An efficient pipeline processing scheme for programming Protocol-independent Packet Processors

OpenFlow is unable to provide customized flow tables, resulting in memory explosions and high switch retirement rates. This is the bottleneck for the development of SDN. Recently, P4 (Programming Protocol-independent Packet Processors) attracts much attentions from both academia and industry. It provides customized networking services by offering flow-level control. P4 can “produce” various forwarding tables according to packets. P4 increases the speed of custom ASICs. However, with the prevalence of P4, the multiple forwarding tables could explode when used in large scale networks. The explosion problem can slow down the lookup speed, which causes congestions and packet losses. In addition, the pipelined structure of forwarding tables brings additional processing delay. In this study, we will improve the lookup performance by optimizing the forwarding tables of P4. Intuitively, we will install the rules according to their popularity, i.e., the popular rules will appear earlier than others. Thus, the packets can hit the matched rule sooner. In this paper, we formalize the optimization problem, and prove that the problem is NP-hard. To solve the problem, we propose a heuristic algorithm called EPSP (Efficient Pipeline Processing Scheme for P4), which can largely reduce the lookup time while keeping the forwarding actions the same. Because running the optimization algorithm frequently brings additional processing burdens, wedesign an incremental update algorithm to alleviate this problem. To evaluate the proposed algorithms, we set up the simulation environments based on ns-3. The simulation results show that the algorithm greatly reduces both the lookup time and the number of memory accesses. The incremental algorithm largely reduces the processing burdens while the lookup time remains almost the same with the non-incremental algorithm. We also implemented a prototype using floodlight and mininet. The results show that our algorithm brings acceptable burder, and performs better than traditional algorithm.