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Routing and Data Aggregation Techniques in Wireless Sensor Networks: Previous Research and Future Scope

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Data Science and Communication (ICTDsC 2023)

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Abstract

Wireless sensor networks (WSNs) consist of a small-sized large number of sensor nodes. The primary task of these sensor nodes is to sense the required event in a specific area of interest. The sensor nodes can be installed in areas where it is difficult for human beings to reach easily. WSNs have a huge number of applications such as agriculture monitoring, habitat monitoring, healthcare monitoring, volcanic erupted areas, security, and battlefield. As the sensor nodes are very small in size, they come up with very limited capability for processing the data. The power backup for the sensor nodes is very less due to which the sensors drain out at a very high speed. Draining of sensor nodes decreases the lifetime of the sensor network, so the network failure rate is very high in WSNs. The sensor nodes are generally close to each other, and because of that, they sense redundant data from the environment. To avoid forwarding redundant data to the base station, various routing and data aggregation techniques are used. Data aggregation is one of the very effective energy-efficient techniques used in WSNs. This technique helps in removing redundant data from the sensed data. This research paper will discuss various data aggregation techniques used in WSNs.

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References

  1. Patel NR, Kumar S (2018) Wireless sensor networks’ challenges and future prospects. In: Proceedings 2018 international conference on system modeling & advancement in research trends, SMART 2018, pp 60–65. https://doi.org/10.1109/SYSMART.2018.8746937

  2. Zhang P, Wang J, Guo K, Wu F, Min G (2018) Multi-functional secure data aggregation schemes for WSNs. Ad Hoc Netw 69:86–99. https://doi.org/10.1016/J.ADHOC.2017.11.004

    Article  Google Scholar 

  3. Tripathi A, Gupta HP, Dutta T, Mishra R, Shukla KK, Jit S (2018) Coverage and connectivity in WSNs: a survey, research issues and challenges. IEEE Access 6:26971–26992. https://doi.org/10.1109/ACCESS.2018.2833632

    Article  Google Scholar 

  4. Biradar M, Mathapathi B (2021) Secure, reliable and energy efficient routing in WSN: a systematic literature survey. In: Proceedings 2021 1st international conference on advances in electrical, computing, communication and sustainable technologies ICAECT 2021. https://doi.org/10.1109/ICAECT49130.2021.9392561

  5. Qubbaj N, Taleb AA, Salameh W (2020) Review on LEACH protocol. In: 2020 11th International conference on information and communication systems ICICS 2020, pp 414–419. https://doi.org/10.1109/ICICS49469.2020.239516

  6. Lindsey S, Raghavendra CS (2002) PEGASIS: power-efficient gathering in sensor information systems. IEEE Aerosp Conf Proc 3:1125–1130. https://doi.org/10.1109/AERO.2002.1035242

    Article  Google Scholar 

  7. Pham T, Kim EJ, Moh M (2004) On data aggregation quality and energy efficiency of wireless sensor network protocols—extended summary. In: Proceedings—first international conference broadband networks, BroadNets, pp 730–732. https://doi.org/10.1109/BROADNETS.2004.51

  8. Lee S, Noh Y, Kim K (2013) Key schemes for security enhanced TEEN routing protocol in wireless sensor networks. Int J Distrib Sens Netw 9(6). https://doi.org/10.1155/2013/391986

  9. Bhushan B, Sahoo G (2019) Routing protocols in wireless sensor networks. Stud Comput Intell 776:215–248. https://doi.org/10.1007/978-3-662-57277-1_10/COVER

    Article  Google Scholar 

  10. Mangali C (2019) Improving wireless sensor network lifetime using self-organizing protocol. Int J Sci Res Sci Technol 6(4):330–338. https://doi.org/10.32628/IJSRST196462

    Article  Google Scholar 

  11. Darabkh KA, El-Yabroudi MZ, El-Mousa AH (2019) BPA-CRP: a balanced power-aware clustering and routing protocol for wireless sensor networks. Ad Hoc Netw 82:155–171. https://doi.org/10.1016/J.ADHOC.2018.08.012

    Article  Google Scholar 

  12. Kareem H, Jameel H (2018) Maintain load balancing in wireless sensor networks using virtual grid based routing protocol. In: ICOASE 2018—international conference on advanced science and engineering, pp 227–232. https://doi.org/10.1109/ICOASE.2018.8548929

  13. Wang NC, Hsu WJ (2020) Energy efficient two-tier data dissemination based on Q-learning for wireless sensor networks. IEEE Access 8:74129–74136. https://doi.org/10.1109/ACCESS.2020.2987861

    Article  Google Scholar 

  14. Das I, Shaw RN, Das S (2021) Location-based and multipath routing performance analysis for energy consumption in wireless sensor networks. Lect Notes Electr Eng 661:775–782. https://doi.org/10.1007/978-981-15-4692-1_59/COVER

    Article  Google Scholar 

  15. Abdulai JD, Adu-Manu KS, Katsriku FA, Engmann F (2022) A modified distance-based energy-aware (mDBEA) routing protocol in wireless sensor networks (WSNs). J Ambient Intell Humaniz Comput 2022:1–23. https://doi.org/10.1007/S12652-021-03683-Y

    Article  Google Scholar 

  16. William P, Badholia A, Verma V, Sharma A, Verma A (2022) Analysis of data aggregation and clustering protocol in wireless sensor networks using machine learning. Lect Notes Data Eng Commun Technol 116:925–939. https://doi.org/10.1007/978-981-16-9605-3_65/COVER

    Article  Google Scholar 

  17. Shahina K, Vaidehi V (2019) Clustering and data aggregation in wireless sensor networks using machine learning algorithms. In: Proceedings 2018 international conference on recent trends in advance computing ICRTAC-CPS 2018, pp 109–115. https://doi.org/10.1109/ICRTAC.2018.8679318

  18. Sharifi SS, Barati H (2021) A method for routing and data aggregating in cluster-based wireless sensor networks. Int J Commun Syst 34(7):e4754. https://doi.org/10.1002/DAC.4754

    Article  Google Scholar 

  19. Nguyen NT, Liu BH, Pham VT, Luo YS (2016) On maximizing the lifetime for data aggregation in wireless sensor networks using virtual data aggregation trees. Comput Netw 105:99–110. https://doi.org/10.1016/J.COMNET.2016.05.022

    Article  Google Scholar 

  20. Prathima EG, Prakash TS, Venugopal KR, Iyengar SS, Patnaik LM (2016) SDAMQ: secure data aggregation for multiple queries in wireless sensor networks. Procedia Comput Sci 89:283–292. https://doi.org/10.1016/J.PROCS.2016.06.060

    Article  Google Scholar 

  21. Sasirekha S, Swamynathan S (2017) Cluster-chain mobile agent routing algorithm for efficient data aggregation in wireless sensor network. J Commun Netw 19(4):392–401. https://doi.org/10.1109/JCN.2017.000063

    Article  Google Scholar 

  22. Wang T, Qin X, Ding Y, Liu L, Luo Y (2017) Privacy-preserving and energy-efficient continuous data aggregation algorithm in wireless sensor networks. Wirel Pers Commun 98(1):665–684. https://doi.org/10.1007/S11277-017-4889-5

  23. Mosavvar I, Ghaffari A (2018) Data aggregation in wireless sensor networks using firefly algorithm. Wirel Pers Commun 104(1):307–324. https://doi.org/10.1007/S11277-018-6021-X

  24. Hu S, Liu L, Fang L, Zhou F, Ye R (2020) A novel energy-efficient and privacy-preserving data aggregation for WSNs. IEEE Access 8:802–813. https://doi.org/10.1109/ACCESS.2019.2961512

    Article  Google Scholar 

  25. Idrees AK, Al-Qurabat AKM, Jaoude CA, Laftah Al-Yaseen W (2019) Integrated divide and conquer with enhanced k-means technique for energy-saving data aggregation in wireless sensor networks. In: 2019 15th International wireless communications and mobile computing conference IWCMC 2019, pp 973–978. https://doi.org/10.1109/IWCMC.2019.8766784

  26. Babu MV, Alzubi JA, Sekaran R, Patan R, Ramachandran M, Gupta D (2020) An improved IDAF-FIT clustering based ASLPP-RR routing with secure data aggregation in wireless sensor network. Mob Netw Appl 26(3):1059–1067. https://doi.org/10.1007/S11036-020-01664-7

  27. Yun WK, Yoo SJ (2021) Q-Learning-based data-aggregation-aware energy-efficient routing protocol for wireless sensor networks. IEEE Access 9:10737–10750. https://doi.org/10.1109/ACCESS.2021.3051360

    Article  Google Scholar 

  28. Pham V-T, Nguyen TN, Liu B-H, Thai MT, Dumba B, Lin T (2022) Minimizing latency for data aggregation in wireless sensor networks: an algorithm approach. ACM Trans Sens Netw 18(3):1–21. https://doi.org/10.1145/3450350

    Article  Google Scholar 

  29. Tan HÖ, Körpeoǧlu I (2003) Power efficient data gathering and aggregation in wireless sensor networks. ACM SIGMOD Rec 32(4):66–71. https://doi.org/10.1145/959060.959072

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Chandigarh University, Mohali, Punjab, India

    Navjyot Kaur & D. Vetrithangam

Authors
  1. Navjyot Kaur
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  2. D. Vetrithangam
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Correspondence to Navjyot Kaur .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Porto (FEUP), Porto, Portugal

    João Manuel R. S. Tavares

  2. National Institute of Telecommunications (INATEL), Santa Rita do Sapucaí, Minas Gerais, Brazil

    Joel J. P. C. Rodrigues

  3. Siliguri Institute of Technology, Siliguri, West Bengal, India

    Debajyoti Misra

  4. Siliguri Institute of Technology, Siliguri, West Bengal, India

    Debasmriti Bhattacherjee

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Kaur, N., Vetrithangam, D. (2024). Routing and Data Aggregation Techniques in Wireless Sensor Networks: Previous Research and Future Scope. In: Tavares, J.M.R.S., Rodrigues, J.J.P.C., Misra, D., Bhattacherjee, D. (eds) Data Science and Communication. ICTDsC 2023. Studies in Autonomic, Data-driven and Industrial Computing. Springer, Singapore. https://doi.org/10.1007/978-981-99-5435-3_51

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