dc.contributor.advisor | Díaz del Río, Fernando | es |
dc.creator | Salmerón García, Javier Jesús | es |
dc.date.accessioned | 2016-04-21T16:42:03Z | |
dc.date.available | 2016-04-21T16:42:03Z | |
dc.date.issued | 2016-03-14 | |
dc.identifier.citation | Salmerón García, J.J. (2016). Estudio y evaluación de plataformas de distribución de cómputo intensivo sobre sistemas externos para sistemas empotrados.. (Tesis doctoral inédita). Universidad de Sevilla, Sevilla. | |
dc.identifier.uri | http://hdl.handle.net/11441/40260 | |
dc.description | Falta palabras clave | |
dc.description.abstract | Nowadays, the capabilities of current embedded systems are constantly increasing, having a wide range of applications. However, there are a plethora of intensive computing tasks that, because of their hardware limitations, are unable to perform successfully. Moreover, there are innumerable tasks with strict deadlines to meet (e.g. Real
Time Systems). Because of that, the use of external platforms with sufficient computing power is becoming widespread, especially thanks to the advent of Cloud Computing in recent years. Its use for knowledge sharing and information storage has been demonstrated innumerable times in the literature. However, its core properties, such as dynamic scalability, energy efficiency, infinite resources... amongst others, also make
it the perfect candidate for computation off-loading. In this sense, this thesis demonstrates this fact in applying Cloud Computing in the area of Robotics (Cloud Robotics). This is done by building a 3D Point Cloud Extraction Platform, where robots can offload
the complex stereo vision task of obtaining a 3D Point Cloud (3DPC) from Stereo Frames. In addition to this, the platform was applied to a typical robotics application: a Navigation Assistant. Using this case, the core challenges of computation offloading were thoroughly analyzed: the role of communication technologies (with special focus on 802.11ac), the role of offloading models, how to overcome the problem of communication
delays by using predictive time corrections, until what extent offloading is a
better choice compared to processing on board... etc. Furthermore, real navigation tests were performed, showing that better navigation results are obtained when using computation offloading. This experience was a starting point for the final research of
this thesis: an extension of Amdahl’s Law for Cloud Computing. This will provide a better understanding of Computation Offloading’s inherent factors, especially focused on time and energy speedups. In addition to this, it helps to make some predictions regarding the future of Cloud Computing and computation offloading. | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.rights | Atribución-NoComercial-SinDerivadas 4.0 España | |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.title | Estudio y evaluación de plataformas de distribución de cómputo intensivo sobre sistemas externos para sistemas empotrados. | es |
dc.type | info:eu-repo/semantics/doctoralThesis | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadores | es |
idus.format.extent | 115 p. | es |
dc.identifier.idus | https://idus.us.es/xmlui/handle/11441/40260 | |