Routing protocols present a convergence latency for all routers to update their tables after a fault occurs and the network topology changes. During this time interval, which in the Internet has been shown to be of up to minutes, packets may be lost before reaching their destinations. In order to allow nodes to continue communicating during the convergence latency interval, we propose the use of alternative routes called detours. In this work we introduce new criteria for selecting detours based on network connectivity. Detours are chosen without the knowledge of which node or link is faulty. Highly connected components present a larger number of distinct paths, thus increasing the probability that the detour will work correctly. Experimental results were obtained with simulation on random Internet-like graphs generated with the Waxman method. Results show that the fault coverage obtained through the usage of the best detour is up to 90%. When the three best detours are considered, the fault coverage is up to 98%.

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We consider the problem of fitting an n x n distance matrix D by a tree metric T. This problem is NP-hard for most reasonable distance functions between D and T. Recently, an approximation algorithm was presented (Agarwala et al., 1996) which achieves a factor of 3 approximation to the L infinity best fitting tree. We call this method the Single Pivot (SP) heuristic. Within the biology community, the so-called Neighbor-Joining (NJ) heuristic (Saitou and Nei, 1987) has wide acceptance. In this paper, we introduced a new Double Pivot (DP) heuristic, which is an extension of the SP heuristic, and show that DP outperforms NJ on biological and random data.

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