Random-deadline missing probability analysis for wireless communications in industrial environments

Abstract

The flexibility of wireless networks, and the need for more data to be transferred in modern industries have motivated the industrial wireless communications. Strict industrial requirements including the time-sensitive delivery of data have led to developing appropriate wireless technologies to satisfy these requirements. Various industrial wireless protocols employ Time division multiple access (TDMA) because of preventing data collision between various transmissions and the easiness of employment. In this work, we study the scheduling problem of multiple wireless data flows for industrial applications. The data flows have random strict deadlines following a given probability distribution. In modern industries, these flows may be sensing data routed from a sensor to the controller or control commands directed from the controller to an actuator. A randomized frame-based scheduling scheme is analyzed where each time slot in the frame is assigned to a data flow randomly. We derive a method to calculate the average number of packets missing their deadlines per frame that can be used for flow admission control or optimization of the scheduling algorithm. Finally, we study the effects of various system parameters on the ratio of the average number of packets missing their deadlines to the average total number of packets generated.