Ubiquitous sensor networks traffic models for medical and tracking applications

Abstract

The Internet of Things (IoT) is a new concept for telecommunication development. The Ubiquitous sensor Network (USN) is one of the general IoT components. The traffic models for such network should be studied well. The USN traffic models study results for medical and tracking applications are considered in this paper. The paper results show that the traffic flows for medical and tracking USN applications are self-similar with the middle level of self-similarity in both cases. The R/S and Higuchi methods were used for Hurst parameter estimation. The Hurst parameter dependence on the length of interval between packets for medical USN and the Hurst parameter dependence on the packet rate and OFF perion length for tracking USN are considered. © 2012 Springer-Verlag.