2026-04-28T00:31:12Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/190872026-02-03T12:05:09Zcom_10630_2254col_10630_37959

Optimal Assignment of Augmented Reality Tasks for Edge-Based Variable Infrastructures Cañete Valverde, Ángel Jesús Amor-Pinilla, María Mercedes Fuentes-Fernández, Lidia Programación ubicua Internet de las Cosas In the last few years, the number of devices connected to the Internet has increased considerably; so has the data interchanged between these devices and the Cloud, as well as energy consumption and the risk of network congestion. The problem can be alleviated by reducing communication between Internet-of-Things devices and the Cloud. Recent paradigms, such as Edge Computing and Fog Computing, propose to move data processing tasks from the Cloud to nearby devices to where data is produced or consumed. One of the main challenges of these paradigms is to cope with the heterogeneity of the infrastructures where tasks can be offloaded. This paper presents a solution for the optimal allocation of computational tasks to edge devices, with the aim of minimizing the energy consumption of the overall application. The heterogeneity is represented and managed by using Feature Models, widely employed in Software Product Lines. Given the application and infrastructure configurations, our Optimal Tasks Assignment Framework generates the optimal task allocation and resources assignment. The resultant deployment represents the most energy efficient configuration at load-time, without compromising the user experience. The scalability and energy saving of the approach are evaluated in the domain of augmented reality applications 2019-12-18T11:52:36Z 2019-12-18T11:52:36Z 2019 2019-12-18 conference output https://hdl.handle.net/10630/19087 eng 13th International Conference on Ubiquitous Computing and Ambient Intelligence, UCAmI 2019 Toledo (Spain) 2-5 Diciembre 2019 open access