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作者机构:Vellore Inst Technol Sch Elect Engn Dept Embedded Technol Vellore 632014 Tamil Nadu India Chandigarh Univ Univ Inst Engn ECE Dept Sahibzada Ajit Singh Naga 140413 India
出 版 物:《IEEE ACCESS》 (IEEE Access)
年 卷 期:2025年第13卷
页 面:9666-9678页
核心收录:
基 金:Vellore Institute of Technology Vellore Tamil Nadu India
主 题:SIM card Internet of Things Real-time systems User experience Interference Handover Ecosystems Delays Wireless fidelity WiMAX Handoff heterogeneous network Internet of Everything (IoE) network selection optimization algorithm prospect theory
摘 要:In the Internet of Everything (IoE) ecosystem, it is necessary for connected devices to move between different access points seamlessly. As IoE is deployed in diverse environments, such as smart cities, industrial settings, and vehicular networks, ensuring reliable connectivity and uninterrupted services across different networks becomes important. As part of the IoE framework, this research paper focuses on developing and evaluating intelligent handoff decision mechanisms. So, in this work, the optimal handoff decision technique is proposed, which transmits the information in a fast manner. The Fuzzy Analytical Hierarchical Process (FAHP) and Analytical Hierarchical Process (AHP) two-user preference calculation algorithms are used. Then, the user preference is included in the prospect algorithm and the optimal network is selected. After that, the result of the prospect algorithm is compared with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Grey Rational Analysis (GRA), and Multiplicative Exponent Weighting (MEW) algorithms in terms of network scores and the number of handoffs. The advantage of network selection using a prospect algorithm is that it will decrease the failure rate and increase the data transfer and user experience. These advantages deliver seamless connectivity for a diverse range of applications and devices using an IoE infrastructure that is more robust and reliable. The network selected by combining different techniques is the optimal network because it selects the most efficient or effective network.