Network Services Management using Programmable Data Planes for Visual Cloud Computing
Alicia Esquivel Morel, Prasad P. Calyam, Chengyi Qu, Durbek Gafurov, Cong Wang, Komal Thareja, Anirban Mandal, Eric Lyons, Michael Zink, George Papadimitriou, Ewa Deelman · 2023
Visual Cloud Computing (VCC) applications provide highly efficient solutions in video data processing pipelines on edge/cloud infrastructures. These applications and their infrastructures demand end-to-end monitoring and fine-grained application traffic control to meet user quality of experience requirements. In this paper, we propose a novel network services management methodology for VCC applications by leveraging the advantages of programmable data planes enabled by Protocol-independent Packet Processors (P4). Specifically, we define a custom fixed-length application header and use it to improve the performance of a video streaming application through congestion avoidance using Multi-Hop Route Inspection (MRI), a variant of In-band Network Telemetry (INT), and switch port forwarding (tunneling) capabilities. For evaluation experiments, we use P4 per-packet telemetry metadata for routing paths, ingress/egress timestamps, queue occupancy in a given node, and egress port link utilization in a VCC testbed on the NSF-supported FABRIC infrastructure. Our experiment results demonstrate performance improvement obtained with our methodology in terms of both packet loss and throughput metrics.