In this paper, we present ReQ-tank, an intricate flow scheduling approach based on a multi-level feedback queue. (MLFQ) devised to achieve flow prioritization ...
Experimental results demonstrate that ReQ-tank can curtail packet wait time in the network, significantly truncate the flow completion time (FCT) of ...
In this paper, we present ReQ-tank, an intricate flow scheduling approach based on a multi-level feedback queue (MLFQ) devised to achieve flow prioritization ...
ReQ-tank: Fine-grained Distributed Machine Learning Flow Scheduling Approach. Resource URI: https://dblp.l3s.de/d2r/resource/publications/conf/icpads ...
This paper introduces, Pias, a practical flow scheduling approach that minimizes FCT with no prior knowledge using commodity switches. At its heart, Pias ...
Experiments and simulation results show that RCDRR scheduling algorithm possesses good fairness, low complexity, and r, can reduce the queuing delay of realtime ...
Oct 1, 2024 · ReQ-tank: Fine-grained Distributed Machine Learning Flow Scheduling Approach. ... Scheduling Coflows Based on Deep Reinforcement Learning ...
ReQ-tank: Fine-grained Distributed Machine Learning Flow Scheduling Approach. Authors. Quanyi Xu · Kedong Yan · Dan Yin · Chanying Huang · Shan Xiao · Yuxin ...
An improved token bucket and weighted fair queue (WFQ) scheduling algorithm is proposed that can effectively carry out flow control and flow shaping and ...
ReQ-tank: Fine-grained Distributed Machine Learning Flow Scheduling Approach ... Deep Reinforcement Learning Based Coflow Scheduling in Data Center Networks.