CERI/DIMACS Workshop on Streaming Graph Algorithms (WSGA) - 2014
The Cyber Engineering Research Institute (CERI) of Sandia National Laboratories, partnering with The Center for Discrete Mathematics and Theoretical Computer Science (DIMACS) will host an invitation-only workshop on streaming graph algorithms on Oct. 23-24, 2014.
Streaming analytics process ever-increasing deluges of real-world data to manipulate and filter them at the front end of modern IT systems. Academia and industry alike are faced with the problem of designing algorithms and systems to handle these data streams that feed Big Data systems.
Streaming analytics process ever-increasing deluges of real-world data to manipulate and filter them at the front end of modern IT systems. Academia and industry alike are faced with the problem of designing algorithms and systems to handle these data streams that feed Big Data systems.
Much of the data in these streams is relational and could be modeled using graph edges. However, the field of streaming graph algorithms is quite young. For example, until very recently there was not any theoretical streaming model to deal with infinite versions of edge streams. The research challenges that remain include the design of sampling-based, sub linear algorithms, the design of ‘accretive’ algorithms that store an infinite stream of relations from a finite world of objects, the modeling of temporal graphs, and the design of streaming frameworks to process graph streams.
The emerging field of streaming graph algorithms stands to benefit from interactions between researchers and industry and/or government experts on applications. To this end, the workshop will bring together academics and practitioners in algorithms, systems, and security to share their research accomplishments and identify core streaming graph problems.
Topics of interest include but are not limited to the following:
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Some participant travel support was provided by DIMACS in conjunction with the DIMACS Special Focus on Information Sharing and Dynamic Data Analysis, funded by the National Science Foundation under grant number 1144502 |
Jonathan Berry
jberry@sandia.govRachel Leyba
rleyba@sandia.govPhyllis Rutka
parutka@sandia.gov