Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Digital Object Identifier (DOI) : 10.14569/IJACSA.2013.040902
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 4 Issue 9, 2013.
Abstract: Graphs are used in diverse set of disciplines ranging from computer networks to biological networks, social networks, World Wide Web etc. With the advancement in the technology and the discovery of new knowledge, size of graphs is increasing exponentially. A graph containing millions of nodes and billions of edges can be of size in TBs. At the same time, the size of graphs presents a big obstacle to understand the essential information they contain. Also with the current size of main memory it seems impossible to load the whole graph into main memory. Hence the need of graph compression techniques arises. In this paper, we present graph compression technique which partition graphs into subgraphs and then each partition can be compressed individually. For partitioning, proposed approach identifies weak links present in the graph and partition graph at those weak links. During query processing, the partitions which are required need to be decompressed, eliminating decompression of whole graph.
Meera Dhabu, Dr. P. S. Deshpande and Siyaram Vishwakarma, “Partition based Graph Compression” International Journal of Advanced Computer Science and Applications(IJACSA), 4(9), 2013. http://dx.doi.org/10.14569/IJACSA.2013.040902