Skip to main content
Log in

Performance analysis of DSDV and OLSR wireless sensor network routing protocols using FPGA hardware and machine learning

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

Wireless Sensor Network (WSN) is a self-organized network, contains sensor nodes deployed in particular regions to gather the environmental parameters and communicate the information to the base station directly through intermediate nodes. In recent times, WSN has gained attention from wireless device manufacturers, researchers, and users for remotely accessing and monitoring the information in diverse environments. The scalability and routing are the major concerns of the network. Apart from that, the performance of WSN depends on network simulation parameters such as delay, throughput, packet delivery ratio (PDR), and control overhead. The research paper focused on the DSDV and OLSR routing protocol realization on the new hardware platform. The hardware chip of these protocols is designed in Xilinx ISE 14.7 software using VHDL, targeted on Virtex-5 FPGA. The node communication is verified on Modelsim 10.0 simulation software. The FPGA hardware and timing parameters are analyzed for different node clusters (N = 10, 20 …150) configuration. The OLSR routing protocol network performance parameters are used to build the machine learning prediction model using cluster tree regression, random forest regression, multiple regression, and K-means clustering. The K-means clustering predicted 99.12% and 98.50% accuracy in terms of the packet delivery ratio and throughput respectively.

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

Similar content being viewed by others

Abbreviations

AODV:

Adhoc on-Demand Distance Vector

BS:

Base Station.

CPU:

Central Processing Unit.

DSR:

Dynamic State Routing.

DSDV:

Destination-Sequenced Distance-Vector.

DYMO:

Dynamic MANET On-Demand Routing.

FPGA:

Field Programmable Gate Array.

GCLK:

Global Clock.

ISE:

Integrated Synthesis Environment.

IoB:

Input/output Block.

HRP:

Hybrid Routing Protocol.

LUT:

Look Up Table.

MANET:

Mobile Adhoc Network.

MEMS :

Micro-Electro-Mechanical Systems.

MPR:

Multipoint Relay.

ML:

Machine Learning.

MPSoC :

Multiprocessor System on Chip.

NS:

Network Simulator.

OLSR:

Optimized Link State Routing.

PDR:

Packet Delivery Ratio.

QoS:

Quality of Service.

RH :

Routing Overhead.

RTL:

Register Transfer Level.

SN:

Sensor Nodes.

TC:

Transmission Control.

TCP:

Transmission Control Protocol.

VHDL:

Very High-Speed Integrated Circuit Hardware Description Language.

WLAN:

Wireless Local Area Network.

WSN:

Wireless Sensor Network.

VANET:

Vehicular Adhoc Network.

bps:

bits per second.

ns:

nanoseconds.

References

  1. Abba S, Lee JA (2016) FPGA-based design of an intelligent on-chip sensor network monitoring and control using dynamically reconfigurable autonomous sensor agents. Int J Distrib Sens Netw 12(2):4246596. https://doi.org/10.1155/2016/4246596

    Article  Google Scholar 

  2. Angurala M, Bala M, Bamber SS (2020) Performance analysis of modified AODV routing protocol with lifetime extension of wireless sensor networks. IEEE Access 8:10606–10613. https://doi.org/10.1109/ACCESS.2020.2965329

    Article  Google Scholar 

  3. Chavan AA, Kurule DS, Dere PU (2016) Performance analysis of AODV and DSDV routing protocol in MANET and modifications in AODV against black hole attack. Proced Comput Sci 79:835–844. https://doi.org/10.1016/j.procs.2016.03.108

    Article  Google Scholar 

  4. De La Piedra A, Braeken A, Touhafi A (2012) Sensor systems based on FPGAs and their applications: a survey. Sensors 12(9):12235–12264. https://doi.org/10.3390/s120912235

    Article  Google Scholar 

  5. Hamerly G, Drake J (2015) Accelerating Lloyd’s algorithm for k-means clustering. In Partitional clustering algorithms (pp. 41-78). Springer Cham. https://doi.org/10.1007/978-3-319-09259-1_2

  6. Joshi P, Singh G, Raghuvanshi AS (2020) Comparative study of different routing protocols for IEEE 802.15. 4-enabled Mobile sink wireless sensor network. In Advances in VLSI, Communication, and Signal Processing (pp. 161–170). Springer, Singapore. https://doi.org/10.1007/978-981-32-9775-3_16

  7. Jubair MA, Khaleefah SH, Budiyono A, Mostafa SA, Mustapha A (2018) Performance evaluation of AODV and OLSR routing protocols in MANET environment. Int J Adv Sci Eng Inf Technol 8(4):1277–1283

    Article  Google Scholar 

  8. Kashyap VK, Astya R, Nand P, Pandey G (2017) Comparative study of AODV and DSR routing protocols in wireless sensor network using NS-2 simulator. In 2017 International Conference on Computing, Communication and Automation (ICCCA) (pp. 687-690). IEEE. doi: https://doi.org/10.1109/CCAA.2017.8229889.

  9. Kaur A (2014) Mobility model based performance analysis of DSDV mobile ad hoc routing protocol. In International Conference on Recent Advances and Innovations in Engineering (ICRAIE-2014) (pp. 1-7). IEEE. doi: https://doi.org/10.1109/ICRAIE.2014.6909326.

  10. Keerthiga R, Kalpana S, Gomathi M (2019) Energy efficiency in cognitive wireless sensor network using DSDV protocol. In 2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN) (pp. 1-6). IEEE. doi: https://doi.org/10.1109/ICSCAN.2019.8878767.

  11. Kumar DP, Amgoth T, Annavarapu CSR (2019) Machine learning algorithms for wireless sensor networks: a survey. Inform Fusion 49:1–25. https://doi.org/10.1016/j.inffus.2018.09.013

    Article  Google Scholar 

  12. Kumar A, Sharma P, Gupta MK, Kumar R (2018) Machine learning based resource utilization and pre-estimation for network on Chip (NoC) communication. Wirel Pers Commun 102(3):2211–2231. https://doi.org/10.1007/s11277-018-5376-3

    Article  Google Scholar 

  13. Kumar H, Arora H, Singla RK (2011) Simulation analysis of optimized link state routing protocol in wireless sensor networks. In 2011, International Conference on Emerging Trends in Networks and Computer Communications (ETNCC) (pp. 192-194). IEEE. doi: https://doi.org/10.1109/ETNCC.2011.5958514.

  14. Kumar P, Babu MN, Jain V (2017) Analysis of energy efficiency in WSN by considering SHM application. In IOP Conference Series: Materials Science and Engineering (Vol. 225, no. 1, p. 012231). IOP publishing. doi:https://doi.org/10.1088/1757-899X/225/1/012231

  15. Liao J, Singh BK, Khalid MA, Tepe KE (2013) FPGA based wireless sensor node with customizable event-driven architecture. EURASIP J Embed Syst 2013(1). https://doi.org/10.1186/1687-3963-2013-5

  16. Morshed MM, Rahman MU, Rahman MH, Islam MR (2012) Performance comparison of TCP variants over AODV, DSDV, DSR, OLSR in NS-2. In 2012 International Conference on Informatics, Electronics & Vision (ICIEV) (pp. 1069-1074). IEEE. doi: https://doi.org/10.1109/ICIEV.2012.6317478.

  17. Mohapatra S, Kanungo P (2012) Performance analysis of AODV, DSR, OLSR and DSDV routing protocols using NS2 simulator. Proced Eng 30:69–76. https://doi.org/10.1016/j.proeng.2012.01.835

    Article  Google Scholar 

  18. Mouiz A, Badri A, Baghdad A, Sahel A (2019) Performance evaluation of OLSR and AODV routing protocols with different parameters in Mobile ad-hoc networks using NS2 simulator. In Proceedings of the 2019, 5th International Conference on Computer and Technology Applications (pp. 134-139). https://doi.org/10.3390/sym11111409.

  19. Mouiz A, Badri A, Baghdad A, Sahel A (2019) Analysis of energy consumption and evaluation of metric parameters of routing protocols in ad hoc (MANET) networks using: NS2 simulator. Journal of Communications, 14(11). doi:https://doi.org/10.12720/jcm.14.11.1067-1074.

  20. Mostafa SA, Mustapha A, Ramli AA, Jubair MA, Hassan MH, Abbas AH (2020). Comparative analysis to the performance of three Mobile ad-hoc network routing protocols in time-critical events of search and rescue missions. In International Conference on Applied Human Factors and Ergonomics (pp. 117-123). Springer, Cham. https://doi.org/10.1007/978-3-030-51064-0_16.

  21. Muruganantham N, El-Ocla H (2020) Routing using genetic algorithm in a wireless sensor network. Wirel Pers Commun 111:1–30. https://doi.org/10.1007/s11277-019-07011-8

    Article  Google Scholar 

  22. Purkar SV, Deshpande RS (2018) Energy efficient clustering protocol to enhance performance of heterogeneous wireless sensor network: EECPEP-HWSN. Journal of Computer Networks and Communications 2018:1–12. https://doi.org/10.1155/2018/2078627

    Article  Google Scholar 

  23. Salem O, Guerassimov A, Mehaoua A, Marcus A, Furht B (2013) Anomaly detection scheme for medical wireless sensor networks. In Handbook of medical and healthcare technologies (pp. 207–222). Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8495-0_8.

  24. Shabbir N, Hassan SR (2017) Routing protocols for wireless sensor networks (WSNs). In Wireless Sensor Networks-Insights and Innovations. Intech open, pp (36-40).

  25. Spaho E, Ikeda M, Barolli L, Xhafa F (2013) Performance comparison of OLSR and AODV protocols in a VANET crossroad scenario. In Information Technology Convergence (pp. 37–45). Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6996-0_5.

  26. Varshovi H, Kavian YS, Ansari-Asl K (2019) Design and implementing wireless multimedia sensor network for movement detection using FPGA local co-processing. Multimed Tools Appl 78(13):17413–17435. https://doi.org/10.1007/s11042-018-7104-0

    Article  Google Scholar 

  27. Waharte S, Boutaba R, Iraqi Y, Ishibashi B (2006) Routing protocols in wireless mesh networks: challenges and design considerations. Multimed Tools Appl 29(3):285–303. https://doi.org/10.1007/s11042-006-0012-8

    Article  Google Scholar 

  28. Yadav S, Yadav RS (2016) A review on energy-efficient protocols in wireless sensor networks. Wirel Netw 22(1):335–350. https://doi.org/10.1007/s11276-015-1025-x

    Article  Google Scholar 

  29. Yick J, Mukherjee B, Ghosal D (2008) Wireless sensor network survey. Comput Netw 52(12):2292–2330. https://doi.org/10.1016/j.comnet.2008.04.002

    Article  Google Scholar 

  30. Yang T, Barolli L, Ikeda M, Xhafa F, Durresi A (2009) Performance analysis of olsr protocol for wireless sensor networks and comparison evaluation with AODV protocol. In 2009 International Conference on Network-Based Information Systems (pp. 335-342). IEEE. doi: https://doi.org/10.1109/NBiS.2009.35.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Arpit Jain.

Ethics declarations

Conflict of interest

The authors declare that there is no conflict of interest regarding the publication of this paper.

Additional information

Publisher’s note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gupta, N., Jain, A., Vaisla, K.S. et al. Performance analysis of DSDV and OLSR wireless sensor network routing protocols using FPGA hardware and machine learning. Multimed Tools Appl 80, 22301–22319 (2021). https://doi.org/10.1007/s11042-021-10820-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-021-10820-4

Keywords

Navigation