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2019 | OriginalPaper | Chapter

A Task Scheduling Algorithm Based on Q-Learning for WSNs

Authors : Benhong Zhang, Wensheng Wu, Xiang Bi, Yiming Wang

Published in: Communications and Networking

Publisher: Springer International Publishing

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Abstract

In industrial Wireless Sensor Networks (WSNs), the transmission of packets usually have strict deadline limitation and the problem of task scheduling has always been an important issue. The problem of task scheduling in WSNs has been proved to be an NP-hard problem, which is usually scheduled using a heuristic algorithm. In this paper, we propose a task scheduling algorithm based on Q-Learning for WSNs called Q-Learning Scheduling on Time Division Multiple Access (QS-TDMA). The algorithm considers the packet priority in combination with the total number of hops and the initial deadline. Moreover, according to the change of the transmission state of packets, QS-TDMA designs the packet transmission constraint and considers the real-time change of packets in WSNs to improve the performance of the scheduling algorithm. Simulation results demonstrate that QS-TDMA is an approximate optimal task scheduling algorithm and can improve the reliability and real-time performance of WSNs.

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Metadata
Title
A Task Scheduling Algorithm Based on Q-Learning for WSNs
Authors
Benhong Zhang
Wensheng Wu
Xiang Bi
Yiming Wang
Copyright Year
2019
Book
Communications and Networking

Print ISBN: 978-3-030-06160-9

Electronic ISBN: 978-3-030-06161-6

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-06161-6_51

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