A Study to Handle Dynamic Graph Partitioning

Abstract

Large dynamic graphs are popular and are used in areas like social sites, bio-informatics etc. Huge memory is required to load large graph. Therefore partitioning of large graphs is important in graph analysis. Dynamic updating of the graph can be done with different sub graphs of a large dynamic graph. Different methods of partitioning worked on static graphs. New methods of partitioning can be achieved through combinations of available methods. The proposed work will analyze the large dynamic graph by partitioning it. Also the system will update graph when multiple nodes and edges will be inserted or deleted at runtime. Certain works also focus on generating overlapped nodes in sub graphs. A method to represent large graph in abstract view is also be proposed.