RT Conference Proceedings
T1 Optimal Assignment of Augmented Reality Tasks for Edge-Based Variable Infrastructures
A1 Cañete Valverde, Ángel Jesús
A1 Amor-Pinilla, María Mercedes
A1 Fuentes-Fernández, Lidia
K1 Programación ubicua
K1 Internet de las Cosas
AB In the last few years, the number of devices connected to the Internet has increasedconsiderably; so has the data interchanged between these devices and the Cloud, as well as energyconsumption and the risk of network congestion. The problem can be alleviated by reducingcommunication between Internet-of-Things devices and the Cloud. Recent paradigms, such as EdgeComputing and Fog Computing, propose to move data processing tasks from the Cloud to nearbydevices to where data is produced or consumed. One of the main challenges of these paradigms is tocope with the heterogeneity of the infrastructures where tasks can be offloaded. This paper presents asolution for the optimal allocation of computational tasks to edge devices, with the aim of minimizingthe energy consumption of the overall application. The heterogeneity is represented and managedby using Feature Models, widely employed in Software Product Lines. Given the application andinfrastructure configurations, our Optimal Tasks Assignment Framework generates the optimal taskallocation and resources assignment. The resultant deployment represents the most energy efficientconfiguration at load-time, without compromising the user experience. The scalability and energysaving of the approach are evaluated in the domain of augmented reality applications
YR 2019
FD 2019-12-18
LK https://hdl.handle.net/10630/19087
UL https://hdl.handle.net/10630/19087
LA eng
NO HADAS TIN2015-64841-R (co-funded by FEDER funds),TASOVA MCIU-AEI TIN2017-90644-REDT, MEDEA RTI2018-099213-B-I00 (co-funded by FEDER funds) LEIA UMA18-FEDERJA-157 (co-funded by FEDER funds)Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 11 abr 2026