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Citation  In Proc. of the International Colloquium on Automata, Languages and Programming (ICALP) 2004.

Authors  Joan Feigenbaum
Sampath Kannan Andrew McGregor Siddharth Suri Jian Zhang 
We formalize a potentially rich new streaming model, the semistreaming model, that we believe is necessary for the fruitful study of efficient algorithms for solving problems on massive graphs whose edge sets cannot be stored in memory. In this model, the input graph, G = (V,E), is presented as a stream of edges (in adversarial order), and the storage space of an algorithm is bounded by O(n polylog n), where n = V. We are particularly interested in algorithms that use only one pass over the input, but, for problems where this is provably insufficient, we also look at algorithms using constant or, in some cases, logarithmically many passes. In the course of this general study, we give semi streaming constant approximation algorithms for the unweighted and weighted matching problems, along with a further algorithmic improvement for the bipartite case. We also exhibit log n/ log log n semistreaming approximations to the diameter and the problem of computing the distance between specified vertices in a weighted graph. These are complemented by \omega(log^{1\epsilon}n) lower bounds.