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Network administrators usually realize network functions in data plane programs. They employ the network-wide program deployment that decomposes input programs into match-action tables (MATs) while deploying each MAT on a specific switch. Since MATs may be deployed on different switches, existing solutions propose the inter-switch coordination that uses the per-packet header space to deliver crucial packet processing information among switches. However, such coordination incurs non-trivial per-packet byte overhead, leading to end-to-end performance degradation. We propose Hermes, a framework that aims to minimize the per-packet byte overhead. The key idea is to formulate network-wide program deployment as a mixed-integer programming (MIP) problem with the objective of minimizing the per-packet byte overhead. Also, Hermes offers a greedy-based heuristic that solves the problem in a near-optimal and timely manner. We have implemented Hermes on Tofino switches. Compared to existing frameworks, Hermes decreases the per-packet byte overhead by 156bytes while preserving end-to-end performance in terms of flow completion time and goodput.

Recent efforts in network measurement place measurement tasks on programmable switches to measure high-speed traffic. These tasks extract flow data, i.e., events, from packets and send events to the control plane. However, the tasks may generate massive events in a short time. In this context, the links transferring events to the control plane and the control plane servers that handle events may be overloaded, i.e., control plane overload. None of existing solutions can eliminate control plane overload. In this paper, we propose MTP, a framework that eliminates control plane overload via careful measurement task placement. Our key idea is to allocate enough resources for each task during task placement to avoid control plane overload at runtime. For each task, MTP estimates its maximum possible rate of sending events to the control plane. Then its optimization framework addresses the resource restrictions of both switches and the control plane. The experiments on Tofino switches indicate that MTP outperforms existing solutions with higher accuracy in several use cases.

Programmable switches empower stateful packet processing, in which incoming packets continuously update states in the data plane, while applications in the control plane read and write states. However, since the data plane and control plane are separated, a consistent view of states in both planes is required for stateful packet processing. Existing approaches suffer from either high latency or low accuracy. In this paper, we propose ApproSync, a framework that offers approximate state synchronization with low latency and high accuracy. To achieve low latency, ApproSync directly transfers states between switch ASICs and the control plane by bypassing switch operating systems. To achieve high accuracy, ApproSync utilizes the resources in the switch ASIC to realize rate control in state synchronization, such that it avoids potential state loss. It also bounds the divergence between the states in the data plane and that in the control plane under limited link capacity. We prototype ApproSync on Barefoot Tofino switches. The experimental results indicate that compared to existing approaches, ApproSync achieves order-of-magnitude latency reduction while maintaining high accuracy of state synchronization. Also, our experiments demonstrate that ApproSync provides significant latency benefits to existing network management applications and well preserves high application-level accuracy.