Resource Management Technique Based on Lightweight and Compressed Sensing for Mobile Internet of Things

Abstract

In mobile Internet of Tings, based on cross-layer design and resource-aware scheduling, the combination of light weight coding and compressed sensing is used to improve the real-time performance of acquisition of system resource and reliability of resource management in this paper. Compressed sensing scheme based on the adaptive frame format definition of lightweight coding is able to set up the parameters such as sample signal, signal and hops. The nonlinear relationship matrixes between resource information of sensors or system and quality of services are built to manage the global or local network resource scheduling. Experimental results show that the proposed scheme is better than the traditional scheme or resource management based on compressed sensing alone scheme, which can make the system be able to achieve optimal resource allocation.

Resource Scheduling Based on Improved Spectral Clustering Algorithm in Edge Computing

“…These devices are not only large in number but also widespread in geographical distribution. In the real world, when users use these IoT devices, there are various requirements for cloud computing, such as low latency and location awareness [7][8][9][10]. In addition, with the advent of the big data era, traditional data analysis methods and storage technology encounter bottlenecks.…”