A theoretical framework for selecting the cost function for source routing

Finding a feasible path subject to multiple constraints in a network is an NP-complete problem and has been extensively studied. Many proposed source routing algorithms tackle this problem by transforming it into the shortest path selection problem, which is P-complete, with an integrated cost function that maps the multi-constraints of each link into a single cost. However, how to select an appropriate cost function is an important issue that has rarely been addressed in literature. In this paper, we provide a theoretical framework for picking a cost function that can improve the performance of source routing in terms of complexity, convergence, and probability of finding a feasible path.