Abstract
Mobile data transmission between nodes and well-known data services is always evolving, and these services offer a variety of communication endurance. Simultaneously, the 4G standards aim to address these services from the outset, recognizing that improving mobility resilience is necessary to achieve performance objectives in these challenging situations. Redefining new devices to meet the low latency and high-performance reliability requirements of mobile devices is essential. Ongoing advancements in mobile data transmission and services underscore the need for constant progress, emphasizing the crucial role of mobility robustness (MR) in optimizing handover-related parameters and enhancing user mobility performance. MR involves automated optimization in active and idle modes, ensuring optimal performance and end-user quality by considering attributes such as load balancing and neighbour relations. The handover procedure in the networking mechanism provides a transition to the base and the destination cell. This is followed by the load balancing (LB) technique, considered vital in the networking domain and used to analyze the energy-efficient path in the data or the node transfer from the base to the destination node. To find the best optimal energy-efficient path, they are classified using the DL techniques by implementing the modified Deep CNN-BiLSTM mechanism for organizing handover or the load balance technique for effective data transfer. The main reason for using DL techniques in this proposed method is to make the handoff of load-balancing techniques stand out and be organized for better node transfer mechanisms. This proposed method provides a low latency of 3.2s and an accuracy of 99.96% compared to existing methods.