Hybrid Flow Table Installation: Optimizing Remote Placements of Flow Tables on Servers to Enhance PDP Switches for In-Network Computing

Abstract

Recently, the programmable data plane (PDP) switches have been considered as the key enablers for in-network computing. However, the limited memory resources in them for flow tables might restrict their performance. This work addresses this challenge by studying how to optimize the placements of flow tables in the external memory on multiple servers, and to access them with remote direct memory access (RDMA) for ensuring low latency. Specifically, we consider a data-center network (DCN) that uses PDP switches as top-of-rack (ToR) switches, and propose and optimize the hybrid flow table installation (hFT-INST) on each ToR switch. With hFT-INST, the switch can either store flow tables in its local memory or use RDMA to install and access them remotely in its rack servers. We first design the protocol and operation procedure of hFT-INST. Then, regarding the key problem of hFT-INST, i.e., how to place the flow tables on the external memory on different servers, we take a few practical parameters into account, and formulate a mixed integer linear programming (MILP) model to tackle it. Next, the optimization in the MILP is transformed into a capacitated facility location problem (CFLP) with additional constraints. We further transform it into a ${k}$ -median problem through pre-processing, and design a polynomial-time approximation algorithm to solve the problem. Extensive simulations confirm the performance of our proposed algorithm. We also prototype our design of the hFT-INST, and conduct experiments to demonstrate its feasibility.