Skip to main content

Quality-Driven Schemes Enhancing Resilience of Wireless Networks under Weather Disruptions

  • Chapter
  • First Online:
Guide to Disaster-Resilient Communication Networks

Abstract

Heavy rain, dense fog, snow, extreme temperatures and moving objects represent a few examples of environmental conditions, which have a significant influence on reliable communications over wireless networks. In particular, a wireless link is vulnerable to precipitation or to fluctuations caused by reflections of signals from moving objects. Wireless signal can experience the so-called path loss or attenuation of signal strength. In this case, critical environmental changes in communication and its degradation are noticeable by users as well as network operators while service and network quality are evaluated by them, respectively. A dependence of the overall quality of communications on different quality parameters can be used as a suitable tool for effective resilience of wireless communications against the environmental disruptions. This chapter presents ideas about how the quality parameters from different communication layers can be used to create alerts when the performance of a service over wireless optical network is being degraded, as well as how data can be rerouted in a wireless sensor network, and a wireless positioning system can be modified in the presence of environmental disruptions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 69.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 89.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Benikovsky J, Brida P, Machaj J (2012) Proposal of user adaptive modular localization system for ubiquitous positioning. In: Asian Conference on Intelligent Information and Database Systems, pp 391–400. Springer, Berlin

    Google Scholar 

  2. Boano CA, Zúñiga M, Brown J, Roedig U, Keppitiyagama C, Römer K (2014) Templab: a testbed infrastructure to study the impact of temperature on wireless sensor networks. In: Proceedings of the 13th International Symposium on Information Processing in Sensor Networks, pp 95–106. IEEE Press

    Google Scholar 

  3. Brida P, Machaj J (2015) Impact of weather conditions on fingerprinting localization based on IEEE 802.11a. In: Núñez M, Nguyen NT, Camacho D, Trawiński B (eds) Computational Collective Intelligence, pp 316–325. Springer International Publishing, Cham

    Google Scholar 

  4. Bruzgiene R, Narbutaite L, Leitgeb E, Pezzei P, Plank T (2017) The effect of weather on quality of experience in optical wireless communication system (selected from CEMA’17 Conference). J Appl Electromagn 19(2):23–32

    Google Scholar 

  5. Çetinkaya EK, Sterbenz JPG (2013) A taxonomy of network challenges. In: 2013 9th International Conference on the Design of Reliable Communication Networks (DRCN), pp 322–330. IEEE

    Google Scholar 

  6. Dhekne A, Gowda M, Choudhury RR, Nelakuditi S (2018) If WiFi APs could move: a measurement study. IEEE Trans Mob Comput 17(10):2293–2306

    Article  Google Scholar 

  7. Guidara A, Fersi G, Derbel F, Jemaa MB (2018) Impacts of temperature and humidity variations on RSSI in indoor wireless sensor networks. Procedia Comput Sci 126:1072–1081

    Article  Google Scholar 

  8. ISO Central Secretary (2000) Information technology—Open Systems Interconnection—basic reference model: the basic model. Standard ISO/IEC 7498-1:1994, International Organization for Standardization, Geneva, CH. URL https://www.iso.org/standard/20269.html

  9. ITU-T (2008) Definitions of terms related to quality of service. Recommendation E.800, International Telecommunication Union, Geneva

    Google Scholar 

  10. ITU-T (2017) Vocabulary for performance, quality of service and quality of experience. Recommendation P.10/G.100, International Telecommunication Union, Geneva

    Google Scholar 

  11. Katz M, Matinmikko-Blue M, Latva-Aho M (2018) 6Genesis flagship program: building the bridges towards 6G-enabled wireless smart society and ecosystem. In: 2018 IEEE 10th Latin-American Conference On Communications (LATINCOM), pp 1–9. IEEE

    Google Scholar 

  12. Kayri M, Kayri İ (2010) A proposed OSI based network troubles identification model. arXiv preprint arXiv:1009.6045

  13. Kumar A, Sun Y (2008) Quality-of-Protection (QoP): a quantitative methodology to grade security services. In: 2008 28th International Conference on Distributed Computing Systems Workshops (ICDCS Workshops)(ICDCSW), pp 394–399

    Google Scholar 

  14. Laoudias C, Piché R, Panayiotou CG (2012) Device signal strength self-calibration using histograms. In: 2012 International Conference on Indoor Positioning and Indoor Navigation (IPIN), pp 1–8

    Google Scholar 

  15. Leitgeb E, Gebhart M, Fasser P, Bregenzer J, Tanczos J (2003) Impact of atmospheric effects in free space optics transmission systems. In: Proceedings of SPIE—The International Society for Optical Engineering, Atmospheric Propagation. SPIE

    Google Scholar 

  16. Lemic F, Handziski V, Aernouts M, Janssen T, Berkvens R, Wolisz A, Famaey J (2019) Regression-based estimation of individual errors in fingerprinting localization. IEEE Access 7:33652–33664

    Article  Google Scholar 

  17. Luomala J, Hakala I (2015) Effects of temperature and humidity on radio signal strength in outdoor wireless sensor networks. In: 2015 Federated Conference on Computer Science and Information Systems (FedCSIS), pp 1247–1255. IEEE

    Google Scholar 

  18. Machaj J, Brida P (2013) Survey of device calibration techniques for fingerprinting localization algorithms. Communications 15(4):48–53

    Google Scholar 

  19. Marfievici R, Murphy AL, Picco GP, Ossi F, Cagnacci F (2013) How environmental factors impact outdoor wireless sensor networks: a case study. In: 2013 IEEE 10th International Conference on Mobile Ad-hoc and Sensor Systems, pp 565–573. IEEE

    Google Scholar 

  20. Mauthe A, Hutchison D, Cetinkaya EK, Ganchev I, Rak J, Sterbenz JPG, Gunkel M, Smith P, Gomes T (2016) Disaster-resilient communication networks: principles and best practices. In: 2016 8th International Workshop on Resilient Networks Design and Modeling (RNDM), pp 1–10. IEEE

    Google Scholar 

  21. Minhas TN, Fiedler M (2013) Quality of experience hourglass model. In: 2013 International Conference on Computing, Management and Telecommunications (ComManTel), pp 87–92. IEEE

    Google Scholar 

  22. Mlynka M, Brida P, Machaj J (2014) Modular localization system for intelligent transport. In: Recent Developments in Computational Collective Intelligence, pp 115–124. Springer, Berlin

    Google Scholar 

  23. Muhammad S, Flecke B, Leitgeb E, Gebhart M (2007) Characterization of fog attenuation in terrestrial free space optical links. Opt Eng 46(6)

    Google Scholar 

  24. Muhammad S, Köhldorfer P, Leitgeb E (2005) Channel modeling for terrestrial free space optical links. In: Proceedings of 2005 7th International Conference Transparent Optical Networks (ICTON 2005). IEEE

    Google Scholar 

  25. Park C, Lahiri K, Raghunathan A (2005) Battery discharge characteristics of wireless sensor nodes: an experimental analysis. In: 2005 Second Annual IEEE Communications Society Conference on Sensor and Ad hoc Communications and Networks, 2005. IEEE SECON 2005, pp 430–440. Citeseer

    Google Scholar 

  26. Popleteev A (2017) Ambiloc: a year-long dataset of FM, TV and GSM fingerprints for ambient indoor localization. In: 8th International Conference on Indoor Positioning and Indoor Navigation (IPIN-2017)

    Google Scholar 

  27. Rademacher M, Kessel M, Jonas K (2016) Experimental results for the propagation of outdoor IEEE802.11 links. VDE ITG-Fachbericht Mobilkommunikation 22

    Google Scholar 

  28. Rafiqul IM, Alam MM, Lwas AK, Mohamad SY (2018) Rain rate distributions for microwave link design based on long term measurement in Malaysia

    Google Scholar 

  29. Rak J (2012) Design of weather disruption-tolerant wireless mesh networks. In: 2012 15th International Telecommunications Network Strategy and Planning Symposium (NETWORKS), pp 1–6. IEEE

    Google Scholar 

  30. Rozhon J, Blaha P, Voznak M, Skapa J (2012) The weather impact on speech quality in GSM networks. In: Kwiecień A, Gaj P, Stera P (eds) Computer Networks. Springer, Berlin, pp 360–369

    Google Scholar 

  31. Tapolcai J, Cholda P, Cinkler T, Wajda K, Jajszczyk A, Autenrieth A, Bodamer S, Colle D, Ferraris G, Lonsethagen H et al (2005) Quality of resilience (QoR): nobel approach to the multi-service resilience characterization. In: 2nd International Conference on Broadband Networks, 2005. BroadNets 2005, pp 1328–1337. IEEE

    Google Scholar 

  32. Tornatore M, André J, Babarczi P, Braun T, Følstad E, Heegaard P, Hmaity A, Furdek M, Jorge L, Kmiecik W et al (2016) A survey on network resiliency methodologies against weather-based disruptions. In: 2016 8th International Workshop on Resilient Networks Design and Modeling (RNDM), pp 23–34. IEEE

    Google Scholar 

  33. University B (2018) Bu-502: discharging at high and low temperatures. https://batteryuniversity.com/learn/article/discharging_at_high_and_low_temperatures. Accessed 16 Apr 2019

  34. Winkler S (2001) Visual fidelity and perceived quality: toward comprehensive metrics. In: Human Vision and Electronic Imaging VI, vol 4299, pp 114–126. International Society for Optics and Photonics

    Google Scholar 

  35. Yaghoubi F, Chen J, Rostami A, Wosinska L (2016) Mitigation of rain impact on microwave backhaul networks. In: 2016 IEEE International Conference on Communications Workshops (ICC), pp 134–139. IEEE

    Google Scholar 

Download references

Acknowledgements

This chapter is based on work from COST Action CA15127 (“Resilient communication services protecting end-user applications from disaster-based failures—RECODIS”) supported by COST (European Cooperation in Science and Technology). Partially funded by Latvian Rural Development Programme 2014–2020.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Rasa Bruzgiene .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Bruzgiene, R. et al. (2020). Quality-Driven Schemes Enhancing Resilience of Wireless Networks under Weather Disruptions. In: Rak, J., Hutchison, D. (eds) Guide to Disaster-Resilient Communication Networks. Computer Communications and Networks. Springer, Cham. https://doi.org/10.1007/978-3-030-44685-7_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-44685-7_12

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-44684-0

  • Online ISBN: 978-3-030-44685-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics