Matai NagiSaeed

Background: Network slicing has turned out to be one of the key enablers in the 5G networks due to the ability to support the diverse applications such as ultra reliable and low latency communications for the self-driving cars or IoT-like massive machine type communications. Prior expeditions lacked integrated tools for the dynamic assignment and allocation of resources and no possibility for maintaining constant QoS. Objective: In this article, the primary aim is to synthesis and test a reinforcement learning–driven slicing framework in order to orchestrate the resources of the three types of slices – URLLC, mMTC, and eMBB. This is to improve the performance of the sliced resource, ensure high availability, and minimize competition of the resources in multi-tenant scenarios in 5G networks. Methods: The proposed study design includes a focus on the key stakeholders and their needs for requirements gathering and an experimental field for actual implementation. Resource distribution is guided by the reinforcement learning algorithms by trying to minimize a cost function which incorporates the relation between the latency, isolation, throughput and energy expended. Using a number of runs, quality of performance is monitored to enable assessment of stability as well as response rates. Results: Experimental results show that the proposed framework achieves a lower level of latency violations and capacity oversubscription compared to heuristic methods. Furthermore, it consistently achieves nearly 2.5X better throughput for telemedicine slices and guarantees less than 5 ms latency for time-sensitive services during dynamic traffic conditions. Conclusion: The study shows how reinforcement learning can be effective and applied for end-to-end 5G network slicing. This sort of adaptive orchestration can increase service dependability while optimising overhead and herald instantly climbable multi-tenant networks compatible with various industries

Background: Digital literacy, education, and human right of internet are also hampered in rural areas keeping the rural people more backward in the technological advancement and not providing them better chance of socioeconomic development. The opportunity of implementing the new 5G technologies can give the new perspective in the elimination of such disparities manifested through the improvement of the connection, the decrease of latency, and the increase of data transfer rates. This research study established that the adoption of 5G for coverage in rural areas is challenged by technical, economic and policy factors. Objective: The article aims at analyzing the technical, economic, and social aspects of 5G technology in the rural context in order to identify such problem the development of appropriate solutions for infrastructure costs, spectrum availability, and consumers. In pursuing this goal, the research seeks to develop practical recommendations on enhancing deployment strategies to increase Internet access where it is scarce. Methods: The study therefore used an exploratory, theoretical-evaluative, and finally empirical approach that involved quantitative modeling, case studies, and key informant interviews. Latency, data throughput, and coverage stand as the most significant factors which were tested using network simulation. Level of cost was used to determine economic feasibility while data for qualitative analysis were obtained from a survey of policymakers and telecom operators, and focus group discussion with rural community leaders. Results: In the case of 5G, the implementation of the system led to a 75% reduction in latency, a 600% improvement in the data throughput, and a 300% increase in coverage area. This finding revealed that the partnerships as a deployment model were the most effective as they resulted to a 58%ROI and lowered infrastructure costs. Conclusion: The study reaffirms the innovation of 5G to rural areas and develops agriculture, healthcare services, and educational systems. Policies, investments in the right areas, optimal management of the available spectrum and engaging with the communities as required should be a key focus for deployment to be just.