Andrea Pietracaprina

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Motivated by the growing interest in mobile systems, we study the dynamics of information dissemination between agents moving independently on a plane. Formally, we consider <i>k</i> mobile agents performing independent random walks on an <i>n</i>-node grid. At time 0, each agent is located at a random node of the grid and one agent has a rumor. The spread(More)
We study the use of sampling for efficiently mining the top-K frequent itemsets of cardinality at most w. To this purpose, we define an approximation to the top-K frequent itemsets to be a family of itemsets which includes (resp., excludes) all very frequent (resp., very infrequent) itemsets, together with an estimate of these itemsets' frequencies with a(More)
We present a constructive deterministic simulation of a PRAM with <italic>n</italic> processors and <italic>m</italic> = <italic>n</italic> <supscrpt>&#945;</supscrpt> shared variables, 1 &lt; &#945; &#8804; 2, on an <italic>n</italic>-node mesh-connected computer where each node hosts a processor and a memory module. At the core of the simulation is a(More)
This paper surveys and places into perspective a number of results concerning the D-BSP (Decomposable Bulk Synchronous Parallel) model of computation , a variant of the popular BSP model proposed by Valiant in the early nineties. D-BSP captures part of the proximity structure of the computing platform , modeling it by suitable decompositions into clusters,(More)
This work explores fundamental modeling and algorithmic issues arising in the well-established MapReduce framework. First, we formally specify a computational model for MapReduce which captures the functional flavor of the paradigm by allowing for a flexible use of parallelism. Indeed, the model diverges from a traditional processor-centric view by(More)
As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is becoming a major challenge in data mining applications. In this work, we address significance in the context of frequent itemset mining. Specifically, we develop a novel methodology(More)
In this work we study the issue of performance prediction on the SGI-Power Challenge, a typical representative of the class of shared-memory Symmetric MultiProcessors. On such a platform, the cost of memory accesses varies depending on their locality and on contention among processors. By running a carefully designed suite of microbenchmarks, we provide(More)