Leena Sameer Baddour

Background: The telecommunication industry is currently witnessing an unparalleled growth in traffic data with a concomitant growth in the complexity of networks. As operators seek to achieve high availability of the networks, it is almost compulsory to employ the BDA for improved quality of service and increased operational performance. Objective: The study aims to provide a systematic review of the deployment of BDA in enhancing the primary characteristic indicators of telecommunications networks, to include availability of upgraded latency and throughput levels and network dependability. Methods: The research method used was summed up by quantitative analyses of the key performance parameters of the networks, along with the qualitative results of case studies conducted with major telecommunications operators. Information was collected from multiple networks as well as analyzed with the use of machine learning to be able to predict possible performance issues. Results: The study demonstrates that there is the possibility for reducing latency utilizing BDA with enhancements of up to 40%. In addition, the throughput has been raised by an average of 30% and the predictable analytics lead to 25% reducing in network downtime to improve the reliability and satisfaction of the user experience. Conclusion: The information provided in this study highlights the importance of Big Data Analytics for the telecommunication industry, proving that the proper integration can bring tangible improvements to the existing networks. One future development that constitutes the need for innovative analytical technologies is the rise in data traffic and sophisticated network requirements.

  Background: Quantum computing has posed a profound threat to the classical cryptographic systems as it is advancing at an exponential rate with the help of quantum algorithms like Shor’s and Grover’s which can easily decipher the Rivest–Shamir–Adleman (RSA) and Elliptic Curve Cryptography (ECC) algorithms. Huge requirements for cryptographic frameworks that can withstand quantum hacking have inspired Quantum Key Distribution (QKD), Post-Quantum Cryptography (PQC), and systems that use both. Objective: The aim of this article is to review the performance, scalability and integration of quantum-secure cryptographic services, with a practical lens on how they can be used in real-time environments like self-driving cars, industrial IoT, and intelligent health systems. It also aims at establishing the drawback of the current model and directions for further enhancement. Methods: The study employs simulative experimentation to understand lest exposures to quantum algorithms and rates cryptographic systems on standards such as latency, Quantum Bit Error Rate (QBER), computational overhead, scalability, and cost. Comparative assessment furniture integrated analysis of QKD, PQC, and hybrid system by identifying the advantages and disadvantage of each system. Results: As a result, adopting hybrid systems provided the best or comparable median results with lowest latency in real-time applications of ~45 ms or lower compared to alternative Multi-Access Edge Computing (MEC) architectures and types of security elements at high scalability. Thus, QKD, while being exceptional in security, has the problem of scalability, while PQC had average results on the given parameters. Conclusion : Quantum threats are adequately dealt with by hybrid cryptographic systems as this study has also pointed out. It is seen that initiation to future work may someday distribute resources effectively, expedite PQC standardization, and embrace artificially intelligent network frameworks for flexibility and expansiveness across different networks.