Journal article
Recorp: Receiver-oriented Policies for Industrial Wireless Networks
ACM transactions on sensor networks, Vol.17(4), pp.1-32
07/22/2021
DOI: 10.1145/3460618
Appears in UI Libraries Support Open Access
Abstract
Future Industrial Internet-of-Things (IIoT) systems will require wireless solutions to connect sensors, actuators, and controllers as part of high data rate feedback-control loops over real-time flows. A key challenge in such networks is to provide predictable performance and adaptability in response to link quality variations. We address this challenge by developing RECeiver ORiented Policies (Recorp), which leverages the stability of IloT workloads by combining offline policy synthesis and run-time adaptation. Compared to schedules that service a single flow in a slot, Recorp policies share slots among multiple flows by assigning a coordinator and a list of flows that may be serviced in the same slot. At run-time, the coordinator will execute one of the flows depending on which flows the coordinator has already received. A salient feature of Recorp is that it provides predictable performance: a policy meets the end-to-end reliability and deadline of flows when the link quality exceeds a user-specified threshold. Experiments show that across IIoT workloads, policies provided a median increase of 50% to 142% in real-time capacity and a median decrease of 27% to 70% in worst-case latency when schedules and policies are configured to meet an end-to-end reliability of 99%.
Details
- Title: Subtitle
- Recorp: Receiver-oriented Policies for Industrial Wireless Networks
- Creators
- Ryan Brummet - University of IowaMd Kowsar Hossain - University of IowaOctav Chipara - University of IowaTed Herman - University of IowaDavid E Stewart - Mathematics
- Resource Type
- Journal article
- Publication Details
- ACM transactions on sensor networks, Vol.17(4), pp.1-32
- Publisher
- Association for Computing Machinery (ACM)
- DOI
- 10.1145/3460618
- ISSN
- 1550-4859
- eISSN
- 1550-4867
- Number of pages
- 32
- Grant note
- CNS-1750155 / NSF; National Science Foundation (NSF)
- Language
- English
- Date published
- 07/22/2021
- Academic Unit
- Internal Medicine; Mathematics; Computer Science
- Record Identifier
- 9984240773002771
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