Semi-Streaming Algorithms for Annotated Graph Streams
Justin Thaler

TL;DR
This paper introduces semi-streaming annotation schemes for graph problems, enabling efficient verification of complex properties like triangle counting and maximum matching in massive graphs, surpassing limitations of traditional semi-streaming algorithms.
Contribution
It proposes the semi-streaming annotation schemes model, demonstrating its advantages for certain problems and limitations for others compared to the standard semi-streaming model.
Findings
Semi-streaming annotation schemes solve triangle counting and maximum matching.
Some problems like connectivity and bipartiteness remain hard in the annotation model.
The model offers a more robust framework for graph streaming computations.
Abstract
Considerable effort has been devoted to the development of streaming algorithms for analyzing massive graphs. Unfortunately, many results have been negative, establishing that a wide variety of problems require space to solve. One of the few bright spots has been the development of semi-streaming algorithms for a handful of graph problems -- these algorithms use space . In the annotated data streaming model of Chakrabarti et al., a computationally limited client wants to compute some property of a massive input, but lacks the resources to store even a small fraction of the input, and hence cannot perform the desired computation locally. The client therefore accesses a powerful but untrusted service provider, who not only performs the requested computation, but also proves that the answer is correct. We put forth the notion of semi-streaming…
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Taxonomy
TopicsComplexity and Algorithms in Graphs · Distributed systems and fault tolerance · Cryptography and Data Security
