Subjective-cost policy routing

We study a model of path-vector routing in which nodes’ routing policies are based on subjective cost assessments of alternative routes. The routes are constrained by the requirement that all routes to a given destination must be confluent. We show that it is NP-hard to determine whether there is a set of stable routes. We also show that it is NP-hard to find a set of confluent routes that minimizes the total subjective cost; it is hard even to approximate the minimum cost closely. These hardness results hold even for very restricted classes of subjective costs.We then consider a model in which the subjective costs are based on the relative importance nodes place on a small number of objective cost measures. We show that a small number of confluent routing trees is sufficient for each node to have a route that nearly minimizes its subjective cost. We show that this scheme is trivially strategy proof and that it can be computed easily with a distributed algorithm. Furthermore, we prove a lower bound on the number of trees required to contain a (1+ϵ)-approximately optimal route for each node and show that our scheme is nearly optimal in this respect.