Intelligent Cross-Layer Resource Allocation Algorithm for Internet of Things Based on Multi-Source Data Analysis
Starting from increasing the resource utilization and users'satisfaction with service quality,this paper proposes an intelligent cross-layer resource allocation algorithm for the Internet of Things based on multi-source data analysis.Information exchange between the physical layer,transmission layer,and ap-plication layer of the Internet of Things is ensured by blurring the boundaries among the layers;multi-sen-sor fusion of multi-source data from the Internet of Things is adopted to obtain the users' needs of IoT re-sources;channel quality being a constraint,the modulation and coding methods are assigned to terminal users with different channel quality requirements;aiming for the optimization goals of maximizing user serv-ice quality(QoS),throughput and fairness between users,fuzzy decision-making is applied to solve multi-objective problems and achieve intelligent cross-layer resource allocation in the Internet of Things.The ex-perimental results show that the throughput of terminal user resource allocation after the application of this algorithm is higher than10×107 bps,with a normalized fairness index of around0.2 and an average inter-ruption rate of 0.05 per second,improving service quality and user satisfaction.the transmission perform-ance of different channels is good after resource allocation,which is less affected by the number of IoT de-vices and enjoys higher reliability.
multi-source datamulti-sensorInternet of Things resourcesservice qualityintelligent cross-layerresource allocation
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