Channel-based Sampling Rate and Queuing State Control in Delay-Constraint Industrial WSNs

Abstract

Industrial Wireless Sensor Networks (IWSNs) improve the transmission precision of control signaling as well as contributing to the real-time data monitoring and instrument fault diagnosing throughout the manufacturing production. However, wireless channel effects, such as multipath attenuations, noise and co- channel interference, may have unpredictable and time-varying impacts on keeping packets transmission delay. To address this issue, we propose a Channel-based Sampling rate and Queuing state Control (CSQC) scheme to minimize the packet transmission delay in IWSNs. Specifically, we explore the rapid fading characteristics of the industrial wireless channel by studying the level crossing rate (LCR). We develop a continuous-time Markov model to evaluate the packet sojourn time and design an expectation-maximization (EM) algorithm to timely calibrate the transition rate in the model. Finally, we optimize the sensor sampling rate and queuing state to minimize the packet queuing delay in IWSNs. Simulation results show that the CSQC scheme has lower delay than IEEE 802.15.4 standard does under varying interference effects.