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Improved self-healing technique for 5G networks using predictive analysis

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Abstract

With the advent of IoT and the seamless advent of the ubiquitous network using the 5G technologies, the ability to provide a continuous service is the requirement of every Internet Service Provider (ISP). The IoT presents a network of humongous network size, troubleshooting and maintaining this network is a challenge, in light of this an automated system to do network diagnostics and predictive self-healing is the need of the current era. The proposed system introduces an automated network diagnostics and self-healing technique for 5G environment using predictive analysis. The performance parameters of the device or network are considered to collect the data and analyze the possible anomalies. When the performance parameters are deviated from the normal ranges, the problems occurred in the network are diagnosed in a productive way and the predictive analysis is done. The time series analysis helps to predict the performance of the network in various time intervals. The proposed technique has been implemented in the live network environment provided by one of the leading ISP and the performance analysis has proven that the predictive analysis and network diagnostics improves the network performance with self-healing in 5G networks.

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Authors and Affiliations

  1. Society for Electronic Transactions & Security, Chennai, India

    T. R. Reshmi

  2. Department of Computer Science Engineering, King Khalid University, Abha, Saudi Arabia

    M. Azath

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  1. T. R. Reshmi
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  2. M. Azath
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This article is part of the Topical Collectio: Special Issue on P2P Computing for Beyond 5G Network and Internet-of-Everything

Guest Editors: P Prakasam, John Ajayan, and Shohel Sayeed

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Reshmi, T.R., Azath, M. Improved self-healing technique for 5G networks using predictive analysis. Peer-to-Peer Netw. Appl. 14, 375–391 (2021). https://doi.org/10.1007/s12083-020-00926-1

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