A Novel Epidemic Model for the Interference Spread in the Internet of Things
| dc.contributor.author | Tuyishimire, Emmanuel | |
| dc.contributor.author | Niyigena, Jean de Dieu | |
| dc.contributor.author | Tubanambazi, Fidèle Mweruli | |
| dc.contributor.author | Rutikanga, Justin Ushize | |
| dc.contributor.author | Gatabazi, Paul | |
| dc.contributor.author | Bagula, Antoine | |
| dc.contributor.author | Niyigaba, Emmanuel | |
| dc.date.accessioned | 2022-04-23T11:22:15Z | |
| dc.date.available | 2022-04-23T11:22:15Z | |
| dc.date.issued | 2022-04-02 | |
| dc.date.updated | 2022-04-21T21:03:54Z | |
| dc.description.abstract | Due to the multi-technology advancements, internet of things (IoT) applications are in high demand to create smarter environments. Smart objects communicate by exchanging many messages, and this creates interference on receivers. Collection tree algorithms are applied to only reduce the nodes/paths’ interference but cannot fully handle the interference across the underlying IoT. This paper models and analyzes the interference spread in the IoT setting, where the collection tree routing algorithm is adopted. Node interference is treated as a real-life contamination of a disease, where individuals can migrate across compartments such as susceptible, attacked and replaced. The assumed typical collection tree routing model is the least interference beaconing algorithm (LIBA), and the dynamics of the interference spread is studied. The underlying network’s nodes are partitioned into groups of nodes which can affect each other and based on the partition property, the susceptible–attacked–replaced (SAR) model is proposed. To analyze the model, the system stability is studied, and the compartmental based trends are experimented in static, stochastic and predictive systems. The results shows that the dynamics of the system are dependent groups and all have points of convergence for static, stochastic and predictive systems. | en_US |
| dc.identifier | doi: 10.3390/info13040181 | |
| dc.identifier.apacitation | Tuyishimire, E., Niyigena, J. d. D., Tubanambazi, F. M., Rutikanga, J. U., Gatabazi, P., Bagula, A., & Niyigaba, E. (2022). A Novel Epidemic Model for the Interference Spread in the Internet of Things. <i>Information</i>, 13(4), 181. http://hdl.handle.net/11427/36385 | en_ZA |
| dc.identifier.chicagocitation | Tuyishimire, Emmanuel, Jean de Dieu Niyigena, Fidèle Mweruli Tubanambazi, Justin Ushize Rutikanga, Paul Gatabazi, Antoine Bagula, and Emmanuel Niyigaba "A Novel Epidemic Model for the Interference Spread in the Internet of Things." <i>Information</i> 13, 4. (2022): 181. http://hdl.handle.net/11427/36385 | en_ZA |
| dc.identifier.citation | Tuyishimire, E., Niyigena, J.d.D., Tubanambazi, F.M., Rutikanga, J.U., Gatabazi, P., Bagula, A. & Niyigaba, E. 2022. A Novel Epidemic Model for the Interference Spread in the Internet of Things. <i>Information.</i> 13(4):181. http://hdl.handle.net/11427/36385 | en_ZA |
| dc.identifier.ris | TY - Journal Article AU - Tuyishimire, Emmanuel AU - Niyigena, Jean de Dieu AU - Tubanambazi, Fidèle Mweruli AU - Rutikanga, Justin Ushize AU - Gatabazi, Paul AU - Bagula, Antoine AU - Niyigaba, Emmanuel AB - Due to the multi-technology advancements, internet of things (IoT) applications are in high demand to create smarter environments. Smart objects communicate by exchanging many messages, and this creates interference on receivers. Collection tree algorithms are applied to only reduce the nodes/paths’ interference but cannot fully handle the interference across the underlying IoT. This paper models and analyzes the interference spread in the IoT setting, where the collection tree routing algorithm is adopted. Node interference is treated as a real-life contamination of a disease, where individuals can migrate across compartments such as susceptible, attacked and replaced. The assumed typical collection tree routing model is the least interference beaconing algorithm (LIBA), and the dynamics of the interference spread is studied. The underlying network’s nodes are partitioned into groups of nodes which can affect each other and based on the partition property, the susceptible–attacked–replaced (SAR) model is proposed. To analyze the model, the system stability is studied, and the compartmental based trends are experimented in static, stochastic and predictive systems. The results shows that the dynamics of the system are dependent groups and all have points of convergence for static, stochastic and predictive systems. DA - 2022-04-02 DB - OpenUCT DP - University of Cape Town IS - 4 J1 - Information KW - interference set KW - interference set KW - LIBA KW - IoT KW - Static KW - Stochastic KW - predictive LK - https://open.uct.ac.za PY - 2022 T1 - A Novel Epidemic Model for the Interference Spread in the Internet of Things TI - A Novel Epidemic Model for the Interference Spread in the Internet of Things UR - http://hdl.handle.net/11427/36385 ER - | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11427/36385 | |
| dc.identifier.vancouvercitation | Tuyishimire E, Niyigena JdD, Tubanambazi FM, Rutikanga JU, Gatabazi P, Bagula A, et al. A Novel Epidemic Model for the Interference Spread in the Internet of Things. Information. 2022;13(4):181. http://hdl.handle.net/11427/36385. | en_ZA |
| dc.language.iso | en | en_US |
| dc.publisher.department | Library and Information Studies Centre (LISC) | en_US |
| dc.publisher.faculty | Faculty of Humanities | en_US |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en_US |
| dc.source | Information | en_US |
| dc.source.journalissue | 4 | en_US |
| dc.source.journalvolume | 13 | en_US |
| dc.source.pagination | 181 | en_US |
| dc.source.uri | https://www.mdpi.com/journal/information | |
| dc.subject | interference set | |
| dc.subject | LIBA | |
| dc.subject | IoT | |
| dc.subject | Static | |
| dc.subject | Stochastic | |
| dc.subject | predictive | |
| dc.title | A Novel Epidemic Model for the Interference Spread in the Internet of Things | en_US |
| dc.type | Journal Article | en_US |