Optimal and heuristic algorithms for quality-of-service routing with multiple constraints

The multi-constrained path (MCP) selection problem occurs when the quality-of-services (QoS) are supported for point-to-point connections in the distributed multimedia applications deployed on the Internet. This NP-complete problem is concerned about how to determine a feasible path between two given end-points, so that a set of QoS path constraints can be satisfied simultaneously. Based on the branch-and-bound technique and tabu-searching strategy, an optimal algorithm and a tabu-search based heuristic are developed in this paper for solving the MCP problem with multiple constraints. The experimental results show that our tabu-search based heuristic not only outperforms the previous method published in literature, but also demonstrates that it is indeed a highly efficient method for solving the MCP problem in large-scale networks.