Andrea Ribichini

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Data stream processing has recently received increasing attention as a computational paradigm for dealing with massive data sets. Surprisingly, no algorithm with both sublinear space and passes is known for natural graph problems in classical read-only streaming. Motivated by technological factors of modern storage systems, some authors have recently(More)
In this paper we show how parallel algorithms can be turned into efficient streaming algorithms for several classical combinatorial problems in the W-Stream model. In this model, at each pass one input stream is read, one output stream is written, and data items have to be processed using limited space; streams are pipelined in such a way that the output(More)
Dataflow languages provide natural support for specifying constraints between objects in dynamic applications, where programs need to react efficiently to changes in their environment. In this article, we show that one-way dataflow constraints, largely explored in the context of interactive applications, can be seamlessly integrated in any imperative(More)
This thesis studies algorithms for graph problems in a data streaming setting. In its classical form, the Streaming computational model assumes that the input data are presented as a sequential read-only stream, that has to be processed in one or more passes, using a memory that is small compared to the length of the stream. Despite its heavy restrictions,(More)
We introduce and investigate a new notion of resilience in graph spanners. Let $$S$$ S be a spanner of a weighted graph $$G$$ G . Roughly speaking, we say that $$S$$ S is resilient if all its point-to-point distances are resilient to edge failures. Namely, whenever any edge in $$G$$ G fails, then as a consequence of this failure all distances do not degrade(More)
In this report I will focus on the research activity carried on during the first two years of my PhD program, at the University of Rome " La Sapienza " , in the field of massive data sets, with particular emphasis on the streaming computational model: in this model data stored in external memory can be accessed only sequentially, in one or several passes,(More)
In allocation problems, a given set of goods are assigned to agents in such a way that the social welfare is maximized, that is, the largest possible global worth is achieved. When goods are indivisible, it is possible to use money compensation to perform a fair allocation taking into account the actual contribution of all agents to the social welfare.(More)