Go-to-Controller is Better: Efficient and Optimal LPM Caching with Splicing.

Modern data center networks are required to support huge and complex forwarding policies as they handle the traffic of the various tenants. However, these policies cannot be stored in their entirety within the limited memory available at commodity switches. The common approach in such scenarios is to have SDN controllers manage the memory available at the switch as a fast cache, updating and changing the forwarding rules in the cache according to the workloads dynamics and the global policy at hand. Many such policies, such as Longest-prefix-match (LPM) policies, introduce dependencies between the forwarding rules. Ensuring that the cache content is always consistent with the global policy often requires the switch to store (potentially many) superfluous rules, which may lead to suboptimal performance in terms of delay and throughput. To overcome these deficiencies, previous work suggested the concept of splicing, where modified Go-to-Controller rules can be inserted into the cache to improve performance while maintaining consistency. These works focused mostly on heuristics, and it was conjectured that the problem is computationally intractable. As our main result, we show that the problem of determining the optimal set of rules, with splicing, can actually be solved efficiently by presenting a polynomial-time algorithm that produces an optimal solution, i.e., for a given cache size we find an optimal set of rules, some of which are go-to-controller, which maximize the total weight of the cache while maintaining consistency. However, such optimality comes at a cost, encompassed by the fact that our algorithm has a significantly larger running time than SoTA solutions which do not employ splicing. Therefore, we further present a heuristic exhibiting close-to-optimal performance, with significantly improved running time, matching that of the best algorithm, which does not employ splicing. In addition, we present the results of an evaluation study that compares the performance of our solutions with that of SoTA approaches, showing that splicing can reduce the cache miss ratio by as much as 30%, without increasing the cache size. Lastly, we propose a simple and fast-to-compute metric (that is consistency-oblivious) in order to evaluate the potential benefits of splicing compared to classical LPM-caching, for a given policy and traffic distribution. We show that our metric is highly correlated with such benefits,