<br> <img src="images/poster-logo-small.png" alt="G* ICDE Poster Logo" width="600px"> <div class="navbar navbar-fixed-top"> <div class="navbar-inner"> <div class="container"> <div id="nav" class="brand" style="float:left; vertical-align:middle; line-height:36px;"> The G* Research Group </div> <div id="nav" class="brand" style="float:right;"> <a href="http://www.cs.albany.edu/~gstar/" class="btn btn-small" style="width:110px;">Home</a> <a href="http://www.cs.albany.edu/~gstar/publications" class="btn btn-small" style="width:110px;">Publications</a> <a href="http://www.cs.albany.edu/~gstar/quick-start-guide" class="btn btn-small" style="width:110px;">Quick Start Guide</a> <a href="http://www.cs.albany.edu/~gstar/operator-reference" class="btn btn-small" style="width:110px;">Operator Reference</a> <a href="http://www.cs.albany.edu/~gstar/request-form" class="btn btn-small" style="width:110px;">Request Form</a> </div> </div> </div> </div> From sensor networks to transportation infrastructure to social networks, we are awash in data. Whether it's analyzing sensor data, making maps, or making recommendations from Facebook activity, many of these real-world networks tend to be large ("big data") and dynamic, evolving over time ("long data"). Their evolution can be modeled as a series of graphs. Traditional systems that store and analyze one graph at a time cannot effectively handle the complexity and subtlety inherent in dynamic graphs. Modern analytics require systems capable of storing and processing series of graphs. We present such a system: G&#42;. <img style="float:right;" src="images/SUNY-Albany.png" alt="SUNY Albany, New York, USA" width="200" height="200"> <div style="width:80%"> Pronounced "jee star", our system compresses dynamic graph data based on commonalities among the graphs in the series for deduplicated storage on multiple servers. In addition to the obvious space-saving advantage, large-scale graph processing tends to be I/O bound, so faster reads from and writes to stable storage enables faster results. Unlike traditional database and graph processing systems, G&#42; executes complex queries on large graphs using distributed operators to process graph data in parallel. It speeds up queries on multiple graphs by processing graph commonalities only once and sharing the results across relevant graphs. <!-- This architecture not only provides scalability, but since G&#42; is not limited to processing only what is available in RAM, its analysis capabilities are far greater than other systems which are limited to what they can hold in memory. --> </div> G&#42; consists of the following components: * the Master that controls the entire system * one or more Workers that manage distributed graph data * one or more interactive Terminals that connect to the Master ### Sponsorship <table style="border:none; position:relative; top:-40px;"> <tr> <td style="background-color:white; border:none;"> <img src="images/NSF.png" alt="National Science Foundation" width="388" height="67"> </td> <td style="background-color: white; border:none; vertical-align:middle;"> This work is supported by the National Science Foundation <br> under [CAREER Award IIS-1149372](http://www.nsf.gov/awardsearch/showAward?AWD_ID=1149372 "NSF CAREER Award"). </td> </tr> <tr> <td colspan="2" style="background-color: white; border:none; vertical-align:middle;"> <img src="images/logo-kisti.jpg" alt="logo-kisti" width="377" height="78"> </td> </tr> </table> <img style="float:right;" src="images/exposure.png" alt="G* Around the World" width="500"> ### For more about G&#42;, please read the following: * [The G&#42; Quick Start Guide](http://www.cs.albany.edu/~gstar/quick-start-guide "G* Quick Start Guide") * [The G&#42; Operator Reference](http://www.cs.albany.edu/~gstar/operator-reference "G* Operator Reference") * [A Demonstration of the G&#42; Graph Database System](http://www.cs.albany.edu/~gstar/docs/gstar-ICDE-2013.pdf "G* ICDE 2013 Demo Paper") from ICDE 2013 * [G&#42; Overview Poster](http://www.cs.albany.edu/~gstar/docs/gstar-poster-ICDE-2013.pdf "G* ICDE 2013 Poster") from ICDE 2013 * [Scalable and Robust Management of Dynamic Graph Data](http://www.cs.albany.edu/~gstar/docs/gstar-VLDB-BD3-2013.pdf "VLDB BD3 2013 Paper") from VLDB BD3 2013 <br> ### Try G&#42; yourself . . . * [. . . by submitting a request form.](http://www.cs.albany.edu/~gstar/request-form "Request G*") <br> ### The G&#42; Team <ul> <li> Faculty <ul> <li><a href="http://www.cs.albany.edu/~jhh/Site/Welcome.html">Jeong-Hyon Hwang</a></li> </ul> </li> <li> Ph.D. Students <ul> <li><a href="http://www.albany.edu/~jb196286/">Jeremy Birnbaum</a></li> <li><a href="https://www.linkedin.com/in/aparnanj">Aparna Joshi</a></li> </ul> </li> <li> Alums <ul> <li><a href="http://www.labouseur.com">Alan G. Labouseur</a>, Marist College</li> <li><a href="https://careers.stackoverflow.com/paulolsen">Paul W. Olsen Jr.</a>, The College of Saint Rose</li> </ul> </li> </ul>

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