Security and network performance analysis of coexistence TWDM – NG-PON2, GPON and 10G-EPON systems based on Hill Cipher
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Alaa Hussein Ali
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Razi J. Al-Azawi
Abstract
The challenges of operating legacy, security-related, and future network technologies simultaneously in point-to-point topologies and passive optical networks (PONs) are discussed in this study. We investigate the problems of coexistence for many types of users, such as home, business, industrial, and mobile users. Future access networks will have to support several technologies at once. In order to solve this issue, our paper demonstrates how time and wavelength division multiplexing next-generation PON2 (TWDM-NG-PON2), gigabit passive optical network (GPON), and 10 Gbps Ethernet passive optical networks (10G-EPON) may use triple coexistence multi-PON modules to coexist on the same optical distribution network for deploying of fiber-to-the-X (FTTX) network access. A grayscale image is encrypted at 2*20 Gbps for TWDM-NG-PON2, 2.5 Gbps for GPON and 10 Gbps for 10G-EPON, for a total capacity of symmetric 52.5 Gbps. According to simulation studies, a bidirectional distance fiber with a ratio of splitting 1:112 can be successfully implemented at 40 km. The downstream and upstream receiver sensitivity demonstrated is −24.8, −27.8, −28.6 dB m and −26.8, −23.8, −28.6 dBm for TWDM-NG-PON2, GPON and 10G-EPON, respectively. High security, high capacity, and a sophisticated long-distance networking that delivers efficient usage source and strengthened authenticity network are all provided by the suggested algorithm in coexistence PON.
Acknowledgements
This research was supported by Al-bayan University. We thank our colleagues who provided insight and expertise that greatly assisted the research.
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Research ethics: The local Institutional Review Board deemed the study exempt from review if the IRB specifically exempted the study from review.
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Informed consent: Informed consent was obtained from all individuals included in this study, or their legal guardians or wards.
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Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The authors state no conflict of interest.
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Research funding: None declared.
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Data availability: Not applicable.
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