Data Locality in Graph Databases through N-Body Simulation by Dominic Pacher, Robert Binna, and Günther Specht.
Data locality poses a major performance requirement in graph databases, since it forms a basis for efficient caching and distribution. This vision paper presents a new approach to satisfy this requirement through n-body simulation. We describe our solution in detail and provide a theoretically complexity estimation of our method. To prove our concept, we conducted an evaluation using the DBpedia dataset data. The results are promising and show that n-body simulation is capable to improve data locality in graph databases significantly.
My first reaction was why clustering of nodes wasn’t compared to n-body simulation? That seems like an equally “natural” method to achieve data locality.
My second reaction was that the citation of “…Simulations of the formation, evolution and clustering of galaxies and quasars. nature, 435(7042):629–636, jun 2005. (citation 16 in the article) was reaching in terms of support for scaling. That type of simulation involves a number of simplifying assumptions that aren’t likely to be true for most graphs.
Imaginative work but it needs a little less imagination and a bit rigor in terms of its argument/analysis.