Software-defined networking has been developing in recent years and the separation of the control plane and the data plane has made networks more flexible. Due to its flexibility, the software method is used to implement the data plane. However, with increasing network speed, the CPU is becoming unable to meet the requirements of high-speed packet processing. FPGAs are usually used as dumb switches to accelerate the data plane, with all intelligence centralized in the remote controller. However, the cost of taking the intelligence out of the switch is the increased latency between the controller and the switch. Therefore, we argue that the control decisions should be made as locally as possible. In this paper, we propose a novel architecture with high performance and flexibility for accelerating SDN based on the MPSoC platform. The control plane is implemented in the on-chip CPU and the data plane is implemented in the FPGA logic. The communication between the two components is performed using Ethernet communication. We design a high-performance TCAM based on distributed RAM. The architecture employs a pipeline design with modules connected via the AXI Stream interface. The designed architecture is flexible enough to support multiple network functions while achieving high performance at 100 Gbps. As far as we know, the architecture is the first proposed in the design of a 100 Gbps system.

Network monitoring is important to improve network performance and security. The separation of the data plane and the control plane of SDN gives the network flexibility. This flexibility facilitates network management and gives rise to the need for accurate and fine-grained management of networks. However, the traditional software-based flow monitoring cannot easily keep up with today’s high-speed networks such as 100 GbE, even with the help of high-performance frameworks such as DPDK. To meet the need for fine-grained management of high-speed networks, an accurate hardware-based flow monitor design is presented in this paper. In our design, the FPGA-based pipelined cuckoo hashing is used to achieve efficient storage of flow entries. The flow information is accurately recorded without any sampling. The proposed design can achieve a higher performance than the non-sketch CPU-based methods and higher accuracy than sketch methods. Compared with other state-of-the-art flow monitors, the proposed design can achieve a performance of 100 Gbps while maintaining high accuracy.

In order to facilitate the transition between networks and the integration of heterogeneous networks, the underlying link design of the current mainstream Information-Centric Networking (ICN) still considers the characteristics of the general network and extends the customized ICN protocol on this basis. This requires that the network transmission equipment can not only distinguish general network packets but also support the identification of ICN-specific protocols. However, traditional network protocol parsers are designed for specific network application scenarios, and it is difficult to flexibly expand new protocol parsing rules for different ICN network architectures. For this reason, we propose a general dynamic extensible protocol parser deployed on FPGA, which supports the real-time update of network protocol parsing rules by configuring extended protocol descriptors. At the same time, the multi-queue protocol management mechanism is adopted to realize the grouping management and rapid parsing of the extended protocol. The results demonstrate that the method can effectively support the protocol parsing of 100 Gbps high-speed network data packets and can dynamically update the protocol parsing rules under ultra-low latency. Compared with the current commercial programmable network equipment, this solution improves the protocol update efficiency by several orders of magnitude and better supports the online updating of network equipment.