dc.contributor.author | Guegan, Loic | |
dc.contributor.author | Rais, Issam | |
dc.contributor.author | Anshus, Otto Johan | |
dc.date.accessioned | 2024-02-15T13:39:46Z | |
dc.date.available | 2024-02-15T13:39:46Z | |
dc.date.issued | 2023-09-27 | |
dc.description.abstract | <p>In Cyber-Physical Systems (CPS) such as Wireless Sensors Networks (WSN), disseminating data is crucial. Under energy constraints with limited communications capabilities, performing data dissemination is challenging. In such contexts, common data dissemination methods cannot be used. Nodes must rely on device-to-device communications policies to mitigate the impact of communications on the nodes energy consumption. However, depending on nodes configuration (up-times duration, wireless technology capabilities and energy consumption), choosing a suitable communication policy is challenging.
<p>This work exposes the problem statement for using analytic algorithms to predict the most suitable device-to-device communication policy, for a given node configuration, to match a given coverage and energy consumption target in a constrained environment. | en_US |
dc.identifier.citation | Guegan L, Rais I, Anshus O: Towards Data Dissemination Policy Prediction for Constrained Environments Using Analytics. In: Kanhere S, Silvestri, Saukh, Nikoletseas S. Proceeding of the 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things - DCOSS-IoT 2023, 2023. IEEE Computer Society Digital Library p. 68-70 | en_US |
dc.identifier.cristinID | FRIDAID 2158997 | |
dc.identifier.doi | 10.1109/DCOSS-IoT58021.2023.00019 | |
dc.identifier.isbn | 979-8-3503-4649-7 | |
dc.identifier.issn | 2325-2936 | |
dc.identifier.issn | 2325-2944 | |
dc.identifier.uri | https://hdl.handle.net/10037/32944 | |
dc.language.iso | eng | en_US |
dc.publisher | IEEE | en_US |
dc.relation.projectID | Norges forskningsråd: 270672 | en_US |
dc.rights.accessRights | openAccess | en_US |
dc.rights.holder | Copyright 2023 The Author(s) | en_US |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0 | en_US |
dc.rights | Attribution 4.0 International (CC BY 4.0) | en_US |
dc.title | Towards Data Dissemination Policy Prediction for Constrained Environments Using Analytics | en_US |
dc.type.version | acceptedVersion | en_US |
dc.type | Journal article | en_US |
dc.type | Tidsskriftartikkel | en_US |