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Spinel: An Opportunistic Proxy for Connecting Sensors to the Internet of Things

Abstract : Nowadays, various static wireless sensor networks (WSN) are deployed in the environment for many purposes: traffic control, pollution monitoring, and so on. The willingness to open these legacy WSNs to the users is emerging, by integrating them to the Internet network as part of the future Internet of Things (IoT), for example, in the context of smart cities and open data policies. While legacy sensors cannot be directly connected to the Internet in general, emerging standards such as 6LoWPAN are aimed at solving this issue but require us to update or replace the existing devices. As a solution to connect legacy sensors to the IoT, we propose to take advantage of the multi-modal connectivity as well as the mobility of smartphones to use phones as opportunistic proxies, that is, mobile proxies that opportunistically discover closeby static sensors and act as intermediaries with the IoT, with the additional benefit of bringing fresh information about the environment to the smartphones’ owners. However, this requires us to monitor the smartphone’s mobility and further infer when to discover and register the sensors to guarantee the efficiency and reliability of opportunistic proxies. To that end, we introduce and evaluate an approach based on mobility analysis that uses a novel path prediction technique to predict when and where the user is not moving, and thereby serves to anticipate the registration of sensors within communication range. We show that this technique enables the deployment of low-cost resource-efficient mobile proxies to connect legacy WSNs with the IoT.
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Contributor : Benjamin Billet Connect in order to contact the contributor
Submitted on : Monday, April 17, 2017 - 5:56:15 PM
Last modification on : Tuesday, November 29, 2022 - 12:08:09 PM
Long-term archiving on: : Tuesday, July 18, 2017 - 12:19:07 PM


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Benjamin Billet, Valérie Issarny. Spinel: An Opportunistic Proxy for Connecting Sensors to the Internet of Things . ACM Transactions on Internet Technology, 2017, 17 (2), pp.1 - 21. ⟨10.1145/3041025⟩. ⟨hal-01505879⟩



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