ENHANCING THE EFFICACY OF PROGRAMMABLE NETWORKS

Abstract

This thesis aims to optimize the design of datacenter networks by improving network telemetry, stateful network functions, and network load balancing using high-speed programmable switches. Our approach involves identifying and addressing bottlenecks and inefficiencies by incorporating switching architecture, hardware resources, interfaces, and traffic patterns into the design. First, we introduce a novel data structure called FCM-Sketch, which supports high resolution, generality, and scaling with the switching fabric throughput at the same time. Next, we develop DySO, a system that executes control actions through the high-speed data-path instead of using the switch's slow control channel. DySO enables quick retrieval of the network telemetry and responsiveness to network changes. Lastly, we present ConWeave, a network load balancing framework for the emerging transport mechanism in data centers, remote direct memory access (RDMA). It provides a fine-grained network load balancing while masking the adverse effects of rerouting (e.g., out-of-order packet arrivals) using programmable switches.