provided by Private Clouds, Hybrid Clouds seem a particularly appealing solution to support meteorological researchers and weather departments in their every-day activity. Cloud Brokers interfacing customers with Cloud providers, may support scientists in the deployment and execution of demanding meteorological simulations, by hiding all the intricacies related to the management of powerful but often complex HPC systems.The paper presents a set of brokering strategies for Hybrid Clouds aimed at the execution of various instances of the weather prediction WRF model subject to different user requirements and computational conditions. A simulation-based analysis documents the performance of the different scheduling strategies at varying workloads and system configuration.


Computing | 2013

A QoS-aware broker for hybrid clouds

Daniele D’Agostino; Antonella Galizia; Andrea Clematis; Matteo Mangini; Ivan Porro; Alfonso Quarati

Hybrid Clouds seems able to offer their customers with differentiate solutions capable of providing more and personalized guarantees with respect to the basic service availability generally supplied. In the context of an Italian research project aimed to transfer ICT advancements from research centers towards ICT SMEs, the paper focuses on the design of a brokering tool for hybrid clouds capable to adequately respond to specific Quality of Service (QoS) constraints. Aimed at satisfying the highest number of user requests while trying maximizing the profit of the private provider, in the context of a posted price economic model, the proposed brokering algorithm may apply different allocation policies, based on the reservation of a quota of private resources to high-level QoS applications.


international conference on image analysis and processing | 2005

An object interface for interoperability of image processing parallel library in a distributed environment

Andrea Clematis; Daniele D'Agostino; Antonella Galizia

Image processing applications are computing demanding and since a long time much attention has been paid to the use of parallel processing. Emerging distributed and Grid based architectures represent new and well suited platforms that promise the availability of the required computational power. In this direction image processing has to evolve to heterogeneous environments, and a crucial aspect is represented by the interoperability and reuse of available and high performance code. This paper describes our experience in the development of PIMA(GE)2, Parallel IMAGE processing GEnoa server, obtained wrapping a library using the CORBA framework. Our aim is to obtain a high level of flexibility and dynamicity in the server architecture with a possible limited overhead. The design of a hierarchy of image processing operation objects and the development of the server interface are discussed.

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Alfonso Quarati

National Research Council

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Ivan Merelli

National Research Council

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Angelo Corana

National Research Council

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