Toward Latency‐Efficient Multicast Coflow Scheduling for Reconfigurable Data Center Networks

ABSTRACT The emerging optical circuit technology, which can establish circuit connections among switches, has been proposed as a promising paradigm for data center networks. This paper investigates the problem of minimizing the completion time of multicast coflows in optical circuit switches (OCSs)‐based data center networks. The existing works either only focused on multicast coflow scheduling or focused solely on circuit scheduling in OCS‐based networks, which greatly limits their performance. Hence, in this paper, we study how to reduce the completion time of multicast coflows by considering circuit scheduling and coflow scheduling simultaneously. First, the problem of multicast coflow scheduling is formulated and proved to be NP‐hard. Then, a Delay‐efficient Multicast Coflow Scheduling (DMCS) algorithm is proposed by integrating multicast coflow scheduling with circuit scheduling. The proposed DMCS algorithm is proved to have an approximation ratio of at most , where represents the number of OCS. Through extensive simulations, it is shown that the proposed DMCS algorithm can achieve high performance compared to state‐of‐the‐art methods.

Authors

Institutions

Publication Details

Journal
Concurrency and Computation Practice and Experience
Published
2025-04-09
DOI
https://doi.org/10.1002/cpe.70085
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Toward Latency‐Efficient Multicast Coflow Scheduling for Reconfigurable Data Center Networks

Zhuowei Wang, Yuhang Wu, Yongchao Tao, Quan Chen et al.
Concurrency and Computation Practice and Experience
Cloud Computing and Resource Management
article

Toward Latency‐Efficient Multicast Coflow Scheduling for Reconfigurable Data Center Networks

Zhuowei Wang, Yuhang Wu, Yongchao Tao, Quan Chen, Yuan Chai, F. Li, Fanlong Zhang
article en

Abstract

ABSTRACT The emerging optical circuit technology, which can establish circuit connections among switches, has been proposed as a promising paradigm for data center networks. This paper investigates the problem of minimizing the completion time of multicast coflows in optical circuit switches (OCSs)‐based data center networks. The existing works either only focused on multicast coflow scheduling or focused solely on circuit scheduling in OCS‐based networks, which greatly limits their performance. Hence, in this paper, we study how to reduce the completion time of multicast coflows by considering circuit scheduling and coflow scheduling simultaneously. First, the problem of multicast coflow scheduling is formulated and proved to be NP‐hard. Then, a Delay‐efficient Multicast Coflow Scheduling (DMCS) algorithm is proposed by integrating multicast coflow scheduling with circuit scheduling. The proposed DMCS algorithm is proved to have an approximation ratio of at most , where represents the number of OCS. Through extensive simulations, it is shown that the proposed DMCS algorithm can achieve high performance compared to state‐of‐the‐art methods.

Concurrency and Computation Practice and ExperienceVol. 37(9-11)
Guangdong University of Technology (CN), Shenzhen Academy of Aerospace Technology (CN)
Openalex Percentile: Top 91%
Cloud Computing and Resource Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Toward Latency‐Efficient Multicast Coflow Scheduling for Reconfigurable Data Center Networks — Zhuowei Wang, Yuhang Wu, et al. · Concurrency and Computation Practice and Experience (2025) | TGRS Research Map | TGRS