TY - GEN
T1 - Adaptive path tracing with programmable bloom filters in software-defined networks
AU - Xiong, Sisi
AU - Cao, Qing
AU - Si, Weisheng
PY - 2019
Y1 - 2019
N2 - One critical challenge of managing modern data center networks lies in that existing network protocols provide limited visibility on the internal routing and forwarding decisions made by the control plane, leading to difficulties on fast diagnosis and identification of root causes for performance bugs and anomalies. In this paper, we develop and evaluate a 'debugging mode' for packet forwarding, where we demonstrate a possible design space by introducing a programmable header field into data packets used for diagnosis purposes. These headers can be manipulated by routers in intermediate hops to perform tracing and diagnosis operations, thereby providing much greater visibility on the control plane and data plane operations. To make this design scalable and feasible, we exploit the software APIs provided by the latest software-defined networking (SDN) technologies, where the network control plane is separated from the underlying data plane, so that we can reprogram the network forwarding functions dynamically. Compared to existing alternative approaches, our approach is adaptive and programmable, allowing dynamic and on-demand receiver-side decoding with extremely low overhead. We emphasize that as this 'debugging mode' can be enabled and disabled by network managers as demanded, it introduces zero overhead to normal traffic if everything is operating as expected. Our evaluation results on a real SDN network testbed demonstrate the effectiveness of the proposed approaches.
AB - One critical challenge of managing modern data center networks lies in that existing network protocols provide limited visibility on the internal routing and forwarding decisions made by the control plane, leading to difficulties on fast diagnosis and identification of root causes for performance bugs and anomalies. In this paper, we develop and evaluate a 'debugging mode' for packet forwarding, where we demonstrate a possible design space by introducing a programmable header field into data packets used for diagnosis purposes. These headers can be manipulated by routers in intermediate hops to perform tracing and diagnosis operations, thereby providing much greater visibility on the control plane and data plane operations. To make this design scalable and feasible, we exploit the software APIs provided by the latest software-defined networking (SDN) technologies, where the network control plane is separated from the underlying data plane, so that we can reprogram the network forwarding functions dynamically. Compared to existing alternative approaches, our approach is adaptive and programmable, allowing dynamic and on-demand receiver-side decoding with extremely low overhead. We emphasize that as this 'debugging mode' can be enabled and disabled by network managers as demanded, it introduces zero overhead to normal traffic if everything is operating as expected. Our evaluation results on a real SDN network testbed demonstrate the effectiveness of the proposed approaches.
KW - computer network protocols
KW - data centers
KW - packet switching (data transmission)
KW - performance
KW - visibility
UR - http://handle.westernsydney.edu.au:8081/1959.7/uws:52402
U2 - 10.1109/INFOCOM.2019.8737387
DO - 10.1109/INFOCOM.2019.8737387
M3 - Conference Paper
SN - 9781728105154
SP - 496
EP - 504
BT - Proceedings IEEE INFOCOM 2019: IEEE Conference on Computer Communications, 29 April-2 May 2019, Paris, France
PB - IEEE
T2 - IEEE Conference on Computer Communications
Y2 - 29 April 2019
ER -