TY - GEN
T1 - FlowMon-DPDK
T2 - 2nd Network Traffic Measurement and Analysis Conference, TMA 2018
AU - Zhang, Tianzhu
AU - Linguaglossa, Leonardo
AU - Gallo, Massimo
AU - Giaccone, Paolo
AU - Rossi, Dario
N1 - Publisher Copyright:
© 2018 IFIP.
PY - 2018/10/23
Y1 - 2018/10/23
N2 - Testing experimental network devices requires deep performance analysis, which is usually performed with expensive, not flexible, hardware equipment. With the advent of highspeed packet I/O frameworks, general purpose equipments have narrowed the performance gap in respect of dedicated hardware and a variety of software-based solutions have emerged for handling traffic at very high speed. While the literature abounds with software traffic generators, existing monitoring solutions do not target worst-case scenarios (i.e., 64B packets at line rate) that are particularly relevant for stress-testing high-speed network functions, or occupy too many resources. In this paper we first analyse the design space for high-speed traffic monitoring that leads us to specific choices characterizing FlowMon-DPDK, a DPDK-based software traffic monitor that we release as an open source project. In a nutshell, FlowMon-DPDK provides tunable fine-grained statistics at both packet and flow levels. Experimental results demonstrate that our traffic monitor is able to provide per-flow statistics with 5-nines precision at high-speed (14.88 Mpps) using an exiguous amount of resources. Finally, we showcase FlowMon-DPDK usage by testing two open source prototypes for stateful flow-level end-host and in-network packet processing.
AB - Testing experimental network devices requires deep performance analysis, which is usually performed with expensive, not flexible, hardware equipment. With the advent of highspeed packet I/O frameworks, general purpose equipments have narrowed the performance gap in respect of dedicated hardware and a variety of software-based solutions have emerged for handling traffic at very high speed. While the literature abounds with software traffic generators, existing monitoring solutions do not target worst-case scenarios (i.e., 64B packets at line rate) that are particularly relevant for stress-testing high-speed network functions, or occupy too many resources. In this paper we first analyse the design space for high-speed traffic monitoring that leads us to specific choices characterizing FlowMon-DPDK, a DPDK-based software traffic monitor that we release as an open source project. In a nutshell, FlowMon-DPDK provides tunable fine-grained statistics at both packet and flow levels. Experimental results demonstrate that our traffic monitor is able to provide per-flow statistics with 5-nines precision at high-speed (14.88 Mpps) using an exiguous amount of resources. Finally, we showcase FlowMon-DPDK usage by testing two open source prototypes for stateful flow-level end-host and in-network packet processing.
UR - https://www.scopus.com/pages/publications/85056453581
U2 - 10.23919/TMA.2018.8506565
DO - 10.23919/TMA.2018.8506565
M3 - Conference contribution
AN - SCOPUS:85056453581
T3 - TMA 2018 - Proceedings of the 2nd Network Traffic Measurement and Analysis Conference
BT - TMA 2018 - Proceedings of the 2nd Network Traffic Measurement and Analysis Conference
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 26 June 2018 through 29 June 2018
ER -