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Main Authors: Wang, Xin, Shen, Hong, Tian, Hui, Wang, Dong
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2604.08242
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author Wang, Xin
Shen, Hong
Tian, Hui
Wang, Dong
author_facet Wang, Xin
Shen, Hong
Tian, Hui
Wang, Dong
contents Coflow provides a key application-layer abstraction for capturing communication patterns, enabling the efficient coordination of parallel data flows to reduce job completion times in distributed systems. Modern data center networks (DCNs) are employing multiple independent optical circuit switching (OCS) cores operating concurrently to meet the massive bandwidth demands of application jobs. However, existing coflow scheduling research primarily focuses on the single-core setting, with multi-core fabrics only for EPS (electrical packet switching) networks. To address this gap, this paper studies the coflow scheduling problem in multi-core OCS networks under the not-all-stop reconfiguration model in which one circuit's reconfiguration does not interrupt other circuits. The challenges stem from two aspects: (i) cross-core coupling induced by traffic assignment across heterogeneous cores; and (ii) per-core OCS scheduling constraints, namely port exclusivity and reconfiguration delay. We propose an approximation algorithm that jointly integrates cross-core flow assignment and per-core circuit scheduling to minimize the total weighted coflow completion time (CCT) and establish a provable worst-case performance guarantee. Furthermore, our algorithm framework can be directly applied to the multi-core EPS scenario with the corresponding approximation ratio under packet-switched fabrics. Trace-driven simulations using real Facebook workloads demonstrate that our algorithm effectively reduces weighted CCT and tail CCT.
format Preprint
id arxiv_https___arxiv_org_abs_2604_08242
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Scheduling Coflows in Multi-Core OCS Networks with Performance Guarantee
Wang, Xin
Shen, Hong
Tian, Hui
Wang, Dong
Distributed, Parallel, and Cluster Computing
Coflow provides a key application-layer abstraction for capturing communication patterns, enabling the efficient coordination of parallel data flows to reduce job completion times in distributed systems. Modern data center networks (DCNs) are employing multiple independent optical circuit switching (OCS) cores operating concurrently to meet the massive bandwidth demands of application jobs. However, existing coflow scheduling research primarily focuses on the single-core setting, with multi-core fabrics only for EPS (electrical packet switching) networks. To address this gap, this paper studies the coflow scheduling problem in multi-core OCS networks under the not-all-stop reconfiguration model in which one circuit's reconfiguration does not interrupt other circuits. The challenges stem from two aspects: (i) cross-core coupling induced by traffic assignment across heterogeneous cores; and (ii) per-core OCS scheduling constraints, namely port exclusivity and reconfiguration delay. We propose an approximation algorithm that jointly integrates cross-core flow assignment and per-core circuit scheduling to minimize the total weighted coflow completion time (CCT) and establish a provable worst-case performance guarantee. Furthermore, our algorithm framework can be directly applied to the multi-core EPS scenario with the corresponding approximation ratio under packet-switched fabrics. Trace-driven simulations using real Facebook workloads demonstrate that our algorithm effectively reduces weighted CCT and tail CCT.
title Scheduling Coflows in Multi-Core OCS Networks with Performance Guarantee
topic Distributed, Parallel, and Cluster Computing
url https://arxiv.org/abs/2604.08242