---
res:
  bibo_abstract:
  - Data-parallel applications run on cluster of servers in a datacenter and their
    communication triggers correlated resource demand on multiple links that can be
    abstracted as coflow. They often desire predictable network performance, which
    can be passed to network via coflow abstraction for application-aware network
    scheduling. In this paper, we propose a heuristic and an optimization algorithm
    for predictable network performance such that they guarantee coflows completion
    within their deadlines. The algorithms also ensure high network utilization, i.e.,
    it's work-conserving, and avoids starvation of coflows. We evaluate both algorithms
    via trace-driven simulation and show that they admit 1.1x more coflows than the
    Varys scheme while meeting their deadlines.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Asif
      foaf_name: Hasnain, Asif
      foaf_surname: Hasnain
      foaf_workInfoHomepage: http://www.librecat.org/personId=63288
  - foaf_Person:
      foaf_givenName: Holger
      foaf_name: Karl, Holger
      foaf_surname: Karl
      foaf_workInfoHomepage: http://www.librecat.org/personId=126
  bibo_doi: https://doi.org/10.1109/CCGrid49817.2020.00010
  dct_date: 2020^xs_gYear
  dct_language: eng
  dct_publisher: IEEE Computer Society@
  dct_subject:
  - Coflow
  - Scheduling
  - Deadlines
  - Data centers
  dct_title: Coflow Scheduling with Performance Guarantees for Data Center Applications@
...