2002
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SUGGEST: a Web usage mining system
Baraglia R, Palmerini PDuring their navigation web users leave many records of their activity. This huge amount of data can be a useful source of knowledge. Sophisticated mining processes are needed for this knowledge to be extracted, understood and used. In this paper we propose aWeb UsageMining (WUM) system, called SUGGEST , designed to efficiently integrate the WUM process with the ordinary web server functionalities. It can provide useful information to make easier the web user navigation and to optimize the web server performance. Two quantities are introduced in order to give a measure of the quality of our WUM system.
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CNR IRIS
| CNR IRIS
2007
Conference article
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Local search for Grid scheduling
Klusacek D, Matyska L, Rudova H, Baraglia R, Capannini GThis work introduces local search based algorithms as a new technique for the Grid scheduling problem. Specific algorithms based on dispatching rules and local search were proposed and implemented to generate schedule for dynamically arriving jobs. Algorithm performance was compared with typical queue-based algorithms from the point of view of objective function optimisation and time required to generate scheduling solutions. Grid environment was simulated by Alea Simulator which is based on modified and extended Grid- Sim toolkit. The results showed that local search based algorithms may be promising technique with better performance than queue-based approaches while still fast enough to provide solution in a reasonable time.
See at:
abotea.rsise.anu.edu.au
| CNR IRIS
| CNR IRIS
2008
Conference article
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VoRaQue: RAnge QUeries on voronoi overlays
Albano M, Ricci L, Baldanzi M, Baraglia RThis paper presents VoRaQue, a software layer supporting range queries on Voronoi P2P overlays. VoRaQue maps data in a 2-dimensional space. The P2P overlay is defined by links connecting nodes that are close in the 2-dimensional space and by a set of long-range links which guarantee a poly-logarithmic routing. When a query is submitted, VoRaQue finds out a node belonging to the region defined by the query. A multicast spanning tree covering that region is then built by applying compass routing, a distributed protocol to embed a spanning tree into a Delaunay Triangulation. The paper presents the basic VoRaQue protocol, then introduces a set of optimizations and finally presents some experimental results.Source: PROCEEDINGS - IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS, pp. 495-500. Marrakech, Morocco, 6-9 Luglio 2008
DOI: 10.1109/iscc.2008.4625648Metrics:
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doi.org
| CNR IRIS
| ieeexplore.ieee.org
| CNR IRIS
2006
Journal article
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HMM: a static mapping algorithm to map parallel applications on grids
Baraglia R, Ferrini R, Ritrovato PIn this paper we present a static mapping heuristic, called Heterogeneous Multi-phase Mapping (HMM), which allows a suboptimal mapping of a parallel program onto a metacomputer to minimize the program execution time. HMM allocates parallel tasks by exploiting the information embedded in the parallelism forms used to implement an application. Moreover, it uses a local search technique together with the tabu search meta-heuristic. The experimental results show that the proposed approach performs well promising a significant potential to develop efficient mapping solutions for metacomputers.
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CNR IRIS
| CNR IRIS
2007
Journal article
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Dynamic personalization of Web sites without user intervention
Baraglia R, Silvestri FThe Web is an integral part of today's busi- ness dealings. Companies and institutions exploit the Web to conduct their business; customers make daily use of the Net to per- form all kinds of transactions. In addition, most users browse through pages of per- sonal interest. The Web, as we know, is massive and its data collected from count- less sources. Consequently, search tools should be able to accurately extract, filter, and select what is "hidden" from such tools.Source: COMMUNICATIONS OF THE ACM, vol. 50 (issue 2), pp. 63-67
DOI: 10.1145/1216016.1216022Metrics:
See at:
dl.acm.org
| Communications of the ACM
| CNR IRIS
| CNR IRIS
2003
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Multi-FPGA Systems Synthesis by Means of Evolutionary Computation
Hidalgo Ji, Fernández F, Lanchares J, Sánchez J M, Hermida R, Tomassini M, Baraglia R, Perego R, Garnica OMulti-FPGA systems (MFS) are used for a great variety of applications, for instance, dynamically re-configurable hardware applications, digital circuit emulation, and numerical computation. There are a great variety of boards for MFS implementation. In this paper a methodology for MFS design is presented. The techniques used are evolutionary programs and they solve all of the design tasks (partitioning placement and routing). Firstly a hybrid compact genetic algorithm solves the partitioning problem and then genetic programming is used to obtain a solution for the two other tasks.
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CNR IRIS
| CNR IRIS
2002
Journal article
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Metay: a Web-based metacomputing problem-solving environment for building complex applications
Baraglia R, Laforenza DIn this article we describe the main features of Meta , a software tool developed at CNUCE-CNR to build PSEs for the execution of complex applications on a Web-based metacomputer. This tool is designed to supply a completely transparent support to the user, who thus does not need to be aware of the location and the allocation of computing resources.Source: ERCIM NEWS, vol. 45, pp. 21-22
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CNR IRIS
| CNR IRIS
2004
Conference article
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An online recommender system
Baraglia R, Silvestri FOne of the most important class of Data Mining applications is the so called 'Web Mining Systems' which analyzes and extracts important and non-trivial knowledge from Web related data. Typical applications of Web Mining are represented by the personalization or recommender systems. These systems are aimed to extract knowledge from the analysis of historical information of a web server in order to improve the web site expressiveness in terms of readability and content availability. Typically, these systems are made up of two parts. One, which is usually executed off-line, analyzes the server access logs in order to find a suitable categorization, and another, which is usually executed online, classifies the active requests, according to the previous off-line analysis. In this paper we propose SUGGEST 2.0 a recommender system which differently from previously proposed WUM systems does not make use of an off-line component. Moreover, in the last part of the paper, we analyze the quality of the generated suggestions and the performance of our solution. To this purpose we also introduce a new quality metric which try to estimate the effectiveness of a recommender system as the capacity to anticipate users' requests that will be issued farther in the future.
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CNR IRIS
| CNR IRIS
2005
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Medical imaging demonstrator on a distributed virtual organisation
Baraglia R, Demi M, Di Bona S, Fontanelli R, Guerri D, Salvetti OIn several fields of the healthcare, there is a wide use of imaging techniques for diagnostic purposes, which usually lead to the acquisition of large sequences of images that are not easily analysed by the experts. The automatic processing of the events monitored represents an important support for the diagnosis. In this paper, we present a distributed decision support system for image classification based on neural networks. The applications presented are multidisciplinary, computational intensive and component based; therefore, a virtual organisation exploiting the GRID paradigm has been introduced in order to guarantee good performances of the diagnostic procedure and reliable results.
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CNR IRIS
| CNR IRIS
2001
Conference article
Unknown
A parallel compact genetic algorithm for multi-FPGA partitioning
Hidalgo J. I., Baraglia R. Perego R., Lanchares J., Tirade F.In this paper we investigate the design of a compact genetic algorithm to solve Multi-FPGA Partitioning problems. Nowadays Multi-FPGA systems are used for a great variety of applications such as dynamically re-configurable hardware applications, digital circuit emulation, and numerical computation. Both a sequential and a parallel version of a compact genetic algorithm (cGA) have been designed and implemented on a cluster of workstations. The peculiarities of the cGA permits to save memory in order to address large Multi-FPGA Parfitioning problems, while the exploitation of parallelism allows to reduce execution times. The good results achieved on several experiments conduced on different Multi-FPGA Partitioning instances show that this solution is viable to solve Multi-FPGA Partitioning problems.Source: Euromicro Workshop on Parallel and Distributed Processing, pp. 113–120, Mantova, Italy, 2001
See at:
CNR ExploRA
2007
Conference article
Open Access
A job scheduling framework for large computing farms
Capannini G, Baraglia R, Puppin D, Ricci L, Pasquali MIn this paper, we propose a new method, called Convergent Scheduling, for scheduling a continuous stream of batch jobs on the machines of large-scale computing farms. This method exploits a set of heuristics that guides the scheduler in making decisions. Each heuristics manages a specific problem constraint, and contributes to carry out a value that measures the degree of matching between a job and a machine. Scheduling choices are taken to meet the QoS requested by the submitted jobs, and optimizing the usage of hardware and software resources. We compared it with some of the most common job scheduling algorithms, i.e. Backfilling, and Earliest Deadline First. Convergent Scheduling is able to compute good assignments, while being a simple and modular algorithmDOI: 10.1145/1362622.1362695Metrics:
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www.di.unipi.it
| dl.acm.org
| doi.org
| CNR IRIS
| CNR IRIS
2007
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Backfilling strategies for scheduling streams of jobs on computational farms
Techiouba A, Capannini G, Baraglia R, Puppin D, Pasquali M, Ricci LThis paper presents a set of strategies for scheduling a stream of batch jobs on the machines of a heterogeneous computational farm. Our proposal is based on a flexible backfilling, which schedules jobs according to a priority assigned to each jobs submitted for the execution. Priority values are computed as a result of a set of heuristics whose main goal is both to improve resources utilization and to meet the QoS requirements of the jobs. The heuristics consider the deadlines of the jobs, their estimated execution time and aging in the scheduling queue. Furthermore, the set of software licenses required by a job is also considered. The different proposals have been compared through simulations. Performance figures show the applicability of our approach.
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CNR IRIS
| CNR IRIS
2009
Conference article
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A priority-based multilevel scheduler for batch jobs on grids
Capannini G, Baraglia R, Pasquali M, Ricci L, Laforenza DDuring the last decades, the architectures devoted to the high performance computing changed their shape and structure several times. From the early SMP machines to the Clusters of computers, through the Computational Grids to nowadays Computing Clouds. If on one side this evolution brought to computing platform able to provide several Petaflops, on the other side the increased amount of computing power, obtained through the usage of thousands computer in parallel makes more and more complex an effective and efficient management of resources. In this paper, we propose a multicriteria job scheduler for scheduling a continuous stream of batch jobs on large-scale computing farms, called Convergent Scheduling 2.0 (CS 2.0), which is an enhancement of the scheduler described in [3]. CS 2.0 exploits a set of heuristics that drive the scheduler in taking decisions. Each heuristics manages a specific constraint, and contributes to compute the measurement of the matching degree between a job and a machine. Scheduling choices are taken both to meet the QoS requested by the submitted jobs and to optimize the exploitation of hardware and software resources. In order to validate CS 2.0, we compared it versus two common job scheduling algorithms: Easy and Flexible backfilling. CS 2.0 demonstrated to be able to compute good assignments that allow a better exploitation of resources with respect to the other algorithms.
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CNR IRIS
| CNR IRIS
| puma.isti.cnr.it