Abstract
The Internet of Things (IoT) requires seamless mobility and services with low power consumption, low packet loss ratio, ultra-low latency, and high reliability. Ultra-dense deployment of small coverage radio access networks improves network throughput, latency, and packet loss ratio but increases the frequency of vertical handovers. Optimal network selection to ensure ultra-reliable, low-latency, seamless connectivity to provide massive machine-type communication to support a wide range of services for the emergence of IoT and Industry 5.0 through the next generation heterogeneous networks is one of the most challenging fields of research. The best network selection is one of the most crucial phases of the vertical handover decision algorithm in an ultra-dense heterogeneous network. Inadequate network selection can lead to failed handovers and ping pong handovers, which drastically affect the quality of services and the quality of experience. In this article, we have developed a new improved method based on improved removal effects of criteria- technique for order performance by similarity to ideal solution (I-MEREC-TOPSIS) network selection scheme. It is based on the removal effect of alternatives’ attributes. It is an intelligent integration of the I-MEREC weight method of alternative criteria and the TOPSIS alternative ranking multi-attribute decision-making technique. In the proposed scheme, optimal network selection is not only dependent on the best performance score of candidate networks but also on the statistically defined threshold value of servicing and target networks. In comparison to CRiteria Importance Through Intercriteria Correlation (CRITIC) TOPSIS, Entropy-TOPSIS, Statistical Variance Procedure(SVP) TOPSIS, and MEREC-TOPSIS, the proposed scheme has reduced ping-pong handovers and handover failures.
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