IDEAS home Printed from https://ideas.repec.org/a/spr/telsys/v67y2018i3d10.1007_s11235-017-0356-6.html
   My bibliography  Save this article

Congestion avoidance in cognitive wireless sensor networks using TOPSIS and response surface methodology

Author

Listed:
  • M. Gholipour

    (Islamic Azad University)

  • A. T. Haghighat

    (Islamic Azad University)

  • M. R. Meybodi

    (Amirkabir University of Technology)

Abstract

Congestion in wireless sensor networks degrades the quality of the channel and network throughput. This leads to packet loss and energy dissipation. To cope with this problem, a two-stage cognitive network congestion control approach is presented in this paper. In the first stage of the proposed strategy, initially downstream nodes calculate their buffer occupancy ratio and estimate congestion degree in the MAC layer. Then, they send the estimated value to both network and transport layers of their upstream nodes. The network layer of the upstream node uses TOPSIS in order to rank all neighbors to select the best one as the next relay node. In the second stage, transport layer of the given node adjusts the transmission rate using an optimized regression analysis by RSM. Extensive simulations demonstrated that the proposed method not only decreases packet loss, but also significantly improves throughput and energy efficiency under different traffic conditions, especially in heavy traffic areas. Also, Tukey test is used to compare performance of algorithms as well as to demonstrate that the proposed method is significantly better than other methods.

Suggested Citation

  • M. Gholipour & A. T. Haghighat & M. R. Meybodi, 2018. "Congestion avoidance in cognitive wireless sensor networks using TOPSIS and response surface methodology," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 67(3), pages 519-537, March.
    • Handle: RePEc:spr:telsys:v:67:y:2018:i:3:d:10.1007_s11235-017-0356-6
    DOI: 10.1007/s11235-017-0356-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11235-017-0356-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11235-017-0356-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jack P. C. Kleijnen, 2015. "Response Surface Methodology," International Series in Operations Research & Management Science, in: Michael C Fu (ed.), Handbook of Simulation Optimization, edition 127, chapter 0, pages 81-104, Springer.
    2. Georgiou, Stelios D. & Stylianou, Stella & Aggarwal, Manohar, 2014. "A class of composite designs for response surface methodology," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1124-1133.
    3. Gaddafi Abdul-Salaam & Abdul Hanan Abdullah & Mohammad Hossein Anisi & Abdullah Gani & Abdulhameed Alelaiwi, 2016. "A comparative analysis of energy conservation approaches in hybrid wireless sensor networks data collection protocols," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 61(1), pages 159-179, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shen-Tsu Wang, 2016. "Integrating grey sequencing with the genetic algorithm--immune algorithm to optimise touch panel cover glass polishing process parameter design," International Journal of Production Research, Taylor & Francis Journals, vol. 54(16), pages 4882-4893, August.
    2. Yek, Peter Nai Yuh & Cheng, Yoke Wang & Liew, Rock Keey & Wan Mahari, Wan Adibah & Ong, Hwai Chyuan & Chen, Wei-Hsin & Peng, Wanxi & Park, Young-Kwon & Sonne, Christian & Kong, Sieng Huat & Tabatabaei, 2021. "Progress in the torrefaction technology for upgrading oil palm wastes to energy-dense biochar: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    3. Qin, Caiyan & Kim, Joong Bae & Lee, Bong Jae, 2019. "Performance analysis of a direct-absorption parabolic-trough solar collector using plasmonic nanofluids," Renewable Energy, Elsevier, vol. 143(C), pages 24-33.
    4. Ramos, Ana & Monteiro, Eliseu & Rouboa, Abel, 2019. "Numerical approaches and comprehensive models for gasification process: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 110(C), pages 188-206.
    5. M'Arimi, M.M. & Mecha, C.A. & Kiprop, A.K. & Ramkat, R., 2020. "Recent trends in applications of advanced oxidation processes (AOPs) in bioenergy production: Review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 121(C).
    6. Renzi, Massimiliano & Bietresato, Marco & Mazzetto, Fabrizio, 2016. "An experimental evaluation of the performance of a SI internal combustion engine for agricultural purposes fuelled with different bioethanol blends," Energy, Elsevier, vol. 115(P1), pages 1069-1080.
    7. Chamberlin Stéphane Azebaze Mboving & Zbigniew Hanzelka & Andrzej Firlit, 2022. "Analysis of the Factors Having an Influence on the LC Passive Harmonic Filter Work Efficiency," Energies, MDPI, vol. 15(5), pages 1-51, March.
    8. Lu Chen & Qincheng Chen & Pinhua Rao & Lili Yan & Alghashm Shakib & Guoqing Shen, 2018. "Formulating and Optimizing a Novel Biochar-Based Fertilizer for Simultaneous Slow-Release of Nitrogen and Immobilization of Cadmium," Sustainability, MDPI, vol. 10(8), pages 1-14, August.
    9. Biranchi Panda & K. Shankhwar & Akhil Garg & M. M. Savalani, 2019. "Evaluation of genetic programming-based models for simulating bead dimensions in wire and arc additive manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 30(2), pages 809-820, February.
    10. Zahedi, Ali Reza & Mirnezami, Seyed Abolfazl, 2020. "Experimental analysis of biomass to biodiesel conversion using a novel renewable combined cycle system," Renewable Energy, Elsevier, vol. 162(C), pages 1177-1194.
    11. Ahmad Abbaszadeh-Mayvan & Barat Ghobadian & Gholamhassan Najafi & Talal Yusaf, 2018. "Intensification of Continuous Biodiesel Production from Waste Cooking Oils Using Shockwave Power Reactor: Process Evaluation and Optimization through Response Surface Methodology (RSM)," Energies, MDPI, vol. 11(10), pages 1-13, October.
    12. de Oliveira, Lucas Guedes & Aquila, Giancarlo & Balestrassi, Pedro Paulo & de Paiva, Anderson Paulo & de Queiroz, Anderson Rodrigo & de Oliveira Pamplona, Edson & Camatta, Ulisses Pessin, 2020. "Evaluating economic feasibility and maximization of social welfare of photovoltaic projects developed for the Brazilian northeastern coast: An attribute agreement analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 123(C).
    13. Gorji, Tahereh B. & Ranjbar, A.A., 2017. "Thermal and exergy optimization of a nanofluid-based direct absorption solar collector," Renewable Energy, Elsevier, vol. 106(C), pages 274-287.
    14. Trung-Thanh Nguyen & Mozammel Mia, 2020. "Modeling and Evaluation of Energy Efficiency of New Hybrid Turning-Burnishing Process in Terms of Surface Properties," Energies, MDPI, vol. 13(18), pages 1-20, September.
    15. Masooma Munir & Muhammad Nadeem & Barkat Ali & Muhammad Sultan & Rabia Kanwal & Huda Abdalrahman Al-Jumayi & Eman Hassan Ahmed Algarni & Maged B. Alnofeai & Samy F. Mahmoud, 2022. "Investigating the Impact of Ultrasound, Microwave, and High-Pressure Processing of Milk on the Volatile Compounds and Sensory Properties of Cheddar Cheese," Agriculture, MDPI, vol. 12(5), pages 1-17, April.
    16. Najafi, Gholamhassan & Ghobadian, Barat & Yusaf, Talal & Safieddin Ardebili, Seyed Mohammad & Mamat, Rizalman, 2015. "Optimization of performance and exhaust emission parameters of a SI (spark ignition) engine with gasoline–ethanol blended fuels using response surface methodology," Energy, Elsevier, vol. 90(P2), pages 1815-1829.
    17. Iftikhar Ahmad & Adil Sana & Manabu Kano & Izzat Iqbal Cheema & Brenno C. Menezes & Junaid Shahzad & Zahid Ullah & Muzammil Khan & Asad Habib, 2021. "Machine Learning Applications in Biofuels’ Life Cycle: Soil, Feedstock, Production, Consumption, and Emissions," Energies, MDPI, vol. 14(16), pages 1-27, August.
    18. Xing Yang & Hailong Wang & Peter James Strong & Song Xu & Shujuan Liu & Kouping Lu & Kuichuan Sheng & Jia Guo & Lei Che & Lizhi He & Yong Sik Ok & Guodong Yuan & Ying Shen & Xin Chen, 2017. "Thermal Properties of Biochars Derived from Waste Biomass Generated by Agricultural and Forestry Sectors," Energies, MDPI, vol. 10(4), pages 1-12, April.
    19. Azman, Nadia Farhana & Abdeshahian, Peyman & Kadier, Abudukeremu & Shukor, Hafiza & Al-Shorgani, Najeeb Kaid Nasser & Hamid, Aidil Abdul & Kalil, Mohd Sahaid, 2016. "Utilization of palm kernel cake as a renewable feedstock for fermentative hydrogen production," Renewable Energy, Elsevier, vol. 93(C), pages 700-708.
    20. Ibrahim, Ayooluwa Paul & Omilakin, Ropo Oluwasesan & Betiku, Eriola, 2019. "Optimization of microwave-assisted solvent extraction of non-edible sandbox (Hura crepitans) seed oil: A potential biodiesel feedstock," Renewable Energy, Elsevier, vol. 141(C), pages 349-358.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:telsys:v:67:y:2018:i:3:d:10.1007_s11235-017-0356-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.