Improving the perfoamnce of Fog-assisted Internet of Things Networks using Bipolar Trapezoidal Neutrosophic sets

Large numbers of devices with varying hardware capabilities and data traffic patterns make up what we call the Internet of Things (IoT). Furthermore, various IoT services, like knowledge economy, e-health, e-business, parking management, etc., display dynamically varying QoS (Quality of Service) needs inside the IoT network. As a consequence of the inconsistency in service delivery, it is difficult to attain spectrum efficiency in the Internet of Things (IoT). There will be a shortage of spectrum for critical IoT services as a result. In this study, we suggest using a Multi-Criteria Decision Making (MCDM) technique to coordinate spectrum sharing across IoT devices. To ensure that the capacity and quality-of-service requirements of IoT devices are met, this framework prioritizes the accessible spectrum bands based on their numerous spectral properties. When all relevant information for reaching a choice is supplied by decision-makers, as is the case in both the trapezoidal and bipolar neutrosophic environments, this research presents a novel, effective approach to tackling these challenges. Conceptually related, the bipolar trapezoidal neutrosophic set's governing principles and rules of operation are laid forth. We cover several important accumulation operations for accumulating bipolar trapezoidal neutrosophic data. The ARAS technique is combined with the bipolar trapezoidal neutrosophic sets to compute the weights of principles and rank the substitutions.