Demonstrating the Advantages of Computational Offloading of XR Services via WebAssembly

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.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-02
DOI
https://doi.org/10.5281/zenodo.15578049
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
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article

Demonstrating the Advantages of Computational Offloading of XR Services via WebAssembly

Zenodo (CERN European Organization for Nuclear Research)
IoT and Edge/Fog Computing
article

Demonstrating the Advantages of Computational Offloading of XR Services via WebAssembly

article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
Ericsson (Sweden) (SE), Universidade Federal de São Carlos (BR), Pontifícia Universidade Católica de Goiás (BR), Universidade do Vale do Rio dos Sinos (BR), Universidade Federal de Goiás (BR)
Affordable and clean energy
Openalex Percentile: Top 52%
IoT and Edge/Fog Computing
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Demonstrating the Advantages of Computational Offloading of XR Services via WebAssembly · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS