Abstract
In recent years, online data-intensive (OLDI) applications have become particularly common in data center networks (DCNs), such as web search, advertisement systems, and distributed machine learning. OLDI applications have strict latency requirements for short flows and must operate under soft-real-time constraints (e.g., 300 ms latency). On the other hand, there exist long flows that are unaware of flow latency but are sensitive to throughput. Thus, a special transmission protocol that can satisfy different demands for both long flows and short flows is immediately needed. L2DCT is one of the most representative differentiated transmission protocols, which aim at the reduction in completion time for short flows. However, the performance of L2DCT becomes less significant in the scenario where short flows account for the majority (e.g., data mining). For the purposes of minimizing the flow completion time (FCT) of short flows, achieving the minimum average flow completion time (AFCT), and guaranteeing the deadline constraints upon flow transmission times, we propose a cubic acceleration TCP for DCNS, which is referred to as A3DCT.A3DCT employs the Shortest Remaining Process Time (SRPT) scheduling policy to adjust its congestion window according to the remaining bytes of the flow. Moreover, to improve the priority of short flows without affecting the throughput of long flows, A3DCT leverages a cubic function to indicate the urgency of short flows. Finally, A3DCT accelerates the recovery speed, in a flexible manner, depending on the urgency of different flows in a non-congestion state to request the bandwidth to finish transmission. We perform simulations of different scales by using NS-3 simulator to evaluate the performance of A3DCT. The evaluation results justify that A3DCT can not only achieve a low flow completion time, especially for short flows, but also guarantee the high throughput of long flows.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.