7,189 research outputs found

    Efficient Subgraph Matching on Billion Node Graphs

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    The ability to handle large scale graph data is crucial to an increasing number of applications. Much work has been dedicated to supporting basic graph operations such as subgraph matching, reachability, regular expression matching, etc. In many cases, graph indices are employed to speed up query processing. Typically, most indices require either super-linear indexing time or super-linear indexing space. Unfortunately, for very large graphs, super-linear approaches are almost always infeasible. In this paper, we study the problem of subgraph matching on billion-node graphs. We present a novel algorithm that supports efficient subgraph matching for graphs deployed on a distributed memory store. Instead of relying on super-linear indices, we use efficient graph exploration and massive parallel computing for query processing. Our experimental results demonstrate the feasibility of performing subgraph matching on web-scale graph data.Comment: VLDB201

    Second Set of Spaces

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    This document describes the Gloss infrastructure supporting implementation of location-aware services. The document is in two parts. The first part describes software architecture for the smart space. As described in D8, a local architecture provides a framework for constructing Gloss applications, termed assemblies, that run on individual physical nodes, whereas a global architecture defines an overlay network for linking individual assemblies. The second part outlines the hardware installation for local sensing. This describes the first phase of the installation in Strathclyde University
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