Infectious Probability Analysis on COVID-19 Spreading With Wireless Edge Networks

The emergence of infectious disease COVID-19 has challenged and changed the world in an unprecedented manner. integration wireless networks with edge computing (namely networks) brings opportunities to address this crisis. In paper, we aim investigate prediction probability propose precautionary measures against assistance networks. Due availability recorded detention time density individuals within a network, stochastic geometry-based method analyze individuals. proposed can well keep privacy system since it does not require know location or trajectory each individual. Moreover, also consider three types mobility models static model Numerical results show that analytical match simulation results, thereby validating accuracy model. numerical offer many insightful implications. Thereafter, number countermeasures spread based on This study lays foundation toward predicting risk realistic environment points out directions mitigating diseases aid