TY - GEN
T1 - Pub/Sub in the Air
T2 - 5th IEEE/ACM Symposium on Edge Computing, SEC 2020
AU - Elbadry, Mohammed
AU - Ye, Fan
AU - Milder, Peter
AU - Yang, Yuanyuan
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/11
Y1 - 2020/11
N2 - 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 a 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 20μs in WiFi to 10\mu s 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.
AB - 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 a 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 20μs in WiFi to 10\mu s 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.
KW - data-centric networks
KW - MAC protocol
KW - multicast
KW - Wireless edge Communication
UR - https://www.scopus.com/pages/publications/85102193610
U2 - 10.1109/SEC50012.2020.00038
DO - 10.1109/SEC50012.2020.00038
M3 - Conference contribution
AN - SCOPUS:85102193610
T3 - Proceedings - 2020 IEEE/ACM Symposium on Edge Computing, SEC 2020
SP - 257
EP - 270
BT - Proceedings - 2020 IEEE/ACM Symposium on Edge Computing, SEC 2020
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 11 November 2020 through 13 November 2020
ER -