Optimized Network Slicing Algorithm for Heterogenous 5G Wireless Access Node in Advanced Surveillance System

Expansion of wireless cellular networks has significantly increased data volume and diversity within smart networks, introducing complex regulatory and architectural challenges. While existing guidelines offer strategies for managing large datasets, efficient resource allocation in multiservice shared networks remains an ongoing research focus. These networks, crucial for enabling smart environments and Internet of Things, must accommodate diverse data streams from Long-Term Evolution and Narrow Band-Internet of Things, balancing real-time traffic (e.g., video and voice) with elastic traffic (e.g., sensor and meter data). To address these challenges, we propose a framework for multi-service access nodes in 5G networks, integrating Processor Sharing Scheduling and access control mechanisms to optimize resource allocation. This model accurately predicts resource demands, ensuring adherence to quality of service requirements while enabling differentiated service levels and traffic prioritization. Additionally, implementation of a dynamic allocation strategy with access restrictions enables efficient servicing of heterogeneous traffic based on resource load by enhancing data transmission quality and overall network integrity.