Latency in edge computing
US11695646B1 · kind B1 · utility
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1References
20Claims
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Key dates
| Filing date | Mar 25, 2022 |
| Grant date | Jul 4, 2023 |
| Priority date | — |
| Expiry date | Mar 25, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2209/509
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Deep reinforcement learning is applied to self-orchestration in edge device computing for offloading within a spatial network community to reduce latency and bandwidth issues. A revised online policy gradient training algorithm based on importance sampling in addition to the use of DRL-based offloading provides for continued use of original sample training data. A request for help scheme supports edge-device cooperation among neighboring devices of the spatial network community by sharing edge device state information (EDSI) for governing task assignments.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.