Wireless sensor network–based delay minimization framework for IoT applications

Personal and Ubiquitous Computing (2021)Cite this article

Abstract

In IoT, the major challenge is processing huge amount of data from different types of sensors and to achieve a reliable data transmission in the sensor network. This makes it a necessity in enhancing Quality of Service, to acquire real-time service with assured quality. The major problem faced in the sensor network is delay, as more time is required to set up a connection with limited spectrum for maintaining numerous state information per connection. Finding the optimal route with efficient bandwidth is not ideal using an existing routing algorithm, both in ad hoc and cognitive network. As a result, a protocol is proposed in this paper to minimize the delay and maximize the effective spectrum allocation. The proposed algorithm is implemented in real-time traffic monitoring application using network simulator to estimate the quality of service. The performance of the proposed system is compared with the existing systems in terms of throughput and delay. The delay decreases by 3% approximately when compared with the existing techniques.

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Abbreviations

IoT:

Internet of things

MANET :

mobile ad hoc networks

AODV:

ad hoc on-demand distance vector routing

DSR:

dynamic source routing

RPL:

routing protocol for low-power networks

LOADng:

lightweight on-demand ad hoc distance-vector routing protocol

CARP:

channel aware routing protocol

MANET:

mobile ad hoc networks

TDMA:

time-division multiple access

DSR:

dynamic source routing

IDS:

intrusion detection system

GAQoS(DM)-AODV:

genetic algorithm quality of service delay minimization-AODV

QoS:

quality of service

SORP:

spectrum on-demand routing protocol

SUMO:

Simulation of Urban MObility

References

  1. 1.

    Muthuramalingam S, Bharathi A, Rakesh Kumar S, Gayathri N, Sathiyaraj R, Balamurugan B (2019) IoT based intelligent transportation system (IoT-ITS) for global perspective: a case study. In: Internet of Things and Big Data Analytics for Smart Generation. Springer, Cham, pp 279–300

    Google Scholar 

  2. 2.

    Dhingra P, Gayathri N, Kumar SR, Singanamalla V, Ramesh C, Balamurugan B (2020) Internet of things–based pharmaceutics data analysis. Emergence of Pharmaceutical Industry Growth with Industrial IoT Approach. Academic Press, Cambridge, pp 85–131

    Google Scholar 

  3. 3.

    Sarhan QI (2018) Internet of things: a survey of challenges and issues. Int J Internet Things Cyber-Assurance 1(1):40–75

    Article  Google Scholar 

  4. 4.

    Kodabagi MM, Patil SB, Patil BB (2016) QoS challenges in wireless sensor networks. J Eng Technol Innov 4:92–94

    Google Scholar 

  5. 5.

    Alahari HP, Yalavarthi SB (2017) A survey on network routing protocols in internet of things (IOT). Int J Comput Appl 160:0975–8887

    Google Scholar 

  6. 6.

    Sethi P, Sarangi SR (2017) Internet of things: architectures, protocols, and applications. J Electr Comput Eng 03:9324035

    Google Scholar 

  7. 7.

    Patel N, Pawar A, Shekokar N (2015) A survey on routing protocols for MANET. Int J Comput Appl 110:0975–8887

    Google Scholar 

  8. 8.

    Priyanka M, Lokhande APT (2015) Maximization of lifetime and minimization of delay for performance enhancement of WSN. Int J Bus Res Dev 4:9–16

    Google Scholar 

  9. 9.

    Kumar SR, Gayathri N (2016) Trust based data transmission mechanism in MANET using sOLSR. In: Annual Convention of the Computer Society of India. Springer, Singapore, pp 169–180

    Google Scholar 

  10. 10.

    Kumar SR, Gayathri N, Balusamy B (2019) Enhancing network lifetime through power-aware routing in MANET. Int J Internet Technol Secured Trans 9(1-2):96–111

    Article  Google Scholar 

  11. 11.

    Xiao L, Wang Z (2013) Internet of things: a new application for intelligent traffic monitoring system. J Netw 6:887–894

    Google Scholar 

  12. 12.

    Devi M, Deka D (2015) A survey on routing protocols for cognitive radio networks. Int J Eng Res Technol 4:2278-0181

    Google Scholar 

  13. 13.

    Ghosh K, Nath A (2015) Cognitive radio networks: a comprehensive study on scope and applications. Int J Innov Res Adv Eng 2:2349–2763

    Google Scholar 

  14. 14.

    Ali A, Iqbal M, Baig A, Wang X (2011) Routing technique in cognitive radio network: a survey. Int J Wirel Mobil Netw 3(3):96–110

    Article  Google Scholar 

  15. 15.

    Abdelaziza S, ElNainay M (2011) Survey of routing protocols in cognitive radio networks. Int J 2

  16. 16.

    El Morabit Y, Mrabti F, Abarkan EH. Cognitive radio spectrum allocation using genetic algorithm. IEEE transaction- Third International Workshop on RFID And Adaptive Wireless Sensor Networks (RAWSN), pp 7173287

  17. 17.

    Yan G, Lv Y, Wang Q, Geng Y (2014) Routing algorithm based on delay rate in cognitive radio network. J Netw 9:948–955

    Google Scholar 

  18. 18.

    Razi A, Valehi A, Bentley E (2014) Delay minimization by adaptive framing policy in cognitive sensor networks. IEEE Trans 6:1558–2612

    Google Scholar 

  19. 19.

    Patil DP, Wadhai VM (2011) Improved algorithm for Mac Layer Spectrum Sensing in Cognitive Radio Networks From Dynamic Spectrum Management Perspective. International Journal of Computer Networking, Wireless and Mobile Communications (IJCNWMC) 4(6):75-90

  20. 20.

    Sakthivel RK, Nagasubramanian G, Al-Turjman F, Sankayya M (2020) Core-level cybersecurity assurance using cloud-based adaptive machine learning techniques for manufacturing industry. Trans Emerg Telecommun Technol. https://doi.org/10.1002/ett.3947

    Article  Google Scholar 

  21. 21.

    Kanhere SK, Goudar M, Wadhai VM (2012) End-to-end delay optimization in wireless sensor network (WSN). Int J Smart Sensors Ad Hoc Netw 1:2248–9738

    Google Scholar 

  22. 22.

    Aiswariya Milan K, Ramesh S (2015) QoS enhanced scheduling framework for IoT using LTE-A, International Journal of Advanced Research in Computer. Eng Technol 4:4273–4276

    Google Scholar 

  23. 23.

    Zibakalam V, Hossein Kahaei M (2012) Increasing throughput and reducing delay in wireless sensor networks using interference alignment. Int J Commun Netw Syst Sci 5:90–97

    Google Scholar 

  24. 24.

    Anbarasi R, Kumutha D (2015) Delay minimization in cognitive mesh networks using recursive algorithm in DORP protocol. Int J Adv Res Electr Electron Instrum 4:2278–8875

    Google Scholar 

  25. 25.

    Mohammed AA, Nagib G (2012) Optimal routing in ad-hoc network using genetic algorithm. Int J Adv Netw Appl 3(5):1323–1328

    Google Scholar 

  26. 26.

    Masum AKM, Shahjalal M, Faruque F, Sarker IH (2011) Solving the vehicle routing problem using genetic algorithm. Int J Adv Comput Sci Appl 2(7):126–131

    Google Scholar 

  27. 27.

    Miao J, Hasan O, Mokhtar SB, Brunie L, Yim K (2013) An investigation on the unwillingness of nodes to participate in mobile delay tolerant network routing. Int J Inf Manag 33:252–262

    Article  Google Scholar 

  28. 28.

    Lebiba FZ, Mellah H, Drias H (2017) Enhancing information source selection using a genetic algorithm and social tagging. Int J Inf Manag 37(6):741–749

    Article  Google Scholar 

  29. 29.

    Li J-Y, Qiao S, Harrison S, Li X (2017) Utilizing an interpersonal communication framework to understand information behaviors involved in HIV disclosure. Int J Inf Manag 37:250–256

    Article  Google Scholar 

  30. 30.

    Li D, Deng L, Lee M, Wang H (2019) IoT data feature extraction and intrusion detection system for smart cities based on deep migration learning. Int J Inf Manag 49:533–545

    Article  Google Scholar 

  31. 31.

    Alkhayyat A, Thabit AA, Al-Mayali FA, Abbasi QH (2019) WBSN in IoT health-based application: toward delay and energy consumption minimization. J Sensors 2019:1–14

    Article  Google Scholar 

  32. 32.

    Mudasser AW, Rasool SM, Gafoor SAAA. An energy efficient routing protocol for WSN assisting IoT

  33. 33.

    Bhandari S, Sharma SK, Wang X (2017) Latency minimization in wireless IoT using prioritized channel access and data aggregation. In: GLOBECOM 2017-2017 IEEE Global Communications Conference. IEEE, Singapore, pp 1-6

  34. 34.

    Bounsiar S, Benhamida FZ, Henni A, Ipiña DLD, Mansilla DC (2019) How to enable delay tolerant network solutions for internet of things: from taxonomy to open challenges. Multidiscip Digit Publishing Inst Proc 31(1):24

    Google Scholar 

  35. 35.

    Lafta HA, Al-Salih AMMS (2014) Efficient routing protocol in the mobile ad-hoc network (MANET) by using genetic algorithm (GA). Int J Comput Eng 16(1):47–54

    Google Scholar 

  36. 36.

    Venkatesh S, Mehata KM (2014) A fault tolerant system based on genetic algorithm for target tracking in wireless sensor networks. Int J Comput Appl Technol Re 3(7):434–438

    Google Scholar 

  37. 37.

    Rieck D, Schünemann B, Radusch I (2015) Advanced Traffic Light Information in OpenStreetMap for Traffic Simulations. Modeling Mobility with Open Data. Springer, Cham, pp 25–34

    Google Scholar 

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Author information

Affiliations

  1. Department of Information Technology, Thiagarajar College of Engineering, Madurai, India

    Muthuramalingam Sankayya

  2. School of Computing Science and Engineering, Galgotias University, Greater Noida, India

    Rakesh kumar Sakthivel & N. Gayathri

  3. Artificial Intelligence Dept., Research Centre for AI and IoT, Near East University, Nicosia, Mersin 10, Turkey

    Fadi Al-Turjman

Authors
  1. Muthuramalingam Sankayya
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  2. Rakesh kumar Sakthivel
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  3. N. Gayathri
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  4. Fadi Al-Turjman
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Corresponding author

Correspondence to N. Gayathri.

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Cite this article

Sankayya, M., Sakthivel, R.k., Gayathri, N. et al. Wireless sensor network–based delay minimization framework for IoT applications. Pers Ubiquit Comput (2021). https://doi.org/10.1007/s00779-020-01517-w

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Keywords

  • Quality of service
  • Delay
  • Throughput
  • Mobile ad hoc network
  • Cognitive radio network