Path diversification for future internet end-to-end resilience and survivability

Path Diversification is a new mechanism that can be used to select multiple paths between a given ingress and egress node pair using a quantified diversity measure to achieve maximum flow reliability. The path diversification mechanism is targeted at the end-to-end layer, but can be applied at any level for which a path discovery service is available. Path diversification also takes into account service requirements for low-latency or maximal reliability in selecting appropriate paths. Using this mechanism will allow future internetworking architectures to exploit naturally rich physical topologies to a far greater extent than is possible with shortest-path routing or equal-cost load balancing. We describe the path diversity metric and its application at various aggregation levels, and apply the path diversification process to 13 real-world network graphs as well as 4 synthetic topologies to asses the gain in flow reliability. Based on the analysis of flow reliability across a range of networks, we then extend our path diversity metric to create a composJ. P. Rohrer* E-mail: [email protected] Tel.: +1 831 656 3196 Computer Science Department, Naval Postgraduate School Monterey, California, USA A. Jabbar* E-mail: [email protected] Advanced Communication Systems Lab, GE Global Research Niskayuna, New York, USA J. P. G. Sterbenz E-mail: jpgs@{ittc.ku.edu|comp.lancs.ac.uk} Tel.: +1 785 864 7890 Information and Telecommunication Technology Center, The University of Kansas Lawrence, Kansas, USA and Lancaster University, Lancaster, UK * Work performed while at The University of Kansas ite compensated total graph diversity metric that is representative of a particular topology’s survivability with respect to distributed simultaneous link and node failures. We tune the accuracy of this metric having simulated the performance of each topology under a range of failure severities, and present the results. The topologies used are from nationalscale backbone networks with a variety of characteristics, which we characterize using standard graph-theoretic metrics. The end result is a compensated total graph diversity metric that accurately predicts the survivability of a given network topology.