research-article

Extensive Analysis of a Real-Time Dense Wired Sensor Network Based on Traffic Shaping

Authors:

João Loureiro,

Raghuraman Rangarajan,

Borislav Nikolic,

Leandro Soares Indrusiak,

Eduardo TovarAuthors Info & Claims

ACM Transactions on Cyber-Physical Systems, Volume 3, Issue 3

Article No.: 27, Pages 1 - 27

https://doi.org/10.1145/3230872

Published: 20 August 2019 Publication History

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.

References

[1]

Ankur Agarwal, Cyril Iskander, and Ravi Shankar. 2009. Survey of network on chip (NoC) architectures 8 contributions. Journal of Engineering, Computing and Architecture 3, 1 (2009), 21--27.

[2]

Scott Anders, William Sellers, and Anthony Washburn. 2004. Active flow control activities at NASA Langley. In Proceedings of the 2nd AIAA Flow Control Conference. 2623.

[3]

Richard Barry. 2016. Mastering the FreeRTOS real time kernel. Real Time Engineers Ltd. https://freertos.org/Documentation/161204_Mastering_the_FreeRTOS_Real_Time_Kernel-A_Hands-On_Tutorial_Guide.pdf.

[4]

William K. Blake. 2012. Mechanics of Flow-Induced Sound and Vibration V2: Complex Flow-Structure Interactions. Vol. 2. Elsevier.

[5]

Louis N. Cattafesta and Mark Sheplak. 2011. Actuators for active flow control. Annual Review of Fluid Mechanics 43 (2011), 247--272.

[6]

R. L. Cruz. 1991. A calculus for network delay. I. Network elements in isolation. IEEE Transactions on Information Theory 37, 1 (Jan 1991), 114--131.

Digital Library

[7]

Artem Dementyev, Hsin-Liu (Cindy) Kao, and Joseph A. Paradiso. 2015. SensorTape: Modular and programmable 3D-aware dense sensor network on a tape. In Proceedings of the 28th Annual ACM Symposium on User Interface Software and Technology (UIST’15). ACM, New York, NY, 649--658.

Digital Library

[8]

Rostislav Reuven Dobkin, Arkadiy Morgenshtein, Avinoam Kolodny, and Ran Ginosar. 2008. Parallel vs. serial on-chip communication. In Proceedings of the 2008 International Workshop on System Level Interconnect Prediction (SLIP’08). ACM, New York, NY, 43--50.

Digital Library

[9]

Xing Fan, Magnus Jonsson, and Jan Jonsson. 2009. Guaranteed real-time communication in packet-switched networks with FCFS queuing. Computer Networks 53, 3 (2009), 400--417.

Digital Library

[10]

M. Fidler. 2010. Survey of deterministic and stochastic service curve models in the network calculus. IEEE Communications Surveys Tutorials 12, 1 (2010), 59--86.

Digital Library

[11]

Jingcao Hu and Radu Marculescu. 2003. Energy-aware mapping for tile-based NoC architectures under performance constraints. In Proceedings of the 2003 Asia and South Pacific Design Automation Conference (ASP-DAC’03). ACM, New York, NY, 233--239.

Digital Library

[12]

Leandro Soares Indrusiak. 2014. End-to-end schedulability tests for multiprocessor embedded systems based on networks-on-chip with priority-preemptive arbitration. Journal of Systems Architecture 60, 7 (2014), 553--561.

[13]

Nobuhide Kasagi, Yuji Suzuki, and Koji Fukagata. 2009. Microelectromechanical systems-based feedback control of turbulence for skin friction reduction. Annual Review of Fluid Mechanics 41 (2009), 231--251.

[14]

N. K. Kavaldjiev and G. J. M. Smit. 2003. A survey of efficient on-chip communications for SoC. In Proceedings of the 4th PROGRESS Symposium on Embedded Systems. 129--140.

[15]

F. Kopsaftopoulos, R. Nardari, Y.-H. Li, and F. K. Chang. 2015. Experimental identification of structural dynamics and aeroelastic properties of a self-sensing smart composite wing. In Proceedings of the 10th International Workshop on Structural Health Monitoring.

[16]

S. Kumar, A. Jantsch, J.-P. Soininen, M. Forsell, M. Millberg, J. Oberg, K. Tiensyrja, and A. Hemani. 2002. A network on chip architecture and design methodology. In Proceedings of the IEEE Computer Society Annual Symposium on VLSI. IEEE, Los Alamitos, CA, 105--112.

Digital Library

[17]

Joshua Lifton, Michael Broxton, and Joseph A. Paradiso. 2005. Experiences and directions in pushpin computing. In Proceedings of the 4th International Symposium on Information Processing in Sensor Networks (IPSN’05). IEEE, Los Alamitos, CA, Article 57. http://dl.acm.org/citation.cfm?id=1147685.1147753.

Digital Library

[18]

J. Loureiro, R. Rangarajan, B. Nikolic, L. Indrusiak, and E. Tovar. 2017. Real-time dense wired sensor network based on traffic shaping. In Proceedings of the 2017 IEEE 23rd International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA’17). 1--10.

[19]

João Loureiro, Raghuraman Rangarajan, and Eduardo Tovar. 2015. Demo abstract: Towards the development of XDense, a sensor network for dense sensing. In Proceedings of the 12th European Conference on Wireless Sensor Networks (EWSN’15). 23. http://www.cister.isep.ipp.pt/ewsn2015/EWSN15PosterDemoProc_WEB.pdf#page=24.

[20]

J. Loureiro, R. Rangarajan, and E. Tovar. 2015. Distributed sensing of fluid dynamic phenomena with the XDense sensor grid network. In Proceedings of the 2015 IEEE 3rd International Conference on Cyberr-Physical Systems, Networks, and Application (CPSNA’15). 54--59.

Digital Library

[21]

João Loureiro, Pedro Santos, Raghuraman Rangarajan, and Eduardo Tovar. 2017. Simulation module and tools for XDense sensor network. In Proceedings of the Workshop on ns-3 (WNS3’17). ACM, New York, NY, 110--117.

Digital Library

[22]

Sorin Manolache, Petru Eles, and Zebo Peng. 2006. Buffer space optimisation with communication synthesis and traffic shaping for NoCs. In Proceedings of the Conference on Design, Automation, and Test in Europe (DATE’06). 718--723. http://dl.acm.org/citation.cfm?id=1131481.1131683.

Digital Library

[23]

Behram F. T. Mistree and Joseph A. Paradiso. 2010. ChainMail: A configurable multimodal lining to enable sensate surfaces and interactive objects. In Proceedings of the 4th International Conference on Tangible, Embedded, and Embodied Interaction (TEI’10). ACM, New York, NY, 65--72.

Digital Library

[24]

F. Palacios, J. Alonso, K. Duraisamy, M. Colonno, J. Hicken, A. Aranake, A. Campos, et al. 2013. Stanford University unstructured (SU 2): An open-source integrated computational environment for multi-physics simulation and design. In Proceedings of the 51st AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition. 287.

[25]

Alexandros Pantelopoulos and Nikolaos G. Bourbakis. 2010. A survey on wearable sensor-based systems for health monitoring and prognosis. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 40, 1 (2010), 1--12.

Digital Library

[26]

Ruiyi Que and Rong Zhu. 2012. Aircraft aerodynamic parameter detection using micro hot-film flow sensor array and BP neural network identification. Sensors 12, 8 (2012), 10920--10929.

[27]

D. Rahmati, S. Murali, L. Benini, F. Angiolini, G. De Micheli, and H. Sarbazi-Azad. 2013. Computing accurate performance bounds for best effort networks-on-chip. IEEE Transactions on Computers 62, 3 (March 2013), 452--467.

Digital Library

[28]

J. Reneaux2004. Overview on drag reduction technologies for civil transport aircraft. ONERA: Tire a Part 153 (2004), 1--18.

[29]

Stephen K. Robinson. 1991. Coherent motions in the turbulent boundary layer. Annual Review of Fluid Mechanics 23, 1 (1991), 601--639.

[30]

Carlos Rodrigues, Carlos Felix, Armindo Lage, and Joaquim Figueiras. 2010. Development of a long-term monitoring system based on FBG sensors applied to concrete bridges. Engineering Structures 32, 8 (2010), 1993--2002.

[31]

Artur Saudabayev and Huseyin Atakan Varol. 2015. Sensors for robotic hands: A survey of state of the art. IEEE Access 3 (2015), 1765--1782.

[32]

V. Schmitt and F. Charpin. 1979. Pressure distributions on the ONERA-M6-Wing at transonic mach numbers. Experimental Data Base for Computer Program Assessment 4 (1979), AR--138.

[33]

J. H. Seo, F. Cadieux, R. Mittal, E. Deem, and L. Cattafesta. 2018. Effect of synthetic jet modulation schemes on the reduction of a laminar separation bubble. Physical Review Fluids 3, 3 (2018), 033901.

[34]

Zheng Shi and Alan Burns. 2008. Real-time communication analysis for on-chip networks with wormhole switching. In Proceedings of the 2nd ACM/IEEE International Symposium on Networks-on-Chip (NOCS’08). IEEE, Los Alamitos, CA, 161--170. http://dl.acm.org/citation.cfm?id=1397757.1397996.

Digital Library

[35]

Vijay Sivaraman, Fabio M. Chiussi, and Mario Gerla. 2006. Deterministic end-to-end delay guarantees with rate controlled EDF scheduling. Performance Evaluation 63, 4 (2006), 509--519.

Digital Library

[36]

J. Specht and S. Samii. 2016. Urgency-based scheduler for time-sensitive switched ethernet networks. In Proceedings of the 2016 28th Euromicro Conference on Real-Time Systems (ECRTS’16). 75--85.

[37]

Troy M. Lau, Joseph T. Gwin, and Daniel P. Ferris. 2012. How many electrodes are really needed for EEG-based mobile brain imaging? Journal of Behavioral and Brain Science 2, 3 (2012), 387.

[38]

Tony Washburn. 2010. Airframe Drag/Weight Reduction Technologies. Green Aviation Summit-Fuel Burn Reduction, NASA Ames Research Center.

[39]

M. Watson, A. J. Jaworski, and N. J. Wood. 2007. Application of synthetic jet actuators for the modification of the characteristics of separated shear layers on slender wings. Aeronautical Journal 111, 1122 (2007), 519--529.

Cited By

Zhao YLi W(2024)Application and Research on Measurement and Control Technology and Intelligentization of Agricultural Machinery in the Information AgeApplied Mathematics and Nonlinear Sciences10.2478/amns-2024-08249:1Online publication date: 1-Apr-2024
https://doi.org/10.2478/amns-2024-0824
Kermia O(2020)Strictly periodic first: An optimal variant of LLF for scheduling tasks in a time‐critical cyber‐physical systemConcurrency and Computation: Practice and Experience10.1002/cpe.590834:7Online publication date: 6-Jul-2020
https://doi.org/10.1002/cpe.5908

Index Terms

Extensive Analysis of a Real-Time Dense Wired Sensor Network Based on Traffic Shaping
1. Networks
  1. Network performance evaluation

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Information & Contributors

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Published In

cover image ACM Transactions on Cyber-Physical Systems

ACM Transactions on Cyber-Physical Systems Volume 3, Issue 3

Special Issue on Real Time Aspects in CPS and Regular Papers (Diamonds)

July 2019

269 pages

ISSN:2378-962X

EISSN:2378-9638

DOI:10.1145/3356396

Editor:
Tei-Wei Kuo
City University of Hong Kong and National Taiwan University, Taiwan

Issue’s Table of Contents

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Journal Family

ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 20 August 2019

Accepted: 01 June 2018

Revised: 01 April 2018

Received: 01 September 2017

Published in TCPS Volume 3, Issue 3

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National Funds through FCT (Portuguese Foundation for Science and Technology)

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Cited By

Zhao YLi W(2024)Application and Research on Measurement and Control Technology and Intelligentization of Agricultural Machinery in the Information AgeApplied Mathematics and Nonlinear Sciences10.2478/amns-2024-08249:1Online publication date: 1-Apr-2024
https://doi.org/10.2478/amns-2024-0824
Kermia O(2020)Strictly periodic first: An optimal variant of LLF for scheduling tasks in a time‐critical cyber‐physical systemConcurrency and Computation: Practice and Experience10.1002/cpe.590834:7Online publication date: 6-Jul-2020
https://doi.org/10.1002/cpe.5908

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