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Real-Time Scheduling for Wireless Networks with Random Deadlines

Published

Author(s)

Mohamed Hany, Nader Moayeri

Abstract

The use of wireless communications in industrial environments is motivated by the flexibility that wireless networks provide and their cost-efficient setup and maintenance. Various wireless technologies have been introduced to satisfy the strict industrial requirements. Time division multiple access (TDMA) protocols have been widely exploited in various wireless technologies due to the ease of implementation and packets collision avoidance. In this work, we consider the problem of scheduling multiple flows over a wireless network in industrial environments. These flows represent the data coming from the sensors to the controller and the control commands going to the actuators from the controllers. These flows are characterized by random strict deadlines for each packet in a flow following a given probability distribution. Moreover, the schedule is built over a frame of transmissions with the objective of minimizing the total number of packets missing their deadlines. We obtain the optimal scheduling scheme by formulating and solving an unobservable Markov decision problem (UMDP). Then, we obtain a sub- optimal scheduling scheme which has a near-optimal performance for a wide range of system parameters. Finally, we evaluate these scheduling schemes numerically to study the effects of various system parameters on the performance.
Proceedings Title
Proceedings of 13th IEEE International Workshop on Factory Communication Systems
Conference Dates
May 31-June 2, 2017
Conference Location
Trondheim, NO
Conference Title
13th IEEE International Workshop on Factory Communication Systems

Keywords

wireless networks, industrial environments, scheduling, deadlines, Markov decision processes

Citation

Hany, M. and Moayeri, N. (2017), Real-Time Scheduling for Wireless Networks with Random Deadlines, Proceedings of 13th IEEE International Workshop on Factory Communication Systems, Trondheim, NO, [online], https://doi.org/10.1109/WFCS.2017.7991954, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=923299 (Accessed May 23, 2024)

Issues

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Created July 26, 2017, Updated April 7, 2022