LINK QUALITY ESTIMATION FOR INDUSTRIAL WIRELESS SENSOR NETWORKS USING BURSTINESS DISTRIBUTION METRIC

Abstract

Industrial wireless sensor network applications are requiring low-power operations, deterministic communications, and end-to-end reliability. However, it is very difficult to achieve this goal because of link burstiness and interference. In this study, we propose a novel link quality estimation mechanism named burstiness distribution metric, which uses the distribution of burstiness in the link to deal with the variations of the wireless link. First, we estimate the link quality by counting the number of consecutive loss packet happenings in each bi-direction link at the receiver node. Based on that, we created a burstiness distribution list and estimate the number of transmissions. The node uses the burstiness distribution metric to choose the best route for the routing and calculate the number of transmissions to reach the reliability target in the scheduling algorithm. Our simulation in Cooja Simulator – the simulator of Contiki showed that our proposal can be used as the input metric to choose the minimal number of transmission packet on each link for the routing protocol and calculate the number of transmission in scheduling to achieve energy efficiency and reliability target in the industrial wireless sensor network.