BPP: Large Graph Storage for Efficient Disk-Based Processing

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Provided by: Kyung Hee University
Topic: Storage
Format: PDF
Graph processing has been a popular research area in the last decade and a lot of research has been targeted at the most common graph processing algorithms such as shortest path and some variations of clustering and page rank. Processing very large graphs like social networks, biological and chemical compounds are a challenging task. Distributed graph processing systems process the billion-scale graphs efficiently but incur overheads of efficient partitioning and distribution of the graph over a cluster of nodes. Distributed processing also requires cluster management and fault tolerance. In order to overcome these problems GraphChi was proposed recently. GraphChi significantly outperformed all the representative distributed processing frameworks.
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