An efficient iterative source routing algorithm

Finding a feasible path subject to multiple constraints in a network is an NP-complete problem and cannot be solved in polynomial time. Thus, many proposed source routing algorithms tackle this problem by transforming it into the shortest path problem, which is P-complete, with an integrated cost function that maps multi-constraints into a single cost. However, this approach may fail to find a feasible path even when it exists. Some algorithms improve their success ratio of finding a feasible path by performing multiple shortest path searches; each search is associated with a different cost function. Thus, how to vary the cost function is a critical issue for this kind of approach. In this paper, we propose an efficient algorithm to expedite the multiple shortest path searches based on the analysis of the cost function. Simulations show that our algorithm outperforms its contender in terms of computational complexity, and success ratio of finding a feasible path.