QUANTUM-ENHANCED EDGE COMPUTING FOR REAL-TIME DATA PROCESSING IN AUTONOMOUS SYSTEMS
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| Format: | Recurso digital |
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Zenodo
2021
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| _version_ | 1866901247752142848 |
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| author | Jain, Pritesh |
| author_facet | Jain, Pritesh |
| contents | <p><span>The proliferation of Internet of Things (IoT) devices and autonomous systems has necessitated advancements in realtime data processing capabilities. Edge computing addresses latency and bandwidth issues by processing data closer to the source. However, traditional edge computing approaches struggle with the computational demands of complex algorithms, especially in autonomous systems. This paper introduces a novel approach that leverages quantum computing principles to enhance edge computing frameworks. We propose a hybrid architecture combining quantum-enhanced processing units with classical edge nodes to optimize real-time data processing. Our results demonstrate significant improvements in processing speed and efficiency, making this approach viable for deployment in autonomous vehicles and smart city infrastructures.</span> </p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15026322 |
| institution | Zenodo |
| language | |
| publishDate | 2021 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | QUANTUM-ENHANCED EDGE COMPUTING FOR REAL-TIME DATA PROCESSING IN AUTONOMOUS SYSTEMS Jain, Pritesh <p><span>The proliferation of Internet of Things (IoT) devices and autonomous systems has necessitated advancements in realtime data processing capabilities. Edge computing addresses latency and bandwidth issues by processing data closer to the source. However, traditional edge computing approaches struggle with the computational demands of complex algorithms, especially in autonomous systems. This paper introduces a novel approach that leverages quantum computing principles to enhance edge computing frameworks. We propose a hybrid architecture combining quantum-enhanced processing units with classical edge nodes to optimize real-time data processing. Our results demonstrate significant improvements in processing speed and efficiency, making this approach viable for deployment in autonomous vehicles and smart city infrastructures.</span> </p> |
| title | QUANTUM-ENHANCED EDGE COMPUTING FOR REAL-TIME DATA PROCESSING IN AUTONOMOUS SYSTEMS |
| url | https://doi.org/10.5281/zenodo.15026322 |