Paper Info
Title
QCluster: Clustering Packets for Flow Scheduling
Abstract
ABSTRACTFlow scheduling is crucial in data centers, as it directly influences user experience of applications. According to different assumptions and design goals, there are four typical flow scheduling problems/solutions: SRPT, LAS, Fair Queueing, and Deadline-Aware scheduling. When implementing these solutions in commodity switches with limited number of queues, they need to set static parameters by measuring traffic in advance, while optimal parameters vary across time and space. This paper proposes a generic framework, namely QCluster, to adapt all scheduling problems for limited number of queues. The key idea of QCluster is to cluster packets with similar weights/properties into the same queue. QCluster is implemented in Tofino switches, and can cluster packets at a speed of 3.2 Tbps. To the best of our knowledge, QCluster is the fastest clustering algorithm. Experimental results in testbed with programmable switches and ns-2 show that QCluster reduces the average flow completion time (FCT) for short flows up to 56.6%, and reduces the overall average FCT up to 21.7% over state-of-the-art. All the source code in ns-2 is available in Github [45].
Year
DOI
Venue
2022
10.1145/3485447.3511980
International World Wide Web Conference
Keywords
DocType
Citations 
Datacenter Networks, Flow Scheduling, Queue Clustering
Conference
0
PageRank 
References 
Authors
0.34
0
8
Name
Order
Citations
PageRank
Tong Yang120837.35
Jin Li283.38
Yikai Zhao321.75
Kaicheng Yang401.35
Hao Wang569632.07
jie jiang68310.90
Yinda Zhang771.44
Nicholas Zhang800.68