Graph Storage and Processing

We develop systems and algorithms for large scale graph processing and explore novel applications for graph-structured data.

Smooth Kronecker Generator

As there are a dearth of truly large, publicly available data sets, synthetic graph generators are critical for evaluating the scalability of graph processing systems. We introduced the Smooth Kronecker generator, which produces Kronecker graphs whose fundamental graph characteristics, such as degree distribution, better reflect real world data.

  1. [Smooth Kronecker: Solving the Combing Problem in Kronecker Graphs ]
  1. [Smooth Kronecker Repository]
On-Going Work
  1. Developing high-performance storage structures to facilitate both point queries and large-scale analytics.
  2. Building frameworks that allow such systems to adapt to variations in hardware platform, workload, and input data.
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Systopia lab is supported by a number of government and industrial sources, including Cisco Systems, the Communications Security Establishment Canada, Intel Research, the National Sciences and Engineering Research Council of Canada (NSERC), Network Appliance, Office of the Privacy Commissioner of Canada, and the National Science Foundation (NSF).