Online Aggregation of the Forwarding Information Base: Accounting for Locality and Churn - 2018


This Project studies the problem of compressing the forwarding info base (FIB), but taking a wider perspective. Indeed, FIB compression goes beyond sheer compression, because the gain in memory use obtained from the compression has consequences on the updates that will have to be applied to the compressed FIB. We have a tendency to are interested in the case where forwarding rules will change over time, e.g., due to frame gateway protocol (BGP) route updates. Accordingly, we have a tendency to frame FIB compression as an online problem and design competitive on-line algorithms to unravel it. In contrast to prior work which largely centered on static optimizations, we study an on-line variant of the problem where routes will change over time and where the number of updates to the FIB is taken into account explicitly. The reason to consider this version of the matter is that leveraging temporal locality whereas accounting for the number of FIB updates helps to keep routers CPU load low and reduces the number of FIB updates to be transferred, e.g., from the network-connected software-outlined network controller to a distant switch. This Project introduces a formal model that is an interesting generalization of several classic on-line aggregation issues. Our main contribution is an O(w)-competitive algorithm, where w is that the length of an IP address. We also derive a lower certain that shows that our result's asymptotically optimal among a natural category of algorithms, based on so-called sticks.

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