Our new paper has been accepted to appear at the ACM/IEEE Symposium on Edge Computing (SEC ‘20). This paper, “Pub/Sub in the Air: A Novel Data-centric Radio Supporting Robust Multicast in Edge Environments,” was co-authored with Stony Brook PhD student Mohammed Elbadry and Professors Fan Ye and Yuanyuan Yang.
Abstract: Peer communication among edge devices (e.g., mobiles, vehicles, IoT and drones) is frequently data-centric: most important is obtaining data of desired content from suitable nodes; who generated or transmitted the data matters much less. Typical cases are robust one-to-many data sharing: e.g., a vehicle sending weather, road, position and speed data streams to nearby cars continuously. Unfortunately, existing address-based wireless communication is ill-suited for such purposes.
We propose V-MAC, a novel data-centric radio that provides a pub/sub abstraction to replace the point-to-point abstraction in existing radios. It filters frames by data names instead of MAC addresses, thus eliminating complexities and latencies in neighbor discovery and group maintenance in existing radios. V-MAC supports robust, scalable and high rate multicast with consistently low losses across receivers of varying reception qualities. Experiments using a Raspberry Pi and commodity WiFi dongle based prototype show that V-MAC reduces loss rate from WiFi broadcast’s 50–90% to 1–3% for up to 15 stationary receivers, 4–5 moving people, and miniature and real vehicles. It cuts down filtering latency from 20us in WiFi to 10us for up to 2 million data names, and improves cross stack latency 60–100× for TX/RX paths. We have ported V-MAC to 4 major WiFi chipsets (including 802.11 a/b/g/n/ac radios), 6 different platforms (Android, embedded and FPGA systems), 7 Linux kernel versions, and validated up to 900Mbps multicast data rate and interoperation with regular WiFi. We will release V-MAC as a mature, reusable asset for edge computing research.
This entry was posted on August 07, 2020.