Class-based Flow Scheduling Framework in SDN-based Data Center Networks
preprintposted on 2020-09-09, 04:50 authored by Maiass Zaher, Aymen AlawadiAymen Alawadi, Sandor Molnar
The emerging technologies leveraging Data Center Networks (DCN) and their consequent trafﬁc patterns impose more necessity for improving Quality of Service (QoS). In this paper, we propose Sieve, a new distributed SDN framework that efﬁciently schedules ﬂows based on the available bandwidth to improve Flow Completion Time (FCT) of mice ﬂows. In addition, we propose a lightweight sampling mechanism to sample a portion of ﬂows. In particular, Sieve schedules the sampled ﬂows, and it reschedules only elephant ﬂows upon threshold hits. Furthermore, our framework allocates a portion of the ﬂows to ECMP, so that the associated overhead can be mitigated in the control plane and ECMP-related packet collisions are fewer as well. Mininet has been used to evaluate the proposed solution, and Sieve provides better FCT up to 50% in comparison to the existing solutions like ECMP and Hedera.