Abstract Computational Grids are powerful platforms gathering computational power and storage spa... more Abstract Computational Grids are powerful platforms gathering computational power and storage space from thousands of geographically distributed resources. The applications running on such platforms need to efficiently and reliably access the various and heterogeneous distributed resources they offer. This can be achieved by using metadata information describing all available resources. It is therefore crucial to provide efficient metadata management architectures and frameworks.
SUMMARY In several scientific and business domains, very large data repositories are generated. T... more SUMMARY In several scientific and business domains, very large data repositories are generated. To find interesting and useful information in those repositories, efficient data mining techniques and knowledge discovery processes must be used.
Distributed Hash Tables (DHTs) provide scalable mechanisms for implementing resource discovery se... more Distributed Hash Tables (DHTs) provide scalable mechanisms for implementing resource discovery services in structured Peer-to-Peer (P2P) networks. However, DHT-based lookups do not support some types of queries that are fundamental in several classes of applications. A way to support arbitrary queries in structured P2P networks is implementing unstructured search techniques on top of DHTbased overlays.
The increasing computing power of mobile devices has opened the way to perform analysis and minin... more The increasing computing power of mobile devices has opened the way to perform analysis and mining of data in many real-life mobile scenarios, such as body-health monitoring, vehicle control, and wireless security systems. A key aspect to enable data analysis and mining over mobile devices is ensuring energy efficiency, as mobile devices are battery-power operated.
Abstract Today a large number of scientific and commercial applications often require to analyse ... more Abstract Today a large number of scientific and commercial applications often require to analyse large data sets maintained over geographically distributed sites by using the computational power of distributed high-performance environments. Advances in networking technology and computational infrastructure made it possible to construct large-scale distributed computing platforms, called computational grids, that provide dependable, consistent, and pervasive access to high-end computational resources.
The increasing use of computers in all the areas of human activities is resulting in huge collect... more The increasing use of computers in all the areas of human activities is resulting in huge collections of digital data. Databases are common everywhere and are used as repositories of every kind of data. Knowledge discovery techniques and tools are used today to analyze those very large data sets to identify interesting patterns and trends in them. When data is maintained over geographically distributed sites the computational power of distributed and parallel systems can be exploited for knowledge discovery in databases.
Abstract The Grid has rapidly moved from a toolkit-centered approach, composed of a set of middle... more Abstract The Grid has rapidly moved from a toolkit-centered approach, composed of a set of middleware tools, toward a more application-oriented Service Oriented Architecture in which resources are exposed as services. The soaring number of available services advocates distributed and semantic-based discovery architectures. Distribution promotes scalability and fault-tolerance whereas semantics is required to provide for meaningful descriptions of services and support their efficient retrieval.
Abstract Providing high level environments and advanced instruments able to support end users and... more Abstract Providing high level environments and advanced instruments able to support end users and developers is of main importance to help designers of complex grid applications and explore many of grid related benefits not yet fully exploited. In this paper we present a high-level grid programming environment oriented to data-intensive and knowledge discovery grid applications that share some common features with the software component paradigm.
Knowledge discovery tools and techniques are used in an increasing number of scientific and comme... more Knowledge discovery tools and techniques are used in an increasing number of scientific and commercial areas for the analysis of large data sets. When large data repositories are coupled with geographic distribution of data, users and systems, it is necessary to combine different technologies for implementing high-performance distributed knowledge discovery systems. On the other hand, computational grid is emerging as a very promising infrastructure for high-performance distributed computing.
Abstract Several systems adopting Peer-to-Peer (P2P) solutions for resource discovery in Grids ha... more Abstract Several systems adopting Peer-to-Peer (P2P) solutions for resource discovery in Grids have recently been proposed. This report looks at a P2P resource discovery framework aiming to manage various Grid resources and complex queries. Following the discussion on characteristics of Grid resources and related query requirements, a DHT-based framework leveraging different P2P resource discovery techniques is proposed.
Abstract Peer-to-peer (P2P) networks and grids are distributed computing models that enable decen... more Abstract Peer-to-peer (P2P) networks and grids are distributed computing models that enable decentralized collaboration by integrating computers into networks in which each can consume and offer services. P2P is a class of self-organizing systems or applications that takes advantage of distributed resources storage, processing, information, and human presence available at the Internet's edges.
Abstract Grid architecture is one of the cornerstones for successful development and proliferatio... more Abstract Grid architecture is one of the cornerstones for successful development and proliferation of Grid computing. The scale, dynamism and openness of the Grid, together with demands on its reliability, security and manageability, pose unique challenges on software architecture.
Computer science applications are becoming more and more network centric, ubiquitous, knowledge i... more Computer science applications are becoming more and more network centric, ubiquitous, knowledge intensive, and computing demanding. This trend will result soon in an ecosystem of pervasive applications and services that professionals and end-users can exploit everywhere. Recently, collections of IT services and applications, such as Web services and Cloud computing services, became available opening the way for accessing computing services as public utilities, like water, gas and electricity.
Abstract Nowadays huge amounts of electronic data are naturally collected in distributed sites, d... more Abstract Nowadays huge amounts of electronic data are naturally collected in distributed sites, due to either plural ownership or geographical distribution of the processes that produce data. Moving data to a location for extracting useful and actionable knowledge is usually considered unfeasible, for either policy or technical reasons. It thus becomes mandatory to mine them by exploiting the multiple distributed resources close to data repositories.
Abstract Through a service-based approach it is possible to define services for supporting distri... more Abstract Through a service-based approach it is possible to define services for supporting distributed and pervasive business intelligence applications in Grids. Those services can address all the tasks needed in data mining and in knowledge discovery processes starting from data selection and transport, to data analysis, knowledge models representation and visualization.
AbstrAct Knowledge discovery is a compute-and data-intensive process that allows for finding patt... more AbstrAct Knowledge discovery is a compute-and data-intensive process that allows for finding patterns, trends, and models in large datasets. The grid can be effectively exploited for deploying knowledge discovery applications because of the high performance it can offer and its distributed infrastructure. For effective use of grids in knowledge discovery, the development of middleware is critical to support data management, data transfer, data mining and knowledge representation.
Analysis of data is a complex process that often involves remote resources (computers, software, ... more Analysis of data is a complex process that often involves remote resources (computers, software, databases, files, etc.) and people (analysts, professionals, end users). Recently, distributed data mining techniques are used to analyze dispersed data sets. An advancement in this research area comes from the use of mobile computing technology for supporting new data analysis techniques and new ways to discover knowledge from every place in which people operate.
MapReduce is a programming model for parallel data processing widely used in Cloud computing envi... more MapReduce is a programming model for parallel data processing widely used in Cloud computing environments. Current MapReduce implementations are based on centralized master-slave architectures that do not cope well with dynamic Cloud infrastructures, like a Cloud of clouds, in which nodes may join and leave the network at high rates.
Abstract The Grid supports the sharing and coordinated use of resources in dynamic heterogeneous ... more Abstract The Grid supports the sharing and coordinated use of resources in dynamic heterogeneous distributed environments. The effective use of a Grid requires the definition of an approach to manage the heterogeneity of the involved resources that can include computers, data, network facilities and software tools provided by different organizations. This issue get more importance when complex applications, such as data-intensive simulations and data mining applications, executed on a Grid.
Peer-to-peer (P2P) computing is recognized as one of most prominent paradigms to achieve scalabil... more Peer-to-peer (P2P) computing is recognized as one of most prominent paradigms to achieve scalability in key components of Grid systems. One of these components is resource discovery, whose duty is to provide system-wide up-to-date information about resources, a task inherently limited in scalability. Unlike typical P2P systems, Grid systems manage not only static resources, but also resources whose characteristics change dynamically over time.
Abstract Computational Grids are powerful platforms gathering computational power and storage spa... more Abstract Computational Grids are powerful platforms gathering computational power and storage space from thousands of geographically distributed resources. The applications running on such platforms need to efficiently and reliably access the various and heterogeneous distributed resources they offer. This can be achieved by using metadata information describing all available resources. It is therefore crucial to provide efficient metadata management architectures and frameworks.
SUMMARY In several scientific and business domains, very large data repositories are generated. T... more SUMMARY In several scientific and business domains, very large data repositories are generated. To find interesting and useful information in those repositories, efficient data mining techniques and knowledge discovery processes must be used.
Distributed Hash Tables (DHTs) provide scalable mechanisms for implementing resource discovery se... more Distributed Hash Tables (DHTs) provide scalable mechanisms for implementing resource discovery services in structured Peer-to-Peer (P2P) networks. However, DHT-based lookups do not support some types of queries that are fundamental in several classes of applications. A way to support arbitrary queries in structured P2P networks is implementing unstructured search techniques on top of DHTbased overlays.
The increasing computing power of mobile devices has opened the way to perform analysis and minin... more The increasing computing power of mobile devices has opened the way to perform analysis and mining of data in many real-life mobile scenarios, such as body-health monitoring, vehicle control, and wireless security systems. A key aspect to enable data analysis and mining over mobile devices is ensuring energy efficiency, as mobile devices are battery-power operated.
Abstract Today a large number of scientific and commercial applications often require to analyse ... more Abstract Today a large number of scientific and commercial applications often require to analyse large data sets maintained over geographically distributed sites by using the computational power of distributed high-performance environments. Advances in networking technology and computational infrastructure made it possible to construct large-scale distributed computing platforms, called computational grids, that provide dependable, consistent, and pervasive access to high-end computational resources.
The increasing use of computers in all the areas of human activities is resulting in huge collect... more The increasing use of computers in all the areas of human activities is resulting in huge collections of digital data. Databases are common everywhere and are used as repositories of every kind of data. Knowledge discovery techniques and tools are used today to analyze those very large data sets to identify interesting patterns and trends in them. When data is maintained over geographically distributed sites the computational power of distributed and parallel systems can be exploited for knowledge discovery in databases.
Abstract The Grid has rapidly moved from a toolkit-centered approach, composed of a set of middle... more Abstract The Grid has rapidly moved from a toolkit-centered approach, composed of a set of middleware tools, toward a more application-oriented Service Oriented Architecture in which resources are exposed as services. The soaring number of available services advocates distributed and semantic-based discovery architectures. Distribution promotes scalability and fault-tolerance whereas semantics is required to provide for meaningful descriptions of services and support their efficient retrieval.
Abstract Providing high level environments and advanced instruments able to support end users and... more Abstract Providing high level environments and advanced instruments able to support end users and developers is of main importance to help designers of complex grid applications and explore many of grid related benefits not yet fully exploited. In this paper we present a high-level grid programming environment oriented to data-intensive and knowledge discovery grid applications that share some common features with the software component paradigm.
Knowledge discovery tools and techniques are used in an increasing number of scientific and comme... more Knowledge discovery tools and techniques are used in an increasing number of scientific and commercial areas for the analysis of large data sets. When large data repositories are coupled with geographic distribution of data, users and systems, it is necessary to combine different technologies for implementing high-performance distributed knowledge discovery systems. On the other hand, computational grid is emerging as a very promising infrastructure for high-performance distributed computing.
Abstract Several systems adopting Peer-to-Peer (P2P) solutions for resource discovery in Grids ha... more Abstract Several systems adopting Peer-to-Peer (P2P) solutions for resource discovery in Grids have recently been proposed. This report looks at a P2P resource discovery framework aiming to manage various Grid resources and complex queries. Following the discussion on characteristics of Grid resources and related query requirements, a DHT-based framework leveraging different P2P resource discovery techniques is proposed.
Abstract Peer-to-peer (P2P) networks and grids are distributed computing models that enable decen... more Abstract Peer-to-peer (P2P) networks and grids are distributed computing models that enable decentralized collaboration by integrating computers into networks in which each can consume and offer services. P2P is a class of self-organizing systems or applications that takes advantage of distributed resources storage, processing, information, and human presence available at the Internet's edges.
Abstract Grid architecture is one of the cornerstones for successful development and proliferatio... more Abstract Grid architecture is one of the cornerstones for successful development and proliferation of Grid computing. The scale, dynamism and openness of the Grid, together with demands on its reliability, security and manageability, pose unique challenges on software architecture.
Computer science applications are becoming more and more network centric, ubiquitous, knowledge i... more Computer science applications are becoming more and more network centric, ubiquitous, knowledge intensive, and computing demanding. This trend will result soon in an ecosystem of pervasive applications and services that professionals and end-users can exploit everywhere. Recently, collections of IT services and applications, such as Web services and Cloud computing services, became available opening the way for accessing computing services as public utilities, like water, gas and electricity.
Abstract Nowadays huge amounts of electronic data are naturally collected in distributed sites, d... more Abstract Nowadays huge amounts of electronic data are naturally collected in distributed sites, due to either plural ownership or geographical distribution of the processes that produce data. Moving data to a location for extracting useful and actionable knowledge is usually considered unfeasible, for either policy or technical reasons. It thus becomes mandatory to mine them by exploiting the multiple distributed resources close to data repositories.
Abstract Through a service-based approach it is possible to define services for supporting distri... more Abstract Through a service-based approach it is possible to define services for supporting distributed and pervasive business intelligence applications in Grids. Those services can address all the tasks needed in data mining and in knowledge discovery processes starting from data selection and transport, to data analysis, knowledge models representation and visualization.
AbstrAct Knowledge discovery is a compute-and data-intensive process that allows for finding patt... more AbstrAct Knowledge discovery is a compute-and data-intensive process that allows for finding patterns, trends, and models in large datasets. The grid can be effectively exploited for deploying knowledge discovery applications because of the high performance it can offer and its distributed infrastructure. For effective use of grids in knowledge discovery, the development of middleware is critical to support data management, data transfer, data mining and knowledge representation.
Analysis of data is a complex process that often involves remote resources (computers, software, ... more Analysis of data is a complex process that often involves remote resources (computers, software, databases, files, etc.) and people (analysts, professionals, end users). Recently, distributed data mining techniques are used to analyze dispersed data sets. An advancement in this research area comes from the use of mobile computing technology for supporting new data analysis techniques and new ways to discover knowledge from every place in which people operate.
MapReduce is a programming model for parallel data processing widely used in Cloud computing envi... more MapReduce is a programming model for parallel data processing widely used in Cloud computing environments. Current MapReduce implementations are based on centralized master-slave architectures that do not cope well with dynamic Cloud infrastructures, like a Cloud of clouds, in which nodes may join and leave the network at high rates.
Abstract The Grid supports the sharing and coordinated use of resources in dynamic heterogeneous ... more Abstract The Grid supports the sharing and coordinated use of resources in dynamic heterogeneous distributed environments. The effective use of a Grid requires the definition of an approach to manage the heterogeneity of the involved resources that can include computers, data, network facilities and software tools provided by different organizations. This issue get more importance when complex applications, such as data-intensive simulations and data mining applications, executed on a Grid.
Peer-to-peer (P2P) computing is recognized as one of most prominent paradigms to achieve scalabil... more Peer-to-peer (P2P) computing is recognized as one of most prominent paradigms to achieve scalability in key components of Grid systems. One of these components is resource discovery, whose duty is to provide system-wide up-to-date information about resources, a task inherently limited in scalability. Unlike typical P2P systems, Grid systems manage not only static resources, but also resources whose characteristics change dynamically over time.
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Papers by Paolo Trunfio