Implementating Graph Indexing for Shortest-Path Finding over Dynamic Sub-Graphs

Implementation of dynamic graphs with labeled edges, where the target is to find a shortest path after filtering some edges based on user-specified query labels. This problem is termed the Edge-Constrained Shortest Path query (or ECSP, for short). For this Edge-Disjoint Partitioning, a new technique for efficiently answering ECSP queries over dynamic graphs. EDP has two main components: a dynamic index that is based on graph partitioning, and a traversal algorithm that exploits the regular patterns of the answers of ECSP queries. EDP partitions the graph based on the labels of the edges. On demand, EDP computes specific sub-paths within each partition and updates its index. The computed sub-paths are cached and can be leveraged by future queries. To answer an ECSP query, EDP connects sub-paths from different partitions using its efficient traversal algorithm. EDP can dynamically handle various types of graph updates, e.g., label, edge, and node updates. The index entries that are potentially affected by graph updates are invalidated and are re-computed on demand. EDP is evaluated using real graph datasets like Tiger, BioGrid, BioMine, String, DBLP, Youtube. Implement EDP on Tiger, BioGrid, BioMine, String, DBLP, Youtube. Compare the EDP preprocessing with CHLR preprocessing, compare Query time of EDP with CHLR. Also, implement EDP for non-directed graphs. There is a code for implementation of EDP which applied on 3 datasets in GitHub. Link: [login to view URL]