Hybrid evolutionary algorithm (NNACOR) for energy minimization in a wireless mesh topology towards green computing

Abstract

Wireless sensor networks are a very rapidly emerging class of network structures being utilized in almost all computing environments. Energy consumption is an essential criterion especially with the recent need in conservation of energy and carbon footprint. The proposed research paper investigated the prospects of green computing towards implementation of a hybrid algorithm (NNACOR) based on evolutionary computing model deriving its behaviour from naturally occurring phenomenon for reducing the energy consumed by each node in the mesh topology. The experiments have been conducted in NS2 and compared against the conventional AODC routing protocol, and the observed results indicate a superior performance of the proposed evolutionary model by providing up to a 48% in energy saving as against a 44% energy saving reported in the literature.

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References

  1. Akyildiz IF, Wang X (2005a) Wireless mesh networks: a survey. Comput Netw J 47(4):445–487

    Article  Google Scholar 

  2. Akyildiz IF, Wang X (2005b) A survey on wireless mesh networks. IEEE Commun Mag 43(9):22–30

    Article  Google Scholar 

  3. Al Hazmi Y, De Meer H, Hummel KA, Meyer H (2011) Energy efficient wireless mesh infrastructures. IEEE Netw 25(2):32–38

    Article  Google Scholar 

  4. Ali Zulfiqar, Shahazad Waseem (2013) Analysis of routing protocols in AD HOC and sensor wireless networks based on swarm intelligence. Int J Netw Commun 3(1):1–11

    Google Scholar 

  5. Amiri E, Keshavarz H, Alizadeh M (2014) Energy efficient routing in wireless sensor networks based on fuzzy ant colony optimization. Int J Distrib Sens Netw 13(4):579–597

    Google Scholar 

  6. Bemmoussat C, Didi F, Feham M (2012) Efficient routing protocol to support QoS in wireless mesh network. Int J Wirel Mob Netw 4(5):89–104

    Article  Google Scholar 

  7. Bianzino A, Chaudet C, Rossi D, Rougier J (2012) A survey of green networking research. IEEE Commun Surv Tutor 14(1):3–20

    Article  Google Scholar 

  8. Capone A, Malandra F, Sanso B (2012) Energy savings in wireless mesh networks in time variable context. Mob Netw Appl 17(2):298–311

    Article  Google Scholar 

  9. Chaudhary D (2010) Bee inspired routing protocols for mobile ad hoc network. J Emerg Technol Web Intell 2(2):86–88

    MathSciNet  Google Scholar 

  10. Christensen K, Gunaratne P, Nordman, George B (2004) The next frontier for communication networks: power management. Comput Commun 27(18):1758–1770

    Article  Google Scholar 

  11. Fan Q, Fan J, Li J, Wang X (2012) A multi-hop energy efficient sleeping MAC protocol based on TDMA scheduling for wireless mesh sensor networks. J Netw. https://doi.org/10.4304/jnw.7.9.1355-1361

    Article  Google Scholar 

  12. Gunaratne C, Christensen K (2005) A new predictive power management method for network devices. IEE Electron Lett 41(13):775–777

    Article  Google Scholar 

  13. Kumaravel K, Marimuthu A (2014) An efficient multi path routing algorithm based on hybrid artificial bee colony algorithm for wireless mesh networks. J Theor Appl Inf Technol 68(1):53–62

    Google Scholar 

  14. Liu Y, Yang Z, Ning T (2014) Efficient quality of service support in mobile opportunistic networks. IEEE Trans Veh Technol 63(9):4574–4584

    Article  Google Scholar 

  15. Mamachaoui S, Didi F, Guy Pujolle (2013) A Survey on energy efficiency for wireless mesh networks. Int J Comput Netw Commun 15(2):105–124

    Article  Google Scholar 

  16. Mamachaoui S, Didi F, Senouci Mohamed, Guy Pujolle (2015) Energy efficient management for wireless mesh networks with green routers. Mob Netw Appl 15(2):105–124

    Google Scholar 

  17. Niyato D, Hossain E, Rashid MM, Bhargava VK (2007) Wireless sensor networks with energy harvesting technologies: a game theoretic approach to optimal energy management. IEEE Wirel Commun 14:90–96

    Article  Google Scholar 

  18. Palak (2016) Energy optimization in Ad Hoc networks using ant colony optimization. Int J Res Appl Sci Eng Technol 4(1):79–82

    Google Scholar 

  19. Ting CK, Liao CC (2010) A Memetic algorithm for extending wireless sensor network lifetime. Inf Sci 180:4818–4833

    Article  Google Scholar 

  20. Wang X, Vasilakos AV, Chen M, Liu Y, Kwon TT (2012) A survey of green mobile networks: opportunities and challenges. Mob Netw Appl 17(1):4–20

    Article  Google Scholar 

  21. Zhao Y, Wu L, Li F, Lu S (2012) On maximizing the lifetime of wireless sensor networks using virtual backbone scheduling. Trans Parallel Distrib Process 23:1528–1535

    Article  Google Scholar 

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Correspondence to B. Prakash.

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Prakash, B., Jayashri, S. & Prabaharan, G. Hybrid evolutionary algorithm (NNACOR) for energy minimization in a wireless mesh topology towards green computing. Soft Comput 24, 10893–10902 (2020). https://doi.org/10.1007/s00500-019-04592-1

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Keywords

  • Wireless mesh networks
  • Routing protocols
  • AODC
  • Evolutionary computing