Load Balanced Data Transmission Strategy Based on Cloud–Edge–End Collaboration in the Internet of Things

Abstract

To improve the response speed and quality of Internet of Things (IoT) services and reduce system operating costs, this paper refines the edge layer according to the different data transmission capabilities of different edge devices, constructs a four-layer heterogeneous IoT framework under cloud–edge–end (CEE) collaboration, and gives the corresponding data hierarchical transmission strategy, so as to effectively process sensitive data such as real-time, near-real-time, and non-real-time data. Meanwhile, the link based high-performance adaptive load balancing scheme is developed to achieve the dynamic optimal allocation of system resources. Simulation results demonstrate that the data hierarchical transmission strategy based on a CEE collaboration framework can not only make full use of resources and improve the successful delivery rate of packets but can also greatly reduce the end-to-end transmission delay of data. Especially, compared with the cloud-mist framework without refining the edge layer, the data transmission rate based on CEE collaboration architecture is increased by about 27.3%, 12.7%, and 8%, respectively, in three network environments of light-weight, medium, and heavy load.