A Case for Sampling-Based Learning Techniques in Coflow Scheduling-Reference-Cited by-同舟云学术

A Case for Sampling-Based Learning Techniques in Coflow Scheduling

Author:

Jajoo Akshay¹^ORCID,Hu Y. Charlie²^ORCID,Lin Xiaojun¹^ORCID

Affiliation:

1. Department of Computer Science, Purdue University, West Lafayette, IN, USA

2. Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA

Funder

NSF

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Computer Science Applications,Software

Link

Reference53 articles.

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5. A study on the Morris Worm;jajoo;arXiv 2112 07647,2021

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3. Coflow scheduling in mapreduce framework for cloud data center;MATERIALS V INTERNATIONAL YOUTH APPLIED RESEARCH FORUM “OIL CAPITAL”: Conference Series “OIL CAPITAL”;2023

4. Coflow scheduling with unknown prior knowledge based on traffic characteristics;2022 IEEE Smartworld, Ubiquitous Intelligence & Computing, Scalable Computing & Communications, Digital Twin, Privacy Computing, Metaverse, Autonomous & Trusted Vehicles (SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta);2022-12