English

DCoflow: Deadline-Aware Scheduling Algorithm for Coflows in Datacenter Networks

Distributed, Parallel, and Cluster Computing 2022-05-04 v1 Networking and Internet Architecture

Abstract

Datacenter networks routinely support the data transfers of distributed computing frameworks in the form of coflows, i.e., sets of concurrent flows related to a common task. The vast majority of the literature has focused on the problem of scheduling coflows for completion time minimization, i.e., to maximize the average rate at which coflows are dispatched in the network fabric. Modern applications, though, may generate coflows dedicated to online services and mission-critical computing tasks which have to comply with specific completion deadlines. In this paper, we introduce DCoflow\mathtt{DCoflow}, a lightweight deadline-aware scheduler for time-critical coflows in datacenter networks. The algorithm combines an online joint admission control and scheduling logic and returns a σ\sigma-order schedule which maximizes the number of coflows that attain their deadlines. Extensive numerical results demonstrate that the proposed solution outperforms existing ones.

Keywords

Cite

@article{arxiv.2205.01229,
  title  = {DCoflow: Deadline-Aware Scheduling Algorithm for Coflows in Datacenter Networks},
  author = {Quang-Trung Luu and Olivier Brun and Rachid El-Azouzi and Francesco De Pellegrini and Balakrishna J. Prabhu and Cédric Richier},
  journal= {arXiv preprint arXiv:2205.01229},
  year   = {2022}
}

Comments

Accepted to IFIP Networking 2022 (Catania, Italy)

R2 v1 2026-06-24T11:05:23.705Z