Title: Research on information capacity prediction of mobile sensing platform in internet of things based on collaborative congestion
Authors: Ying Li
Addresses: School of Information Engineering, Jiaozuo University, Jiaozuo 454000, China
Abstract: The traditional information capacity prediction method ignores the research on collaborative congestion, which leads to the problems of low prediction accuracy and poor comprehensive performance. This paper proposes a collaborative congestion based information capacity prediction method for mobile sensor platform of the internet of things (IoT). The cooperative congestion strategy model and the extended forwarding strategy model are constructed, and the ACJ strategy model is built by combining them. Through this model, the information capacity of mobile sensing platform is established. Finally, information entropy is used to generate information. By solving the capacity model, the prediction results of the information capacity of the mobile sensor platform are obtained. Simulation results show that this method has high prediction accuracy and good comprehensive prediction performance, which is of certain reference value to the research in related fields.
Keywords: cooperative congestion strategy; mobile sensing technology in the internet of things; sensing platform; mobile sensing platform information; information capacity prediction; capacity estimation.
International Journal of Autonomous and Adaptive Communications Systems, 2020 Vol.13 No.3, pp.211 - 228
Received: 27 Jun 2019
Accepted: 22 Nov 2019
Published online: 13 Oct 2020 *