Canine Algorithm for Node Disjoint Paths

Node Disjoint Paths (NDP) is one of the extensively studied Graph Theory problem. In this problem, the input is a directed n vertex graph and the set of source destination pair of vertices. The goal is to find the maximum number of paths connecting each such pair, so that such discovered paths are node-disjoint. In this paper, a novel Canine Inspired Algorithm is proposed which is a bio-inspired one, based on the olfactory capabilities of canines in tracing and reaching a destination. Currently many of the existing algorithms try to identify disjoint paths in a linear manner, whereas the Canine algorithm can be executed in a concurrent manner, depending on the number of canines deployed to find the disjoint paths. The time complexity of the algorithm is estimated to be [Formula: see text] . We hope that this algorithm finds many applications in problems related to various fields such as communication networks, scheduling and transportation and provides better results.