Salvato in:
| Autori principali: | , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2509.07338 |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866911144151613440 |
|---|---|
| author | Dai, Yuanjun Guo, Qingzhe Wang, Xiangren |
| author_facet | Dai, Yuanjun Guo, Qingzhe Wang, Xiangren |
| contents | Sketch-based monitoring in SDN often suffers from tightly coupled pipeline and memory constraints, limiting algorithmic flexibility and reducing accuracy. We propose PSketch, the first in-kernel priority-aware sketching framework implemented with eBPF. It ensures lossless tracking of high-priority flows via a hash-based table and approximates top-k elephant flows using a sketch pipe. PSketch supports both TCP and UDP and enables in-kernel retransmission tracking with minimal overhead. Unlike SDN-based approaches, it runs on commodity Linux systems, removing hardware dependencies. We perform evaluation on 10 Gbps CAIDA traces. Results show that PSketch achieves 96.0% top-k detection accuracy, 96.4% retransmission recall, and only 0.7% throughput degradation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_07338 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | PSketch: A Priority-Aware Sketch Architecture for Real-Time Flow Monitoring via eBPF Dai, Yuanjun Guo, Qingzhe Wang, Xiangren Emerging Technologies Sketch-based monitoring in SDN often suffers from tightly coupled pipeline and memory constraints, limiting algorithmic flexibility and reducing accuracy. We propose PSketch, the first in-kernel priority-aware sketching framework implemented with eBPF. It ensures lossless tracking of high-priority flows via a hash-based table and approximates top-k elephant flows using a sketch pipe. PSketch supports both TCP and UDP and enables in-kernel retransmission tracking with minimal overhead. Unlike SDN-based approaches, it runs on commodity Linux systems, removing hardware dependencies. We perform evaluation on 10 Gbps CAIDA traces. Results show that PSketch achieves 96.0% top-k detection accuracy, 96.4% retransmission recall, and only 0.7% throughput degradation. |
| title | PSketch: A Priority-Aware Sketch Architecture for Real-Time Flow Monitoring via eBPF |
| topic | Emerging Technologies |
| url | https://arxiv.org/abs/2509.07338 |