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Optimising Redundancy in Distributed Sensor Networks

Published:07 June 2023Publication History

ABSTRACT

Whether it be for environmental sensing or Internet of Things (IoT) applications, sensor networks are of growing use thanks to their large-scale sensing and distributed data storage abilities. However, when used in hazardous conditions and thus undergoing technical failures, data within sensor networks may never be retrieved due to critical node failures. For this purpose, data redundancy can be introduced to relieve this data loss but comes at a cost of increased data transmission and storage, hence reducing the network's lifetime through increased power consumption. Here, a novel distributed storage strategy based on graph topology estimations is proposed to optimise the use of redundancy in fallible sensor networks. The storage strategy is found to outperform other strategies in providing the highest robustness whilst ensuring considerable lifetime, in the form of limited data transmission and storage use.

References

  1. Mohammadnaser Ansari and Jeffrey S. Smith. 2017. Warehouse Operations Data Structure (WODS): A data structure developed for warehouse operations modeling. Computers & Industrial Engineering 112 (oct 2017), 11--19. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Jacob Beal. 2003. Persistent Nodes for Reliable Memory in Geographically Local Networks. MIT AI Memos (1959--2004) (2003).Google ScholarGoogle Scholar
  3. Alexander Bertrand and Marc Moonen. 2013. Distributed computation of the Fiedler vector with application to topology inference in ad hoc networks. Signal Processing 93, 5 (may 2013), 1106--1117. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Neerja Bhatnagar, Kevin M. Greenan, Rosie Wacha, Ethan L. Miller, and Darrell D. E. Long. 2008. Energy-reliability tradeoffs in sensor network storage. In In Proceedings of the 5th Workshop on Embedded Networked Sensors.Google ScholarGoogle Scholar
  5. Matthew Gadd and Paul Newman. 2015. A framework for infrastructure-free warehouse navigation. In 2015 IEEE International Conference on Robotics and Automation (ICRA). IEEE. Google ScholarGoogle ScholarCross RefCross Ref
  6. Paul Gaynor and Daniel Coore. 2014. Towards distributed wilderness search using a reliable distributed storage device built from a swarm of miniature UAVs. In 2014 International Conference on Unmanned Aircraft Systems (ICUAS). IEEE. Google ScholarGoogle ScholarCross RefCross Ref
  7. Cinara Ghedini, Cristian Secchi, Carlos H.C. Ribeiro, and Lorenzo Sabattini. 2015. Improving robustness in multi-robot networks. IFAC-PapersOnLine 48, 19 (2015), 63--68. Google ScholarGoogle ScholarCross RefCross Ref
  8. Jacopo Panerati, Marco Minelli, Cinara Ghedini, Lucas Meyer, Marcel Kaufmann, Lorenzo Sabattini, and Giovanni Beltrame. 2018. Robust connectivity maintenance for fallible robots. Autonomous Robots 43, 3 (nov 2018), 769--787. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Stanley Wasserman and Katherine Faust. 1994. Social Network Analysis. Cambridge University Press. Google ScholarGoogle ScholarCross RefCross Ref
  10. James Wilson and Sabine Hauert. 2022. Information transport in communication limited swarms. Artificial Life and Robotics (jun 2022). Google ScholarGoogle ScholarDigital LibraryDigital Library

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        • Published in

          cover image ACM Conferences
          SAC '23: Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing
          March 2023
          1932 pages
          ISBN:9781450395175
          DOI:10.1145/3555776

          Copyright © 2023 Owner/Author(s)

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          Publication History

          • Published: 7 June 2023

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