Optimization of Wireless Networks for Resilience to Adverse Weather Conditions

Part of the Computer Communications and Networks book series (CCN)


In this chapter, we consider how adverse weather conditions such as rain or fog affect the performance of wireless networks, and how to optimize these networks so as to make them robust to these conditions. We first show how to analyze the weather conditions in order to make them useful for network optimization modelling. Using an example realistic network, we show how to optimize two types of wireless networks: free-space optical (FSO) networks and wireless mesh networks (WMN). The key difference between the two network types is that in WMNs, links interfere with each other, while in FSO networks, link rates may be assumed independent. We formulate optimization problems to protect each network type against adverse weather conditions, discuss solution methods to solve them and present a numerical study illustrating the considerations of the chapter.



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). M. Pióro, E. Fitzgerald and I. Kalesnikau were supported by the National Science Center (Poland) [Grant 2015/17/B/ST7/03910 “Logical tunnel capacity control—a traffic routing and protection strategy for communication networks with variable link capacity” and Grant 2017/25/B/ST7/02313: “Packet routing and  transmission scheduling optimization in multi-hop wireless networks with multicast traffic”]. The work of D. Nace was carried out in the framework of the Labex MS2T [Reference ANR-11-IDEX-0004-02].


  1. 1.
    Ahuja R, Magnanti T, Orlin J (1993) Network flows: theory, algorithms, and applications. Prentice Hall, New JerseyGoogle Scholar
  2. 2.
    Bertsimas D, Sim M (2004) The price of robustness. Oper Res 52(1):35–53MathSciNetzbMATHCrossRefGoogle Scholar
  3. 3.
    Björklund P, Värbrand, Yuan D (2003) Resource optimization of spatial TDMA in ad hoc radio networks: a column generation approach. In: IEEE INFOCOM’03, pp 818–824Google Scholar
  4. 4.
    Capone A, Carello G (2006) Scheduling optimization in wireless MESH networks with power control and rate adaptation. In: Proc SECON 2006Google Scholar
  5. 5.
    Capone A, Carello G, Filippini I, Gualandi S, Malucelli F (2010) Routing, scheduling and channel assignment in wireless mesh networks: optimization models and algorithms. Ad Hoc Netw 8:545–563Google Scholar
  6. 6.
  7. 7.
  8. 8.
    Fitzgerald E, Pióro M, Tomaszewski A (2018) Protecting wireless mesh networks against adverse weather conditions. In: Proceedings of RNDM 2018. IEEE, pp 1–7Google Scholar
  9. 9.
    Fitzgerald E, Pióro M, Tomaszewski A (2018) Protecting wireless mesh networks against adverse weather conditions. In: Proceedings of RNDM 2018. Longyearbyen, Norway.
  10. 10.
    FSona optical wireless (2017)
  11. 11.
    International Telecommunication Union Radiocommunication Sector (ITU-R) (2012) Recommendation ITU-R p.1817–1: propagation data required for the design of terrestrial free-space optical links. In: P Series Radiowave PropagationGoogle Scholar
  12. 12.
    Kalesnikau I, Pióro M, Poss M, Nace D, Tomaszewski A (2019) A robust optimization model for affine/quadratic flow thinning—a traffic protection mechanism for networks with variable link capacity. Networks.
  13. 13.
    Koster A, Zymolka A, Jäger M, Hülserman R (2005) Demand-wise shared protection for meshed optical networks. J Netw Syst Manag 13(1):35–55CrossRefGoogle Scholar
  14. 14.
    Lasdon L (1970) Optimization theory for large systems. Macmillan, New YorkGoogle Scholar
  15. 15.
    LightPointe AireLink 80 10 Gbps 70/80GHz Radios (2017)Google Scholar
  16. 16.
    Malhotra J, Kumar M, Sharma A (2013) Performance comparison of PS-QPSK and PM-QPSK modulation schemes in high capacity long haul DWDM optical communication link. Int J Eng Sci 2(5):154–159Google Scholar
  17. 17.
    Minoux M (1986) Mathematical programming—theory and algorithms. Wiley, ChichesterGoogle Scholar
  18. 18.
    Nace D, Pióro M, Poss M, D’Andreagiovanni F, Kalesnikau I, Shehaj M, Toma-szewski A (2019) An optimization model for robust FSO network dimensioning. Opt Switching Netw 32:25–40Google Scholar
  19. 19.
    Nemhauser GL, Wolsey LA (1988) Integer and combinatorial optimization. Wiley, New YorkGoogle Scholar
  20. 20.
    Pióro M, Fouquet Y, Nace D, Poss M (2016) Optimizing flow thinning protection in multicommodity networks with variable links capacity. Oper Res 64(2):273–289MathSciNetzbMATHCrossRefGoogle Scholar
  21. 21.
    Pióro M, Kalesnikau I, Poss M (2017) An optimization model for affine flow thinning—a traffic protection mechanism for FSO networks. In: Proceedings of RNDM 2017, Alghero, Italy.
  22. 22.
    Pióro M, Kalesnikau I, Poss M (2018) Path generation for affine flow thinning. Electron Notes Discrete Math 64:355–364MathSciNetzbMATHCrossRefGoogle Scholar
  23. 23.
    Pióro M, Kalesnikau I, Poss M (2019) An optimization model for quadratic flow thinning—a traffic protection mechanism for FSO networks. Opt Switch Netw 31:168–182CrossRefGoogle Scholar
  24. 24.
    Pióro M, Kalesnikau I, Poss M (2017) Path generation for affine flow thinning. In: Proceedings of INOC 2017, Lisbon, Portugal, FebruaryGoogle Scholar
  25. 25.
    Pióro M, Kalesnikau I, Poss M, Nace D, Tomaszewski A (2018) Practical aspects of flow thinning optimization. In: Proceedings of RNDM 2018, Longyearbyen, Norway.
  26. 26.
    Pióro M, Medhi D (2004) Routing, flow, and capacity design in communication and computer networks. Morgan-Kaufmann, San FranciscoGoogle Scholar
  27. 27.
    Pióro M, Tomaszewski A, Capone A (2018) Maximization of multicast periodic traffic throughput in multi-hop wireless networks with broadcast transmissions. Ad Hoc Netw 77:119–142. Scholar
  28. 28.
    Pióro M, Żotkiewicz M, Staehle B, Staehle D, Yuan D (2014) On max-min fair flow optimization in wireless mesh networks. Ad Hoc Netw 13:134–152Google Scholar
  29. 29.
    Population city: France—population (2018) Accessed 29 Mar 2018
  30. 30.
    Priyanka J, Bhuperdra S, Rashmi C (2014) Survey on performance of free space optical communication links under various field parameters. IOSR-JEEE 9(2):71–75Google Scholar
  31. 31.
    Rak J (2015) Measures of region failure survivability for wireless mesh networks. Wirel Netw 21(2):673–684CrossRefGoogle Scholar
  32. 32.
    Rak J (2016) A new approach to design of weather disruption-tolerant wireless mesh networks. Telecommun Syst 61(2):311–323CrossRefGoogle Scholar
  33. 33.
    Revolution Wi-Fi: Wi-Fi SNR to MCS data rate mapping reference.
  34. 34.
    Svensson A (2007) An introduction to adaptive QAM modulation schemes for known and predicted channels. Proc IEEE 95(12):2322–2336. Scholar
  35. 35.
    Tomaszewski A, Pióro M, Żotkiewicz M (2010) On the complexity of resilient network design. Networks 55:109–118MathSciNetzbMATHCrossRefGoogle Scholar
  36. 36.
    Wessäly R, Orlowski S, Zymolka A, Koster A, Gruber C (2005) Demand-wise shared protection revisited: a new model for survivable network design. In: Proceedings of INOC 2005, pp 100–105Google Scholar
  37. 37.
    World weather online. Accessed 29 Mar 2018

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Warsaw University of TechnologyWarszawaPoland
  2. 2.Lund UniversityLundSweden
  3. 3.Sorbonne universités, Université de technologie de Compiègne, Heudiasyc UMR CNRS 7253CompiègneFrance
  4. 4.Faculty of Electronics, Telecommunications and InformaticsGdańsk University of TechnologyGdańskPoland

Personalised recommendations