Preemptive Scheduling for Distributed Machine Learning Jobs in Edge-Cloud Networks-Reference-Cited by-同舟云学术

Preemptive Scheduling for Distributed Machine Learning Jobs in Edge-Cloud Networks

Published:2022-08 Issue:8 Volume:40 Page:2411-2425
ISSN:0733-8716
Container-title:IEEE Journal on Selected Areas in Communications
language:
Short-container-title:IEEE J. Select. Areas Commun.

Author:

Wang Ne¹^ORCID,Zhou Ruiting²^ORCID,Jiao Lei³^ORCID,Zhang Renli²^ORCID,Li Bo⁴,Li Zongpeng¹

Affiliation:

1. School of Computer Science, Wuhan University, Wuhan, China

2. School of Computer Science and the Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan, China

3. Department of Computer and Information Science, University of Oregon, Eugene, OR, USA

4. Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong

Funder

NSFC

Hubei Science Foundation

Compact Exponential Algorithm Project of Huawei

Huawei

U.S. National Science Foundation

Research Grant Committee (RGC) Research Impact Fund

RGC General Research Fund (GRF) Grants

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications

Link

https://ieeexplore.ieee.org/ielam/49/9830856/9791406-aam.pdf

Reference46 articles.

1. Aggregated Residual Transformations for Deep Neural Networks

2. A competitive algorithm for minimizing weighted flow time on unrelatedmachines with speed augmentation

3. Minimizing Average Flow-time : Upper and Lower Bounds

4. Non-convex mixed-integer nonlinear programming: A survey

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