SDN Soft Computing Application for Detecting Heavy Hitters

Abstract

To avoid distributed denial-of-service (DDoS) attacks or real-time transmission control protocol (TCP) incast in the software-defined networking (SDN) environment, the HashPipe algorithm was developed following the space-saving approach. Unfortunately, HashPipe implemented in the behavioral model (bmv2) cannot be directly executed at a real programming protocol-independent packet processor (P4) switch due to P4 pipeline limitation. Based on the Banzai machine model, this paper shows how to smartly utilize the Banzai atoms to develop HashPipe as a soft computing application in a real P4 switch. Then we propose an enhanced HashPipe algorithm that significantly improves the accuracy of the original HashPipe. The proposed heavy hitter detection is executed at the line-rate of the Tofino P4 switch with the highest process rate in the world.