posted on 2025-06-19, 11:16authored byMimi Qian, Lin Cui, Xiaoquan Zhang, Fung Po TsoFung Po Tso, Yuhui Deng, Zhetao Li, Weijia Jia
In programmable networks, measurement tasks are placed on programmable switches to monitor network traffic at line rate. These tasks typically require substantial resources (e.g., significant SRAM), while programmable switches are constrained by limited resources due to their hardware design (e.g., Tofino ASIC), making distributed deployment essentially. Measurement tasks must monitor specific network locations or traffic flows, introducing significant complexity in deployment optimization. This target-constrained nature makes task optimization on switches (e.g., task merging) become device-dependent and order-dependent, which can lead to deployment failures or performance degradation if ignored. In this paper, we introduce DisPLOY, a novel target-constrained distributed deployment framework specifically designed for network measurement tasks on the data plane. DisPLOY enables operators to specify monitoring targets—network traffic or device/link—across multiple switches. Given the monitoring targets, DisPLOY effectively minimizes redundant operations and optimizes deployment to achieve both resource efficiency (e.g., minimizing stage consumption) and high-performance monitoring (e.g., high accuracy). We implement and evaluate DisPLOY through deployment on both P4 hardware switches (Intel Tofino ASIC) and BMv2. Experimental results show that DisPLOY significantly reduces stage consumption by up to 66% and improves ARE by up to 78.4% in flow size estimation while maintaining end-to-end performance.
History
School
Science
Department
Computer Science
Published in
IEEE Transactions on Parallel and Distributed Systems
This accepted manuscript has been made available under the Creative Commons Attribution licence (CC BY) under the IEEE JISC UK green open access agreement.