Loureiro, Joao, Rangarajan, Raghuraman, Nikolic, Borislav et al. (2 more authors) (2019) Extensive Analysis of a Real-Time Dense Wired Sensor Network Based on Traffic Shaping. ACM Transactions on Cyber-Physical Systems. 27. ISSN 2378-9638
Abstract
XDense is a novel wired 2D mesh grid sensor network system for application scenarios that benefit from densely deployed sensing (e.g., thousands of sensors per square meter). It was conceived for cyber-physical systems that require real-time sensing and actuation, like active flow control on aircraft wing surfaces. XDense communication and distributed processing capabilities are designed to enable complex feature extraction within bounded time and in a responsive manner. In this article, we tackle the issue of deterministic behavior of XDense. We present a methodology that uses traffic-shaping heuristics to guarantee bounded communication delays and the fulfillment of memory requirements. We evaluate the model for varied network configurations and workload, and present a comparative performance analysis in terms of link utilization, queue size, and execution time. With the proposed traffic-shaping heuristics, we endow XDense with the capabilities required for real-time applications.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 Association for Computing Machinery. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details. |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Funding Information: | Funder Grant number EPSRC EP/P003664/1 |
Depositing User: | Pure (York) |
Date Deposited: | 12 Jun 2018 11:00 |
Last Modified: | 06 Feb 2025 00:08 |
Published Version: | https://doi.org/10.1145/3230872 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1145/3230872 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:131890 |