Compressing sparse graphs to speed up Dijkstra’s shortest path algorithm
Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
One of the problems that arises from the continuously growing amount of data is that it slows down and limits the uses of large graphs in real world situations. Because of this, studies are being done to investigate the possibility of compressing data in large graphs. This report presents an investigation on the usefulness of compressing sparse graphs and then applying Dijkstra’s shortest path algorithm. A minimal spanning tree algorithm was used to compress a graph and compared with a self-implemented compression algorithm. The minimal distances and how long time it takes for Dijkstra's algorithm to find the shortest path between nodes are investigated.
The results show that it is not worth compressing the type of sparse graphs used in this study. It is hard to compress the graph without losing too much of the edges that preserve the shortest paths. The time gained when running Dijkstra's algorithm on the compressed graphs is not enough to compensate for the lack of getting a good shortest path solution.
Place, publisher, year, edition, pages
IdentifiersURN: urn:nbn:se:kth:diva-166730OAI: oai:DiVA.org:kth-166730DiVA: diva2:812016
Na Nongkai, Danupon