Congestion control algorithms (CCAs) play a critical role in determining transmission quality. With their rapid evolution during the past few decades, understanding the CCA landscape on the Internet has become increasingly essential for network advancement. Traditional CCA census tools, however, rely heavily on manual configuration and construction, necessitating significant human effort to keep pace with the introduction of new CCAs.

Software Defined Networking (SDN) provides users with a unified abstraction of physical networks. To meet the demands of modern data centers, many works have focused on designing network virtualization hypervisors that support multi-tenant SDN. Ternary Content Addressable Memory (TCAM) is widely used in SDN switches for rule storage. While it has extremely high lookup throughput, it also features drawbacks such as small capacity and slow update speed. Faced with multi-tenant scenarios, its limitations are even more pronounced. Existing hypervisors lack consideration for TCAM isolation, leading to slower TCAM updates and the mutual impact of requests from different tenants. Consequently, they fail to provide guaranteed performance to tenants. To solve these problems, we propose TCAMVisor, which further isolates TCAM resources based on traditional SDN hypervisors. Specifically, TCAMVisor provides better allocation mechanisms for TCAM entry and control bandwidth, ensuring inter-tenant isolation while improving resource utilization. Additionally, TCAMVisor improves the update speed of TCAM by delicately placing tenant rules. To the best of our knowledge, TCAMVisor is the first work to effectively achieve tenant isolation in TCAM, with an average throughput improvement of 5.5 times compared to FlowVisor.

Programmable packet scheduling enables the integration of scheduling algorithms into switches without the need for hardware redesign. The Push-In First-Out (PIFO) queue facilitates a programmable packet scheduler, supporting a single scheduling algorithm flexibly. However, hierarchical scheduling required in Multi-Tenant Data Centers (MTDCs) remains non-programmable. Dynamic and diverse hierarchical scheduling algorithms necessitate alterations in both the number of PIFO queues and their connection topology, posing a significant challenge to support them on fixed hardware.

Ternary Content Addressable Memory (TCAM) is widely used in Software-Defined Networking (SDN) switches due to its impressive throughput. But its unique circuit design results in long and inconsistent update delays. To overcome this challenge, many TCAM update algorithms based on rule semantics have been proposed. These algorithms eliminate unnecessary order restrictions, thus reducing update delays in theory. However, most commodity switches are semantic-unaware, which maintain rules in strict priority order. These algorithms are therefore not available for practical use. To address this issue, this paper proposes Rusen, a framework that enables the use of many semantic-based algorithms on Semantic-unaware commodity switches. Working as a transparent middle layer, the core idea of Rusen is to express the update scheme derived by semantic-based algorithms as messages that the Semantic-unaware switches can execute. In addition, Rusen optimizes the update scheme based on the specific characteristics of each switch, leading to improved performance of these algorithms. We evaluate the performance of Rusen by enabling several state-of-the-art semantic-based algorithms on commodity SDN switches. Results show that the average update delay can be significantly reduced by 23%∼94% on OpenFlow switches and 39%∼84% on a P4 switch.