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Efficient Resource Scheduling for Multipath Retransmission over Industrial WSAN Systems
Beijing Jiaotong University, Beijing, China.
Beijing Jiaotong University, Beijing, China.
Beijing Jiaotong University, Beijing, China.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.ORCID iD: 0000-0003-0873-7827
2019 (English)In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 19, no 18Article in journal (Refereed) Published
Abstract [en]

With recent adoption of Wireless Sensor-Actuator Networks (WSANs) in industrial automation, wireless control systems have emerged as a frontier of industrial networks. Hence, it has been shown that existing standards and researches concentrate on the reliability and real-time performance of WSANs. The multipath retransmission scheme with multiple channels is a key approach to guarantee the deterministic wireless communication. However, the efficiency of resource scheduling is seldom considered in applications with diverse data sampling rates. In this paper, we propose an efficient resources scheduling algorithm for multipath retransmission in WSANs. The objective of our algorithm is to improve efficiency and schedulability for the use of slot and channel resources. In detail, the proposed algorithm uses the approaches of CCA (clear channel assessment)-Embedded slot and Multiple sinks with Rate Monotonic scheme (CEM-RM) to decrease the number of collisions. We have simulated and implemented our algorithm in hardware and verified its performance in a real industrial environment. The achieved results show that the proposed algorithm significantly improves the schedulability without trading off reliability and real-time performance.

Place, publisher, year, edition, pages
2019. Vol. 19, no 18
Keywords [en]
monitoring and control system, multipath retransmission, realtime wireless communication, resource scheduling, Wireless Sensor and Actuator Networks (WSANs)
Identifiers
URN: urn:nbn:se:miun:diva-37415DOI: 10.3390/s19183927Scopus ID: 2-s2.0-85072574471OAI: oai:DiVA.org:miun-37415DiVA, id: diva2:1355545
Available from: 2019-09-30 Created: 2019-09-30 Last updated: 2019-09-30Bibliographically approved

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