Abstract

The rise of heterogeneous access networks (HANs) stems from the growing need for universal mobility services and wireless connectivity, as the demand for heterogeneous connectivity fuels the convergence of different classes of wireless access technologies. The fundamental problem Issue of primary concern noted relates to the design and realization of effective 'no service interruption' handover strategies for cross-network mobility that do not compromise service quality, induce excessive delay or cause service interruption. In this paper, we present a comprehensive study of seamless handover designs for heterogeneous access networks, focusing on systems, their distinct decision processes, various mobility management protocols, and hyper-aware mobility situation adjustments. We analyze the mechanisms of both horizontal and vertical handovers and demonstrate the use of multi-criteria decision-making methods, considering numerous criteria, including signal strength, latency, bandwidth, user preferences, and application demands. Moreover, the use of software-defined networking (SDN), anticipatory machine learning models, and media-independent handover control (IEEE 802.21) frameworks are addressing new solutions. With these approaches, the paper will address numerous issues arising from the integration of these control interfaces. A review of the available mechanisms is conducted, focusing on their advantages and disadvantages, as well as their effectiveness in various mobility situations. Lastly, we propose a context-aware, real-time policy adjustment framework that utilizes context-aware policies with real-time monitoring and analysis to lower the chances of handover failures. The proposed method's efficacy has been examined so far using simulations for performance metrics such as handover delay, packet loss, and throughput. Moreover, this work explores how cross-layer optimization and user-centric network selection enhance handover reliability. The focus is on the neglected factors within mobile devices during traditional handover procedures, specifically on the Quality of Experience (QoE) and energy efficiency. The Framework also enables the dynamic allocation of network resources at different levels to support latency-critical applications, including VoIP and video streaming. The problem is solved by placing intelligent decision layers on the system and applying predictive mobility models, which aim to minimize unnecessary handovers while optimizing the user experience. For advanced intelligent environments and mobile broadband systems, these sophisticated solutions are designed to create adaptable and robust handover schemes.