2010/04/16 by Graham Cormode, Michael Mitzenmacher, Cormode, Graham +3
Computer Science · #Complexity and Algorithms in Graphs #Privacy-Preserving Technologies in Data #Distributed systems and fault tolerance
paper · pdf · doi:10.48550/arxiv.1004.2899
Motivated by the trend to outsource work to commercial cloud computing services, we consider a variation of the streaming paradigm where a streaming algorithm can be assisted by a powerful helper that can provide annotations to the data stream. We extend previous work on such \em annotation models by considering a number of graph streaming problems. Without annotations, streaming algorithms for graph problems generally require significant memory; we show that for many standard problems, including all graph problems that can be expressed with totally unimodular integer programming formulations, only a constant number of hash values are needed for single-pass algorithms given linear-sized annotations. We also obtain a protocol achieving optimal tradeoffs between annotation length and memory usage for matrix-vector multiplication; this result contributes to a trend of recent research on numerical linear algebra in streaming models.