Layer-4 load balancers are a popular solution to high tail latencies but perform poorly under unpredictable skewed workloads because they statically assign connections to servers. We present Capybara, a new load balancer architecture that enables dynamic rebalancing of established connections. Capybara divides load balancing responsibility into a fast L4 load balancer, a host-switch co-designed connection migration protocol, and a transport interface for application-level connection state migration. Capybara leverages two trends - programmable switches and kernel-bypass - to efficiently implement connection migration without disruption, while maintaining transparency to clients. Under realistic workloads, Capybara achieves up to 149× lower tail latency and more than 2× higher throughput for scale-out services compared to state-of-the-art load balancing approaches.

Middleboxes are becoming indispensable in modern networks. However, programming the network stack of middleboxes to support emerging transport protocols and flexible stack hierarchy is still a daunting task. To this end, we propose Rubik, a language that greatly facilitates the task of middlebox stack programming. Different from existing hand-written approaches, Rubik offers various high-level constructs for relieving the operators from dealing with massive native code, so that they can focus on specifying their processing intents. We show that using Rubik one can program the middlebox stack with minor effort, e.g., 250 lines of code for a complete TCP/IP stack, which is a reduction of 2 orders of magnitude compared to the hand-written versions. To maintain a high performance, we conduct extensive optimizations at the middle-and back-end of the compiler. Experiments show that the stacks generated by Rubik outperform the mature hand-written stacks by at least 30% in throughput.

Mission critical systems deployed in data centers today are facing more sophisticated failures. Byzantine fault-tolerant (BFT) protocols are capable of masking these types of failures, but are rarely deployed due to their performance cost and complexity. In this work, we propose a new approach to designing high performance BFT protocols in data centers. By re-examining the ordering responsibility between the network and the BFT protocol, we advocate a new abstraction offered by the data center network infrastructure. Concretely, we design a new authenticated ordered multicast primitive (aom) that provides transferable authentication and non-equivocation guarantees. Feasibility of the design is demonstrated by two hardware implementations of aom- one using HMAC and the other using public key cryptography for authentication - on new-generation programmable switches. We then co-design a new BFT protocol, NeoBFT, that leverages the guarantees of aom to eliminate cross-replica coordination and authentication in the common case. Evaluation results show that NeoBFT outperforms state-of-the-art protocols on both latency and throughput metrics by a wide margin, demonstrating the benefit of our new network ordering abstraction for BFT systems.

Network programming languages (NPLs) empower operators to program network data planes (NDPs) with unprecedented efficiency. Currently, various NPLs and NDPs coexist and no one can prevail over others in the short future. Such diversity is raising many problems including: (1) programs written with different NPLs can hardly interoperate in the same network, (2) most NPLs are bound to specific NDPs, hindering their independent evolution, and (3) compilation techniques cannot be readily reused, resulting in much wasteful work. These problems are mostly owing to the lack of modularity in the compilers, where the missing part is an intermediate representation (IR) for NPLs. To this end, we proposeNetwork Transaction Automaton (NTA), a highly-expressive and language-independent IR, and show it can express semantics of 7 mainstream NPLs. Then, we designCODER, a modular compiler based on NTA, which currently supports 2 NPLs and 3 NDPs. Experiments with real and synthetic programs show CODER can correctly compile those programs for real networks within moderate time.

Network programming languages (NPLs) empower operators to program network data planes (NDPs) with unprecedented efficiency. Currently, various NPLs and NDPs coexist and no one can prevail over others in the short future. Such diversity is raising many problems including: (1) programs written with different languages can hardly interoperate in the same network, and (2) most NPLs are bound to specific NDPs, hindering their independent evolution. These problems are mostly owing to the lack of modularity in the compilers, where the missing part is an intermediate representation (IR) for NPLs. To this end, we propose Network Transaction Automaton (NTA), a highly-expressive and language-independent representation as the IR. We show that NTA can express semantics of 6 mainstream NPLs, and can be composed efficiently without any semantics loss.

Network programming languages (NPLs) empower operators to program network data planes (NDPs) with unprecedented efficiency. Currently, various NPLs and NDPs coexist and no one can prevail over others in the short future. Such diversity is raising many problems including: (1) programs written with different NPLs can hardly interoperate in the same network, (2) most NPLs are bound to specific NDPs, hindering their independent evolution, and (3) compilation techniques cannot be readily reused, resulting in much wasteful work. These problems are mostly owing to the lack of modularity in the compilers, where the missing part is an intermediate representation (IR) for NPLs. To this end, we propose Network Transaction Automaton (NTA), a highly-expressive and language-independent IR, and show it can express semantics of 7 mainstream NPLs. Then, we design CODER, a modular compiler based on NTA, which currently supports 2 NPLs and 3 NDPs. Experiments with real and synthetic network programs show CODER is efficient and scalable.