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Nianbing Yu

dblp:299/2216 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2022
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 2 · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
2 papers
Cloud and datacenter computing · 61% Interconnection networks and networks-on-chip · 20% Hardware accelerators and domain-specific architectures · 20%
Computer networks
2 papers
Software-defined and programmable networks · 74% Transport protocols and congestion control · 26%

Topics — the 7 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Interconnection networks and networks-on-chip › flow control
backpressure
0.612022
MIMIC: SmartNIC-aided Flow Backpressure for CPU Overloading Protection in Multi-Tenant Clouds · ICNP 2022
Cloud and datacenter computing › multi-tenancy
multi-tenant cloud
0.612022
MIMIC: SmartNIC-aided Flow Backpressure for CPU Overloading Protection in Multi-Tenant Clouds · ICNP 2022
Cloud and datacenter computing › virtualization › network virtualization
network function virtualization
0.612022
MIMIC: SmartNIC-aided Flow Backpressure for CPU Overloading Protection in Multi-Tenant Clouds · ICNP 2022
Hardware accelerators and domain-specific architectures › network accelerator
SmartNIC
0.612022
MIMIC: SmartNIC-aided Flow Backpressure for CPU Overloading Protection in Multi-Tenant Clouds · ICNP 2022
Software-defined and programmable networks
programmable data plane
0.512021
Sailfish: accelerating cloud-scale multi-tenant multi-service gateways with programmable switches · SIGCOMM 2021
Cloud and datacenter computing › cloud networking
cloud gateway
0.512021
Sailfish: accelerating cloud-scale multi-tenant multi-service gateways with programmable switches · SIGCOMM 2021
Transport protocols and congestion control
explicit congestion notification
0.212022
MIMIC: SmartNIC-aided Flow Backpressure for CPU Overloading Protection in Multi-Tenant Clouds · ICNP 2022

Methods — techniques the papers use, named apart from their topics

pre-filtering · 1.1hierarchical memory design · 1.1FPGA acceleration · 1.1table splitting · 1.0table compression · 1.0hardware-software co-design · 1.0
YearPublicationVenuePosition
2022 MIMIC: SmartNIC-aided Flow Backpressure for CPU Overloading Protection in Multi-Tenant Clouds
abstract
In multi-tenant clouds, off-the-shelf x86 boxes are widely deployed as middleboxes. With the rapid growth of cloud traffic and the migration to NFV deployment in recent years, CPU overloading at middleboxes becomes more of an issue. From our data centers, we observed that the CPU overloading was caused by heavy hitters. To address this issue, we propose MIMIC, a cloud-scale flow backpressure system, implemented onto our existing SmartNIC with FPGA acceleration. MIMIC rate-limits the selected heavy hitters through a new per-flow backpressure protocol and a new heavy-hitter detection system, to protect the other tenants. The detection system is based on hierarchical memory design, leveraging on-chip SRAM and off-chip DRAM, which can handle highly concurrent cloud traffic without the losses of flow information. We extend the design by adding a pre-filtering procedure for rapid detection. To avoid CPU being flooded by FPGA through frequent heavy-hitter reporting, due to their performance disparity, the CPU queries the FPGA on demand. The backpressure protocol is non-invasive to protect tenant privacy and allows controllable rate-limiting through the novel use of ECN and meter tables. The SmartNIC acts as a man in the middle to facilitate heavy-hitter detection and per-flow backpressuring. In a production setting, we observe that MIMIC can react quickly and bring down CPU load to the normal level within 10ms without packet losses.
Enge Song, Nianbing Yu, Tian Pan 0001, Qiang Fu 0011, Xionglie Wei, Yisong Qiao, Jianyuan Lu, Yijian Dong, Mingxu Xie, Jinkui Mao, Zhengjie Luo, Chenhao Jia, Jiao Zhang 0002, Tao Huang 0005, Biao Lyu, Shunmin Zhu
ICNP2
2021 Sailfish: accelerating cloud-scale multi-tenant multi-service gateways with programmable switches
abstract
The cloud gateway is essential in the public cloud as the central hub of cloud traffic. We show that horizontal scaling of software gateways, once sustainable for years, is no longer future-proof facing the massive scale and rapid growth of today's cloud. The root cause is the stagnant performance of the CPU core, which is prone to be overloaded by heavy hitters as traffic growth goes far beyond Moore's law. To address this, we propose \emph{Sailfish}, a cloud-scale multi-tenant multi-service gateway accelerated by programmable switches. The new challenge is that large forwarding tables due to multi-tenancy cannot be fit into the limited on-chip memories. To this end, we devise a multi-pronged approach with (1) hardware/software co-design for table sharing, (2) horizontal table splitting among gateway clusters, (3) pipeline-aware table compression for a single node. Compared with the x86 gateway of a similar price, Sailfish reduces latency by 95% (2μs), improves throughput by more than 20x in bps (3.2Tbps) and 71x in pps (1.8Gpps) with packet length < 256B. Sailfish has been deployed in Alibaba Cloud for more than two years. It is the first P4-based cloud gateway in the industry, of which a single cluster carries dozens of Tbps traffic, withstanding peak-hour traffic in large online shopping festivals.
Tian Pan 0001, Nianbing Yu, Chenhao Jia, Jianwen Pi, Yisong Qiao, Jianyuan Lu, Enge Song, Jiao Zhang 0002, Tao Huang 0005, Shunmin Zhu
SIGCOMM2