Microscope: Queue-based Performance Diagnosis for Network Functions
Junzhi Gong, Yuliang Li, Bilal Anwer, Aman Shaikh, Minlan Yu
Abstract
By moving monolithic network appliances to software running on commodity hardware, network function virtualization allows flexible resource sharing among network functions and achieves scalability with low cost. However, due to resource contention, network functions can suffer from performance problems that are hard to diagnose. In particular, when many flows traverse a complex topology of NF instances, it is hard to pinpoint root causes for a flow experiencing performance issues such as low throughput or high latency. Simply maintaining resource counters at individual NFs is not sufficient since the effect of resource contention can propagate across NFs and over time. In this paper, we introduce Microscope, a performance diagnosis tool, for network functions that leverages queuing information at NFs to identify the root causes (i.e., resources, NFs, traffic patterns of flows etc.). Our evaluation on realistic NF chains and traffic shows that we can correctly capture root causes behind 89.7% of performance impairments, up to 2.5 times more than the state-of-the-art tools, with very low overhead.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Cited by top-tier papers10
- LightGuardian: A Full-Visibility, Lightweight, In-band Telemetry System Using SketchletsYikai Zhao, Kaicheng Yang, Zirui Liu, Tong Yang et al.NSDI 2021 · 131 citations
- How to diagnose nanosecond network latencies in rich end-host stacksRoni Haecki, Radhika Niranjan Mysore, Lalith Suresh, Gerd Zellweger et al.NSDI 2022 · 58 citations
- Hostping: Diagnosing Intra-host Network Bottlenecks in RDMA ServersKefei Liu, Zhuo Jiang, Jiao Zhang, Haoran Wei et al.NSDI 2023 · 52 citations
- Nuberu: reliable RAN virtualization in shared platformsGines Garcia-Aviles, Andres Garcia-Saavedra, Marco Gramaglia, Xavier Costa-Pérez et al.MobiCom 2021 · 40 citations
- Minder: Faulty Machine Detection for Large-scale Distributed Model TrainingYangtao Deng, Xiang Shi, Zhuo Jiang, Xingjian Zhang et al.NSDI 2025 · 36 citations
Related papers
- Contention-Aware Performance Prediction For Virtualized Network FunctionsAntonis Manousis, Rahul Anand Sharma, Vyas Sekar, Justine SherrySIGCOMM 2020 · 57 citations
- Performance Interfaces for Network FunctionsRishabh R. Iyer, Katerina J. Argyraki, George CandeaNSDI 2022 · 20 citations
- Dyssect: Dynamic Scaling of Stateful Network FunctionsFabrício B. Carvalho, Ronaldo A. Ferreira, Ítalo Cunha, Marcos A. M. Vieira et al.INFOCOM 2022 · 10 citations
- Automatic Parallelization of Software Network FunctionsFrancisco Pereira, Fernando M. V. Ramos, Luis PedrosaNSDI 2024 · 14 citations
- Non-invasive performance prediction of high-speed softwarized network services with limited knowledgeQiong Liu, Tianzhu Zhang, Leonardo LinguaglossaINFOCOM 2024 · 2 citations
