Title
Unbiased Quantized Congestion Notification for Scalable Server Fabrics.
Abstract
Ethernet is the predominant layer-2 networking technology in the datacenter, and it is evolving into an economical alternative for high-performance computing clusters. Ethernet traditionally drops packets in the event of congestion, but IEEE introduced lossless class services to enable the convergence of storage and IP networks. Losslessness is a simple, well-known concept, but its application in datacenters is hampered by the fear of ensuing saturation trees. In this article, the authors aim to accelerate the deployment of Quantized Congestion Notification (QCN). In particular, they first eliminate the intrinsic unfairness of QCN under typical fan-in scenarios by installing the congestion points at inputs, instead of at outputs as standard QCN does. They then demonstrate that QCN at input buffers cannot always discriminate between culprit and victim flows. To overcome this limitation, they propose a novel QCN-compatible marking scheme called "occupancy sampling." They have implemented these methods in a server-rack fabric with 640 100-Gigabit Ethernet ports.
Year
DOI
Venue
2016
10.1109/MM.2015.131
IEEE Micro
Keywords
Field
DocType
Ethernet,Telecommunication traffic,Throughput,Ports (Computers),Telecommunication network management,Congestion control,Telecommunication traffic
Convergence (routing),Computer science,Parallel computing,Network packet,Server,Computer network,ATA over Ethernet,Real-time computing,Ethernet,Network congestion,Throughput,Scalability
Journal
Volume
Issue
ISSN
36
6
0272-1732
Citations 
PageRank 
References 
0
0.34
0
Authors
8
Name
Order
Citations
PageRank
Nikolaos Chrysos1608.56
Fredy D. Neeser2152.69
R. Clauberg352.29
Daniel Crisan4494.24
Kenneth M. Valk5112.27
Claude Basso6626.85
Cyriel Minkenberg739939.21
Mitchell Gusat815816.23