Intel corporation (20240185592). PRIVACY-PRESERVING DISTRIBUTED VISUAL DATA PROCESSING simplified abstract
Contents
- 1 PRIVACY-PRESERVING DISTRIBUTED VISUAL DATA PROCESSING
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 PRIVACY-PRESERVING DISTRIBUTED VISUAL DATA PROCESSING - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
PRIVACY-PRESERVING DISTRIBUTED VISUAL DATA PROCESSING
Organization Name
Inventor(s)
Shao-Wen Yang of San Jose CA (US)
Yen-Kuang Chen of Palo Alto CA (US)
Addicam V. Sanjay of Gilbert AZ (US)
PRIVACY-PRESERVING DISTRIBUTED VISUAL DATA PROCESSING - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240185592 titled 'PRIVACY-PRESERVING DISTRIBUTED VISUAL DATA PROCESSING
Simplified Explanation
The patent application describes an apparatus that can identify a workload, generate a workload graph, identify device connectivity, privacy policy, privacy level information, and privacy constraints, and determine a workload schedule based on these factors.
- The apparatus includes a processor to perform various tasks related to workload management.
- It also includes a communication interface to send the workload schedule to processing devices.
- The workload schedule is determined based on privacy constraints, workload graph, and device connectivity graph.
Potential Applications
The technology described in the patent application could be applied in cloud computing, edge computing, and distributed computing environments where workload scheduling and privacy constraints are crucial.
Problems Solved
This technology solves the problem of efficiently mapping workloads onto processing devices while considering privacy constraints and device connectivity.
Benefits
The benefits of this technology include improved workload management, enhanced privacy protection, and optimized resource utilization in distributed computing systems.
Potential Commercial Applications
A potential commercial application of this technology could be in cloud service providers, edge computing companies, and IoT device manufacturers looking to optimize workload scheduling while ensuring data privacy.
Possible Prior Art
One possible prior art could be existing workload scheduling algorithms in distributed computing systems that do not explicitly consider privacy constraints in their decision-making process.
What are the potential security implications of implementing this technology in real-world systems?
Implementing this technology in real-world systems could raise security concerns related to data privacy, as the mapping of workloads onto processing devices must be done in a way that protects sensitive information from unauthorized access.
How does this technology compare to existing workload scheduling algorithms in terms of efficiency and performance?
This technology aims to improve efficiency and performance by taking into account privacy constraints and device connectivity information, which may not be considered in traditional workload scheduling algorithms. Further research and comparative studies would be needed to evaluate the effectiveness of this approach.
Original Abstract Submitted
in one embodiment, an apparatus comprises a processor to: identify a workload comprising a plurality of tasks; generate a workload graph based on the workload, wherein the workload graph comprises information associated with the plurality of tasks; identify a device connectivity graph, wherein the device connectivity graph comprises device connectivity information associated with a plurality of processing devices; identify a privacy policy associated with the workload; identify privacy level information associated with the plurality of processing devices; identify a privacy constraint based on the privacy policy and the privacy level information; and determine a workload schedule, wherein the workload schedule comprises a mapping of the workload onto the plurality of processing devices, and wherein the workload schedule is determined based on the privacy constraint, the workload graph, and the device connectivity graph. the apparatus further comprises a communication interface to send the workload schedule to the plurality of processing devices.
