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http://inaoe.repositorioinstitucional.mx/jspui/handle/1009/318| Azcatl: A Bio-inspired data foraging mechanism based on indirect communication in mobile sensor networks for dynamic environments | |
| JOSUE CASTAÑEDA CISNEROS | |
| SAUL EDUARDO POMARES HERNANDEZ JESUS ANTONIO GONZALEZ BERNAL JOSE ROBERTO PEREZ CRUZ | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| Bio-Inspired data foraging Mobile wireless sensor networks Fuzzy-Causal relation Indirect communication | |
| Sparse Wireless Sensor Networks (SWSN) have been proposed to explore and gather data from harsh environments. Exploration has been focused on finding optimal paths to obtain knowledge about the environment while data gathering has mainly been oriented to obtain raw data indiscriminately of the environment. However, dynamic environments were the usefulness of data is constantly changing, these solutions are not useful. Therefore, for these types of environments, both exploration and data gathering must be focused on repeatedly searching for valuable data sources over a particular area; as some animals perform foraging. Data foraging is a continuous process which involves: exploration, identification and selective exploitation (harvesting) of profitable data sources. We propose a bio-inspired data foraging mechanism for SWSN in dynamic environments. To develop our mechanism, indirect communication is modeled taking inspiration from the stigmergy principe. We establish artificial pheromones based on the fuzzy causal relation. Each step of data foraging is formally defined and mathematically evaluated. In addition we show the viability of each step by simulations which have been tested through statistical hypothesis. | |
| Instituto Nacional de Astrofísica, Óptica y Electrónica | |
| 2016 | |
| Tesis de maestría | |
| Inglés | |
| Estudiantes Investigadores Público en general | |
| Castañeda-Cisneros J. | |
| CIENCIA DE LOS ORDENADORES | |
| Versión aceptada | |
| acceptedVersion - Versión aceptada | |
| Aparece en las colecciones: | Maestría en Ciencias Computacionales |
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| CastanedaCJ.pdf | 2.33 MB | Adobe PDF | Visualizar/Abrir |