← Search

Julong Lan

3 accepted papers

2020

DeepWeave: Accelerating Job Completion Time with Deep Reinforcement Learning-based Coflow Scheduling

IJCAI 2020poster

To improve the processing efficiency of jobs in distributed computing, the concept of coflow is proposed. A coflow is a collection of flows that are semantically correlated in a multi-stage computation task. A job consists of multiple coflows and can be usually formulated as a Directed-Acyclic Graph…

Cited by 0SourcePDFScholar
2020

Improving the Scalability of Deep Reinforcement Learning-Based Routing with Control on Partial Nodes

ICASSP 2020accepted

Machine Learning (ML)-based routing optimization has been proposed to optimize the performance of flow routing for future networks, such as Software-Defined Networks (SDNs). However, existing studies are either hard to converge for large networks or vulnerable to topology changes. In this paper, we…

Cited by 0SourceScholar
2020

QOS-Aware Flow Control for Power-Efficient Data Center Networks with Deep Reinforcement Learning

ICASSP 2020accepted

Reducing the power consumption and maintaining the Flow Completion Time (FCT) for the Quality of Service (QoS) of applications in Data Center Networks (DCNs) are two major concerns for data center operators. However, existing works either fail in guaranteeing the QoS due to the neglect of the FCT co…

Cited by 0SourceScholar