| Texto completo | |
| Autor(es): |
Espindola, Gabriel
;
Pires, Matheus
;
Spadotto, Gustavo
;
Both, Cristiano
;
Silvestre, Bruno
;
Cardoso, Kleber
;
Williams, Andrew
;
Verdi, Fabio
;
Correa
Número total de Autores: 9
|
| Tipo de documento: | Artigo Científico |
| Fonte: | NOMS 2025-2025 IEEE NETWORK OPERATIONS AND MANAGEMENT SYMPOSIUM; v. N/A, p. 3-pg., 2025-01-01. |
| Resumo | |
Extended reality (XR) services form the basis of various innovative applications. These new applications are expected to run on mobile devices with limited computational and energy capabilities. At the same time, XR services should fulfill some expectations regarding data rates and end-to-end latency to guarantee an uninterrupted user experience. In this context, offloading intensive computation to the edge is particularly advantageous for mobile devices, enabling access to more capable processing hardware. Current studies on computational offloading focus mainly on the compute and network continuum formed between edge and cloud and realized mostly through containers. Conversely, this demonstration showcases a computational offloading framework that allows the expansion of XR services functionality from the connected mobile device to an edge computing environment. The presented framework is based on a portable, lightweight, and secure WebAssembly runtime and uses open technology implementations. We demonstrate that the developed framework allows significant performance improvements in a Yolo object detection application and reduces heat generation on mobile devices. (AU) | |
| Processo FAPESP: | 21/00199-8 - Redes e serviços inteligentes rumo 2030 (SMARTNESS) |
| Beneficiário: | Christian Rodolfo Esteve Rothenberg |
| Modalidade de apoio: | Auxílio à Pesquisa - Programa Centros de Pesquisa Aplicada |