Skip to main content
Log in

Cross Layer Design for Wi-Fi Sensor Network Handling Static and Dynamic Environment Using Local Automate Based Autonomic Network Architecture

  • Original Research
  • Published:
SN Computer Science Aims and scope Submit manuscript

Abstract

In social activities with shared Wi-Fi needs to accommodate large number of users and effectively handle congestion. These are critical issues due to the presence of larger density nodal activity at nearby access points involving inter-technology interference. An interference involves a statistical approach in monitoring access points with its received errors. The received errors vary with frame reception at their fields like PHY, MAC headers and payloads. Local automate-based Autonomic Network Architecture a cross layer approach algorithm is proposed to channelize a frame reception and can effectively avoid inter-technology interference. This results in P2P communication at initial stages and can accommodate multiple mobile devices with varying signal strengths. The algorithm is deployed for a dynamic environment along with static clusters. The throughput of the entire network is increased by 20% because of identifying multiple nodes with lesser latency avoiding congestion.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  1. Zeng X, Liu K, Ma J, Chen M, Yu M. Reliability and delay trade-off analysis of unslotted IEEE 802.15.4 sensor network for shipboard environment. IEEE Sens J. 2021;21(2):2400–11.

    Article  Google Scholar 

  2. Nguyen TT, Oh H. SCSMA: a smart CSMA/CA using blind learning for wireless sensor networks. IEEE Trans Ind Electron. 2020;67(12):10981–8.

    Article  Google Scholar 

  3. Barroca N, Velez FJ, Borges LM, Chatzimisios P. Performance enhancement of IEEE 802.15.4 by employing RTS/CTS and frame concatenation. IET Wirel Sens Syst. 2020;10(6):308–19.

    Article  Google Scholar 

  4. Kumar Shah I, Maity T, Singh Dohare Y. Algorithm for energy consumption minimisation in wireless sensor network. IET Commun. 2020;14(8):1301–10.

    Article  Google Scholar 

  5. Deng C, et al. IEEE 802.11be Wi-Fi 7: new challenges and opportunities. IEEE Commun Surv Tutor. 2020;22(4):2136–66.

    Article  Google Scholar 

  6. Garrido-Valenzuela F, Raveau S, Herrera JC. Bayesian route choice inference to address missed bluetooth detections. In: IEEE Transactions on Intelligent Transportation Systems; 2020. pp. 1–10.

  7. Yang G, Shi X, Feng L, He S, Shi Z, Chen J. CEDAR: a cost-effective crowdsensing system for detecting and localizing drones. IEEE Trans Mob Comput. 2020;19(9):2028–43.

    Article  Google Scholar 

  8. Cao X, Song Z, Yang B, Qian L, Han Z. Full-Duplex MAC in LAA/ Wi-Fi coexistence networks: design, modeling, and analysis. IEEE Trans Wirel Commun. 2020;19(8):5531–46.

    Article  Google Scholar 

  9. Biswas S, Roy SD, Chandra A. Cross-layer energy model for non-beacon-enabled IEEE 802.15.4 networks. IEEE Wirel Commun Lett. 2020;9(7):1084–8.

    Google Scholar 

  10. Tang X, Xiao B, Li K. Indoor crowd density estimation through mobile smartphone Wi-Fi probes. IEEE Trans Syst Man Cybern Syst. 2020;50(7):2638–49.

    Article  Google Scholar 

  11. Khan M, Wang G, Bhuiyan M, Yang K. Toward Wi-Fi hallow signal coverage modeling in collapsed structures. IEEE Internet J. 2020;7(3):2181–96.

    Article  Google Scholar 

  12. Dziedzic A, Sathya V, Rochman M, Ghosh M, Krishnan S. Machine learning enabled spectrum sharing in dense LTE-U/Wi-Fi coexistence scenarios. IEEE Open J Vehicul Technol. 2020;1(1):173–89.

    Article  Google Scholar 

  13. Chiu J, Hsiao S, Tseng P, Lai Y, Huang C. An ultra compact, low-cost, and high-performance rf package technique for Wi-Fi FEM Applications. IEEE Microw Wirel Comp Lett. 2020;30(3):265–7.

    Article  Google Scholar 

  14. Guo L, Lu Z, Wen X, Zhou S, Han Z. From signal to image: capturing fine-grained human poses with commodity Wi-Fi. IEEE Commun Lett. 2020;24(4):802–6.

    Article  Google Scholar 

  15. Liu R, Asma KT, Dorrance R, Dasalukunte D, Kristem V, Santana Lopez M, Min A, Azizi S, Park M, Carlton B. An 802.11ba-based wake-up radio receiver with Wi-Fi transceiver integration. IEEE J Solid State Circuits. 2020;55(5):1151–64.

    Article  Google Scholar 

  16. Li Y, Barthelemy J, Sun S, Perez P, Moran B. A case study of Wi-Fi sniffing performance evaluation. IEEE Access. 2020;8(1):129224–35.

    Article  Google Scholar 

  17. Khan M, Hamila R, Hasna M. Optimal group formation in dense Wi-Fi direct net-works for content distribution. IEEE Access. 2019;7(1):161231–45.

    Article  Google Scholar 

  18. Bocanegra C, Kennouche T, Li Z, Favalli L, Felice M, Chowdhury K. E-Fi: evasive Wi-Fi measures for surviving LTE within 5 GHz unlicensed band. IEEE Trans Mob Comput. 2019;18(4):830–44.

    Article  Google Scholar 

  19. Lu C, Xiangli Y, Zhao P, Chen C, Trigoni N, Markham A. Autonomous learning of speaker identity and Wi-Fi geofence from noisy sensor data. IEEE Internet Things J. 2019;6(5):8284–95.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to K. N. Sanjay.

Ethics declarations

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of the topical collection “Cyber Security and Privacy in Communication Networks” guest edited by Rajiv Misra, R K Shyamsunder, Alexiei Dingli, Natalie Denk, Omer Rana, Alexander Pfeiffer, Ashok Patel and Nishtha Kesswani.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sanjay, K.N., Shaila, K. & Venugopal, K.R. Cross Layer Design for Wi-Fi Sensor Network Handling Static and Dynamic Environment Using Local Automate Based Autonomic Network Architecture. SN COMPUT. SCI. 2, 232 (2021). https://doi.org/10.1007/s42979-021-00599-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s42979-021-00599-4

Keywords

Navigation