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Distributed computing and big data techniques for efficient fault detection and data management in wireless networks

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Abstract

Due to social media, internet websites, and cellular networks, the world is undergoing a digital avalanche. Extensive information will mask this pattern, emerging quickly and in many ways. Big data analytics will filter large amounts of unprocessed data to provide more manageable data to help parties make intelligent decisions. This research demonstrates how large geographical datasets are essential to numerous cutting-edge wireless communication technologies. We also argue that geospatial and spatio-temporal concerns matter differently in massive datasets than interpersonal issues. We present three significant geospatial information use cases with distinct architectural and analytical challenges. Next, using map-based Reduce computing, we offer our research on developing highly available multi-processing systems for geographical information on Hadoop. Our results show that Hadoop allows for highly extendable spatial data analysis methodologies. However, designing such applications requires specialized skills, stressing the need for simpler alternatives.

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References

  • Borkar, V.R., Carey, M.J., Li, C.: Big data platforms, XRDS: crossroads. ACM Magaz. Stud. 19, 44–49 (2012)

    Google Scholar 

  • Gani, A., Siddiqa, S., Shamshirband, F.: Hanum, A survey on indexing techniques for big data: taxonomy and performance evaluation. Know. Inf. Syst. 46, 241–284 (2016)

    Article  Google Scholar 

  • Hapsari, W., et al.: Minimization of drive tests solution in 3GPP. IEEE Commun. Mag.commun. Mag. 50(6), 28–36 (2012)

    Article  Google Scholar 

  • Kachhoria, R., Jaiswal, S., Lokhande, M., Rodge, J.: Lane detection and path prediction in autonomous vehicle using deep learning. In: Intelligent edge computing for cyber physical applications, 111–127 (2023)

  • Kandavalli, S.R., Edberk, A.S., Rajendran, D.K., Rajagopal, V.: A progressive review on wire arc additive manufacturing: mechanical properties, metallurgical and defect analysis. Adv. Addit. Manuf. Processes 1, 178 (2021). https://doi.org/10.2174/9789815036336121010014

    Article  Google Scholar 

  • Landset, S., Khoshgoftaar, T.M., Richter, A.N., Hasanin, T.: A survey of open source tools for machine learning with big data in the Hadoop ecosystem. J. Big Data 2, 1–36 (2015)

    Article  Google Scholar 

  • Lee, K., Jung, K., Park, J., Kwon, D.: ARLS: a MapReduce-based output analysis tool for large-scale simulations. Adv. Eng. Softw.softw. 95, 28–37 (2016)

    Article  Google Scholar 

  • Lemoudden, M., Ouahidi, B.E.: Managing cloud-generated logs using big data technologies. In: 2015 International conference on wireless networks and mobile communications (WINCOM), IEEE, pp. 1–7 (2015)

  • Leonid, T.T., Kanna, H., Claudia Christy, V.J., Hamritha, A.S., Lokesh, C.: Human wildlife conflict mitigation using YOLO algorithm. In: 2023 Eighth international conference on science technology engineering and mathematics (ICONSTEM), Chennai, India, 2023, pp. 1–7, https://doi.org/10.1109/ICONSTEM56934.2023.10142629.

  • Mainetti, L., Patrono, L., Vilei, A.: Evolution of wireless sensor networks towards the internet of things: a survey. In: Proceedings of 19th international conference on software, telecommunications and computer networks, pp. 1–6 (2011)

  • Markkandan, S., Logeshwaran, R., Venkateswaran, N.: Analysis of precoder decomposition algorithms for MIMO system design. IETE J. Res. 69, 1–8 (2021). https://doi.org/10.1080/03772063.2021.1920848

    Article  Google Scholar 

  • Pyne, S., Rao, B.P., Rao, S.B.: Big data analytics: methods and applications. Springer, Berlin (2016)

    Google Scholar 

  • Qadir, J., Ahad, N., Mushtaq, E., Bilal, M.: SDNs, clouds, and big data: new opportunities. In: 2014 12th international conference on frontiers of information technology, IEEE, pp. 28–33 (2014)

  • Sayrac, B., et al.: Cognitive radio systems specific for IMT systems: operator’s view and perspectives. Telecommun. Policy 37(2–3), 154–166 (2013)

    Article  Google Scholar 

  • Shemer, J., Neches, P.: The genesis of a database computer. Computer 17, 42–56 (1984)

    Article  Google Scholar 

  • Singh, D., Reddy, C.K.: A survey on platforms for big data analytics. J. Big Data 2, 8 (2014). https://doi.org/10.1186/s40537-014-0008-6

    Article  Google Scholar 

  • Vijayan, V.P., Juvanna, I., Maheshwara Rao, V.V.R., Raseena, K.M., Sundareswari, K., Jayachitra, S.: Intelligent exploration strategy for a mobile robot to reduce the repeated searches in an unknown environment. Int. J. Syst. Assur. Eng. Manag.Manag., 1-62022). https://doi.org/10.1007/s13198-022-01776-1

  • White, T.: Hadoop: the definitive guide. O'Reilly Media, Inc., (2012)

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Authors and Affiliations

  1. Department of Computer Science and Engineering, MLR Institute of Technology, Dundigal, Hyderabad, Telangana, 500043, India

    Ajmeera Kiran

  2. School of Computer Science and Engineering, Vellore Institute of Technology, Chennai Campus, Chennai, India

    P. N. Renjith

  3. Department of Computer Science Engineering, Jain (Deemed to Be University), Bangalore, India

    Sapna Gupta

  4. Computer Engineering Department, Pimpri Chinchwad College of Engineering, Pune, Maharashtra, India

    Srinivas Ambala

  5. Department of ECE, SRM Valliammai Engineering College, Chennai, Tamil Nadu, India

    Preethi Sambandam Raju

  6. Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur Dist., Andhra Pradesh, 522502, India

    Drakshayani Sriramsetti

Authors
  1. Ajmeera Kiran
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  2. P. N. Renjith
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  3. Sapna Gupta
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  4. Srinivas Ambala
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  5. Preethi Sambandam Raju
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  6. Drakshayani Sriramsetti
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Contributions

Dr AK: Contributed to conceptualization, literature review, data analysis, and manuscript writing. RPN: Provided guidance, conceptualization, methodology development, and manuscript revisions. SG: Assisted with research design, data collection, analysis, and manuscript revisions. Dr. SA: Involved in data preprocessing, algorithm implementation, visualization, and manuscript writing. Dr. PSR: Supported in data collection, AI algorithm implementation, evaluation, and manuscript revisions. DS: Assisted with data analysis, visualization, and manuscript writing.

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Correspondence to Ajmeera Kiran.

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Kiran, A., Renjith, P.N., Gupta, S. et al. Distributed computing and big data techniques for efficient fault detection and data management in wireless networks. Opt Quant Electron 55, 1200 (2023). https://doi.org/10.1007/s11082-023-05502-4

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