Towards An Adaptive Time-Triggered Protocol in Wireless Networks
Jin Zhang, Fan Liang, Wei Yu, David W. Griffith, Wenqi Guo, Avi Gopstein
Time sensitive activities occur extensively in industrial Internet of Things (IoT) environments. Classical time-triggered protocols in wired networks, such as Ethernet, have been proven effective in supporting real-time and safety-critical communications. Along with the increasing use of wireless devices, designing wireless network protocols that handle the delivery of time-sensitive activities becomes an important issue. Unlike the Time-Triggered Ethernet (TTE) protocol designed for wired networks, a time-triggered protocol tailored to wireless networks faces a number of barriers, such as unstable data transmission under high radio interference, high bit error rate, and limited computation and storage capabilities on IoT devices. In this paper, we introduce an Adaptive Time-Triggered Protocol (ATTP) for wireless networks. In particular, we design a dynamic repetition scheme that transmits replicated copies of one time-triggered data packet to ensure the reliability and low latency of data transmission. To minimize the overhead raised by the replication of packets, we dynamically select the necessary number of replicated copies according to the instantaneous quality of the connection link. To effectively utilize wireless resources, we also design a multi-class traffic scheduling scheme to handle three traffic types, time-triggered (TT) traffic that requires an absolute latency guarantee, event-triggered (ET) traffic that requires a relatively low latency guarantee, and best-effort (BE) traffic without any latency guarantee requirement. Via an extensive simulation study, we validate the effectiveness of our approach, achieving expected performance for time-triggered traffic with respect to latency, packet loss ratio, and overhead reduction.
, Liang, F.
, Yu, W.
, Griffith, D.
, Guo, W.
and Gopstein, A.
Towards An Adaptive Time-Triggered Protocol in Wireless Networks, 2021 IEEE Smart World Congress, Atlanta, GA, US, [online], https://doi.org/10.1109/SWC50871.2021.00091, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=931904
(Accessed December 5, 2022)