Network monitoring systems are designed to fulfill operators’ intents and serve as essential tools to modern networks. As a result of rapidly increasing network bandwidth and scale nowadays, network monitors should satisfy on-demand network monitoring for continuously growing traffic volumes. However, existing monitoring systems either cannot satisfy flexible intents on demand or produce significant overheads. In this paper, we presentNewton, an intent-driven traffic monitor that is able to specify operators’ intents with traffic monitoring queries and conduct dynamic and scalable network-wide queries deployment.Newtonenables operators to customize and modify queries dynamically without interrupting the network workflow. Besides,Newtonproposes systematic optimizations at device level and network-wide level to reduce resource consumption while deploying queries.Newtoncan combine the resources across switches to deploy complex queries with high resilience to dynamic network status. Evaluations prove thatNewtonis of high flexibility, scalability, and resource efficiency, which demonstratesNewtonis promising to be deployed in large-scale programmable networks.

Modern network devices and systems are raising higher requirements on network testers that are regularly used to evaluate performance and assess correctness. These requirements include high scale, high accuracy, flexibility and low cost, which existing testers cannot fulfill at the same time. In this paper, we propose HyperTester, a network tester leveraging new-generation programmable switches and achieving all of the above goals simultaneously. Programmable switches are born with features like high throughput and linerate, deterministic processing pipelines and nanosecond-level hardware timestamps, the P4 programming model as well as comparable pricing with commodity servers, but they come with limited programmability and memory resources. HyperTester uses template-based packet generation to overcome the limitations of the switch ASIC in programmability and designs a stateless connection mechanism as well as counter-based state compression algorithms to overcome the memory resource constraints in the data plane. We have implemented HyperTester on Tofino, and the evaluations on the hardware testbed show that HyperTester supports high-scale packet generation (more than 1.6Tbps) and achieves highly accurate rate control and timestamping. We demonstrate that programmable switches can be potential and attractive targets for realizing network testers.

Modern network research and operations are inseparable from network testers to evaluate performance limits of proofs-of-concept, troubleshoot failures, etc. Existing network testers suffer from either constrained flexibility or a low performance-cost ratio. In this paper, we propose a new network tester, HyperTester. The core of HyperTester is to leverage new-generation programmable switches for generating and capturing test traffic with high performance, low cost, and remarkable flexibility. We design a series of efficient mechanisms, including template-based packet generation, false-positive-free counter-based queries, and stateless connections to realize various network testing tasks upon switches with limited programmability and resources. Meanwhile, to facilitate developing testing tasks upon HyperTester, we provide a high-level network testing API. We have implemented HyperTester on the Tofino switch and built dozens of network testing tasks. The evaluations on the hardware testbed show that HyperTester supports line-rate packet generation (400Gbps in the testbed) with highly-accurate rate control, while HyperTester can save $40150 per Tps and 9225W per Tbps when compared with the software network testers.

P4 and programmable data planes bring significant flexibility to network operation but are inevitably prone to various faults. Some faults, like P4 program bugs, can be verified statically, while some faults, like runtime rule faults, only happen to running network devices, and they are hardly possible to handle before deployment. Existing network testing systems can troubleshoot runtime rule faults via injecting probes, but are insufficient for programmable data planes due to large overheads or limited fault coverage. In this paper, we propose P4Tester, a new network testing system for troubleshooting runtime rule faults on programmable data planes. First, P4Tester proposes a new intermediate representation based on Binary Decision Diagram, which enables efficient probe generation for various P4-defined data plane functions. Second, P4Tester offers a new probe model that uses source routing to forward probes. This probe model largely reduces rule fault detection overheads, i.e. requiring only one server to generate probes for large networks and minimizing the number of probes. Moreover, this probe model can test all table rules in a network, achieving full fault coverage. Evaluation based on real-world data sets indicates that P4Tester can efficiently check all rules in programmable data planes, generate 59% fewer probes than ATPG and Pronto, be faster than ATPG by two orders of magnitude, and troubleshoot multiple rule faults within one second on BMv2 and Tofino.