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SSEER: Segmented sectors in energy efficient routing for wireless sensor network

  • 1174: Futuristic Trends and Innovations in Multimedia Systems Using Big Data, IoT and Cloud Technologies (FTIMS)
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Abstract

Nowadays, wireless sensor network (WSN) is an essential segment in the Internet of Things (IoT) paradigm. Essentially, WSN provides access to location, latest information of different objects of the environment, computing and communication for IoT monitoring. Considering distance as a critical factor, the communication process is energy healing as compared to computing; due to this, energy is found as one of the major constraints for WSN. As per the application, sensor devices may have either limited or unlimited power backup. Hence, they must connect directly from the power supply or battery, which needs energy-efficiency to sustain in the network. In this paper, we propose a segmented sector network that can work efficiently to increase the lifetime of the network. Heterogeneity parameters for sensor nodes are used, normal nodes transmit the information using direct diffusion & advanced nodes participate in the clustering process. With such integration of direct diffusion and clustering, the network lifetime and stability increase significantly by sectoring the network field. Simulation results of the proposed scheme show significant improvement in the energy efficiency by 11% and stability by 19% compared to the Z-SEP protocol.

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References

  1. Roy SK, Roy A, Misra S, Raghuwanshi NS, Obaidat MS (2015) AID: A prototype for agricultural intrusion detection using wireless sensor network. In: 2015 IEEE International conference on communications (ICC), pp 7059–7064

  2. Tyagi S, Tanwar S, Gupta S, Kumar N, Rodrigues J (2014) Selective cluster based temperature monitoring system for homogeneous wireless sensor networks. ZTE Communications 12:22–29

    Google Scholar 

  3. Verma VK, Gupta P, Jha AV, Barbhuiya PN (2017) Recent trends in wireless sensors for medical applications. In: 2017 International conference on communication and signal processing (ICCSP). IEEE

  4. Singh PK, Sharma A (2017) An insight to forest fire detection techniques using wireless sensor networks. In: 2017 4th International conference on signal processing, computing and control (ISPCC), pp 647–653

  5. Malaver A, Motta N, Corke P, Gonzalez F, Passaro VMN, Lamberti F (2015) Development and integration of a solar powered unmanned aerial vehicle and a wireless sensor network to monitor greenhouse gases. Sensors 15:4072–4096

    Article  Google Scholar 

  6. Boubrima A, Bechkit W, Rivano H (2017) Optimal WSN deployment models for air pollution monitoring. IEEE Transactions on Wireless Communications 16:2723–2735

    Article  Google Scholar 

  7. BenSaleh MS, Saida R, Kacem YH, Abid M (2020) Wireless sensor network design methodologies: A survey. Journal of Sensors 2020:1–13

    Article  Google Scholar 

  8. Li Y, Zhao Y, Zhang Y (2019) A spanning tree construction algorithm for industrial wireless sensor networks based on quantum artificial bee colony. EURASIP Journal on Wireless Communications and Networking:2019

  9. Rabiner HW, Anantha C, Hari B (2000) Energy-efficient communication protocol for wireless microsensor networks. In: Proceedings of the 33rd annual hawaii international conference on system sciences. IEEE Comput. Soc

  10. Smaragdakis G, Matta I, Bestavros A (2004) SEP : A stable election protocol for clustered heterogeneous wireless sensor networks

  11. Aderohunmu FA, Deng JD, Others, (2009) An enhanced stable election protocol (sep) for clustered heterogeneous wsn. Department of Information Science, University of Otago, New Zealand

  12. Tyagi S, Gupta SK, Tanwar S, Kumar N (2013) EHE-LEACH: Enhanced heterogeneous LEACH protocol for lifetime enhancement of wireless SNs. In: 2013 International conference on advances in computing, communications and informatics (ICACCI), pp 1485–1490

  13. Open fog reference architecture for fog computing. Open Fog Consortium Architecture Working Group, (2017)

  14. Gupta SK, Kumar S, Tyagi S, Tanwar S (2020) Energy efficient routing protocols for wireless sensor network. 1132, Springer International Publishing

  15. Gupta P, Sharma A (2020) Clustering-based heterogeneous optimized-HEED protocols for WSNs. Soft Computing 24(3):1737–1761

    Article  Google Scholar 

  16. Gou H, Yoo Y, Zeng H (2009) A partition-based LEACH algorithm for wireless sensor networks. In: 2009 Ninth IEEE international conference on computer and information technology, vol 2, pp 40–45

  17. Mahboub A, En-Naimi EM, Arioua M, Ez-Zazi I, El Oualkadi A (2016) Multi-zonal approach clustering based on stable election protocol in heterogeneous wireless sensor networks, In: 2016 4th IEEE international colloquium on information science and technology (CiSt), pp 912–917

  18. Jain N, Trivedi P (2012) An adaptive sectoring and cluster head selection based multi-hop routing algorithm for WSN. In: 2012 Nirma University international conference on engineering (NUiCONE), pp 1–6

  19. Tanwar S, Tyagi S, Kumar N, Obaidat MS (2019) LA-MHR: Learning automata based multilevel heterogeneous routing for opportunistic shared spectrum access to enhance lifetime of WSN. IEEE Systems Journal 13:313–323

    Article  Google Scholar 

  20. Tyagi S, Tanwar S, Kumar N, Rodrigues JJPC (2015) Cognitive radio-based clustering for opportunistic shared spectrum access to enhance lifetime of wireless sensor network. Pervasive and Mobile Computing 22:90–112

    Article  Google Scholar 

  21. Kumar N, Tyagi S, Deng D-J (2014) LA-EEHSC: Learning automata-based energy efficient heterogeneous selective clustering for wireless sensor networks. Journal of Network and Computer Applications 46:264–279

    Article  Google Scholar 

  22. Tyagi S, Kumar N (2013) A systematic review on clustering and routing techniques based upon LEACH protocol for wireless sensor networks

  23. Rishiwal V, Singh O, Tanwar S, Tyagi S, Budhiraja I, Kumar N, Obaidat MS (2018) Base station oriented multi route diversity protocol for wireless sensor networks, In: 2018 IEEE Globecom workshops (GC Wkshps), pp 1–6

  24. Tyagi S, Tanwar S, Kumar N (2015) Learning automata-based coverage oriented clustering in HWSNs, In: 2015 Second international conference on advances in computing and communication engineering, pp 78–83

  25. Dutt S, Kaur G, Agrawal S (2019) Energy efficient sector-based clustering protocol for heterogeneous WSN. Springer, vol 46, pp 117–125

  26. Sundaran K, Ganapathy V, Sudhakara P (2017) Energy minimization in wireless sensor networks by incorporating unequal clusters in multi-sector environment. Cluster Computing, Springer 22:9599–9613

    Article  Google Scholar 

  27. Sudha C, Suresh D, Nagesh A (2020) An enhanced dynamic cluster head selection approach to reduce energy consumption in WSN. Book Series, Springer, pp 215–224

  28. Alghamdi TA (2020) Energy efficient protocol in wireless sensor network: optimized cluster head selection model. Telecommunication Systems 74:331–345

    Article  Google Scholar 

  29. Anandh SJ, Baburaj E (2020) Energy efficient routing technique for wireless sensor networks using ant-colony optimization, wireless personal communications

  30. Arikumar KS, Natarajan V, Satapathy SC (2020) EELTM: An energy efficient lifetime maximization approach for WSN by PSO and fuzzy-based unequal clustering. Arabian Journal for Science and Engineering

  31. Famila S, Jawahar A (2020) Improved artificial bee colony optimization-based clustering technique for WSNs. Wireless Personal Communications 110:2195–2212

    Article  Google Scholar 

  32. Sah DK, Amgoth T (2020) A novel efficient clustering protocol for energy harvesting in wireless sensor networks. Wireless Networks 26:4723–4737

    Article  Google Scholar 

  33. Nori MK, Sharifian S (2020) EDMARA2: a hierarchical routing protocol for EH-WSNs. Wireless Networks:24

  34. Loganathan S, Arumugam J (2019) Energy centroid clustering algorithm to enhance the network lifetime of wireless sensor networks. Multidimensional Systems and Signal Processing 31:829–856

    Article  Google Scholar 

  35. Micheletti M, Mostarda L, Navarra A (2019) CER-CH: Combining Election and Routing Amongst Cluster Heads in Heterogeneous WSNs. IEEE Access 7:125481–125493

    Article  Google Scholar 

  36. Agrawal A, Singh V, Jain S, Gupta RK (2018) GCRP: Grid-cycle routing protocol for wireless sensor network with mobile sink. AEU - International Journal of Electronics and Communications 94:1–11

    Article  Google Scholar 

  37. Faisal S, Javaid N, Javaid A, Khan MA, Bouk SH, Khan ZA (2013) Z-SEP: Zonal-stable election protocol for wireless sensor networks. arxiv:1303.5364

  38. Kumar H, Singh PK (2017) Node energy based approach to improve network lifetime and throughput in wireless sensor networks, Journal of Telecommunication. Electronic and Computer Engineering (JTEC) 9(3–6):79–88

    Google Scholar 

  39. Hong C, Zhang Y, Xiong Z, Xu A, Chen H, Ding W (2018) FADS : Circular/spherical sector based forwarding area division and adaptive forwarding area selection routing protocol in WSNs. Ad Hoc Networks 70:121–134

    Article  Google Scholar 

  40. Sharma R, Sohi BS, Mittal N (2019) Zone-based energy efficient routing protocols for wireless sensor networks. Scalable computing: Practice and experience 20:55–70

    Google Scholar 

  41. C. Intanagonwiwat, R. Govindan, and D. Estrin (2000) Directed diffusion: A scalable and robust communication paradigm for sensor networks. In: Proceedings of the 6th annual international conference on mobile computing and networking, MobiCom ’00, (New York, NY, USA), ACM, pp 56–67

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Correspondence to Sudhanshu Tyagi.

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Gupta, S.K., Kumar, S., Tyagi, S. et al. SSEER: Segmented sectors in energy efficient routing for wireless sensor network. Multimed Tools Appl 81, 34697–34715 (2022). https://doi.org/10.1007/s11042-021-11829-5

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  • DOI: https://doi.org/10.1007/s11042-021-11829-5

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