Scheduling Coflows in Multi-Core OCS Networks with Performance Guarantee
2026-04-09 • Distributed, Parallel, and Cluster Computing
Distributed, Parallel, and Cluster Computing
AI summaryⓘ
The authors study how to schedule coflows, which are groups of related data flows, in data center networks that use multiple optical circuit switches working at the same time. They focus on a model where changing one circuit doesn't stop others, which creates challenges because flows can move across different switching cores and each core has its own scheduling rules. To solve this, the authors created an algorithm that assigns flows and schedules circuits together to reduce job completion times with guaranteed performance. They tested their approach using real data and found it improves overall and tail completion times compared to previous methods.
coflowdata center networksoptical circuit switchingmulti-core switchingreconfiguration delayflow schedulingapproximation algorithmjob completion timetraffic assignmentpacket switching
Authors
Xin Wang, Hong Shen, Hui Tian, Dong Wang
Abstract
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.