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RL-IoT: Reinforcement Learning to Interact with IoT Devices

descriptionPublicationkeyboard_double_arrow_right Article , Preprint , Other literature type , Conference object 23 Aug 2021Embargo end date: 01 Jan 2021 Italy Publisher:IEEEJournal:2021 IEEE International Conference on Omni-Layer Intelligent Systems (COINS)

Authors: Milan, Giulia; Vassio, Luca; Drago, Idilio; Mellia, Marco;

doi: 10.1109/coins51742.2021.9524260 , 10.48550/arxiv.2105.00884

arXiv: http://arxiv.org/abs/2105.00884

handle: 11583/2922203 , 2318/1805835

RL-IoT: Reinforcement Learning to Interact with IoT Devices

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Abstract

Our life is getting filled by Internet of Things (IoT) devices. These devices often rely on closed or poorly documented protocols, with unknown formats and semantics. Learning how to interact with such devices in an autonomous manner is the key for interoperability and automatic verification of their capabilities. In this paper, we propose RL-IoT, a system that explores how to automatically interact with possibly unknown IoT devices. We leverage reinforcement learning (RL) to recover the semantics of protocol messages and to take control of the device to reach a given goal, while minimizing the number of interactions. We assume to know only a database of possible IoT protocol messages, whose semantics are however unknown. RL-IoT exchanges messages with the target IoT device, learning those commands that are useful to reach the given goal. Our results show that RL-IoT is able to solve both simple and complex tasks. With properly tuned parameters, RL-IoT learns how to perform actions with the target device, a Yeelight smart bulb in our case study, completing non-trivial patterns with as few as 400 interactions. RL-IoT paves the road for automatic interactions with poorly documented IoT protocols, thus enabling interoperable systems.

9 pages, 11 figures, 2021 IEEE International Conference on Omni-Layer Intelligent Systems (COINS)

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Italy

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Keywords

Computer Science - Networking and Internet Architecture, Networking and Internet Architecture (cs.NI), FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Performance evaluation; Protocols; Dictionaries; Roads; Semantics; Reinforcement learning; Internet of Things, Machine Learning (cs.LG)

1 Research products, page 1 of 1

RL-IoT software on GitHub
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