Add to ORKGAbstract. 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 and one output stream is written; streams are pipelined in such a way that the output stream produced at pass i is given as input stream at pass i + 1. Our techniques give new insights on devel-oping streaming algorithms and yield optimal algorithms (up to polylog factors) for several classical problems in this model including sorting, con-nectivity, minimum spanning tree, biconnected components, and maximal independent set.
The semi-streaming model is a variant of the streaming model frequently used for the computation of ...
AbstractWe study a new model of computation, called best-order stream, for graph problems. Roughly, ...
Motivated by the trend to outsource work to commercial cloud computing services, we consider a varia...
In this paper we show how parallel algorithms can be turned into efficient streaming algorithms for ...
In this paper we show how parallel algorithms can be turned into efficient streaming algorithms for ...
AbstractIn this paper we show how parallel algorithms can be turned into efficient streaming algorit...
In this paper we show how PRAM algorithms can be turned into efficient streaming algorithms for seve...
Over the last few years, there has been considerable amount of study and work on developing algorith...
Streaming algorithms, which process very large datasets received one update at a time, are a key too...
In this paper we present the first algorithm to compute the Strongly Connected Components of a graph...
The need to deal with massive data sets in many practical applications has led to a growing interest...
For many algorithmic problems, traditional algorithms that optimise on the number of instructions ex...
www.elsevier.com/locate/tcs We formalize a potentially rich new streaming model, the semi-streaming ...
Over the last decade, there has been considerable in-terest in designing algorithms for processing m...
Over the last decade, there has been considerable in-terest in designing algorithms for processing m...
The semi-streaming model is a variant of the streaming model frequently used for the computation of ...
AbstractWe study a new model of computation, called best-order stream, for graph problems. Roughly, ...
Motivated by the trend to outsource work to commercial cloud computing services, we consider a varia...
In this paper we show how parallel algorithms can be turned into efficient streaming algorithms for ...
In this paper we show how parallel algorithms can be turned into efficient streaming algorithms for ...
AbstractIn this paper we show how parallel algorithms can be turned into efficient streaming algorit...
In this paper we show how PRAM algorithms can be turned into efficient streaming algorithms for seve...
Over the last few years, there has been considerable amount of study and work on developing algorith...
Streaming algorithms, which process very large datasets received one update at a time, are a key too...
In this paper we present the first algorithm to compute the Strongly Connected Components of a graph...
The need to deal with massive data sets in many practical applications has led to a growing interest...
For many algorithmic problems, traditional algorithms that optimise on the number of instructions ex...
www.elsevier.com/locate/tcs We formalize a potentially rich new streaming model, the semi-streaming ...
Over the last decade, there has been considerable in-terest in designing algorithms for processing m...
Over the last decade, there has been considerable in-terest in designing algorithms for processing m...
The semi-streaming model is a variant of the streaming model frequently used for the computation of ...
AbstractWe study a new model of computation, called best-order stream, for graph problems. Roughly, ...
Motivated by the trend to outsource work to commercial cloud computing services, we consider a varia...