17968944. MOVEMENT OF OPERATIONS BETWEEN CLOUD AND EDGE PLATFORMS simplified abstract (Dell Products L.P.)
Contents
- 1 MOVEMENT OF OPERATIONS BETWEEN CLOUD AND EDGE PLATFORMS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 MOVEMENT OF OPERATIONS BETWEEN CLOUD AND EDGE PLATFORMS - 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
MOVEMENT OF OPERATIONS BETWEEN CLOUD AND EDGE PLATFORMS
Organization Name
Inventor(s)
Subhasis Bandyopadhyay of Bangalore (IN)
Parminder Singh Sethi of Ludhiana (IN)
MOVEMENT OF OPERATIONS BETWEEN CLOUD AND EDGE PLATFORMS - A simplified explanation of the abstract
This abstract first appeared for US patent application 17968944 titled 'MOVEMENT OF OPERATIONS BETWEEN CLOUD AND EDGE PLATFORMS
Simplified Explanation
The abstract describes a method for transferring the execution of a machine learning algorithm from a cloud platform to an edge platform based on the analysis of the algorithm's results.
- Moving operations between cloud and edge platforms
- Executing a machine learning algorithm on a cloud platform
- Analyzing results of the machine learning algorithm
- Determining whether the algorithm should be additionally trained
- Transferring further execution of the algorithm to an edge platform based on a negative determination
Potential Applications
This technology could be applied in various industries such as healthcare, finance, and manufacturing where real-time data analysis and decision-making are crucial.
Problems Solved
1. Efficient resource utilization by transferring operations to edge platforms when necessary. 2. Improved performance and reduced latency by executing operations closer to the data source.
Benefits
1. Enhanced scalability and flexibility in deploying machine learning algorithms. 2. Cost-effective utilization of cloud and edge computing resources. 3. Improved response time and decision-making capabilities.
Potential Commercial Applications
Optimizing resource allocation in IoT devices for smart homes and cities.
Possible Prior Art
One possible prior art could be the use of edge computing for real-time data processing in IoT devices.
Unanswered Questions
How does this technology impact data privacy and security in edge computing environments?
This article does not address the potential implications of transferring operations to edge platforms on data privacy and security.
What are the potential challenges in implementing this method across different cloud and edge platforms?
The article does not discuss the challenges that may arise when transferring operations between various cloud and edge platforms.
Original Abstract Submitted
Techniques are disclosed for moving operations between cloud and edge platforms. For example, a method comprises executing a machine learning algorithm on a cloud platform and analyzing results of executing the machine learning algorithm. Based at least in part on the analysis, a determination is made whether the machine learning algorithm should be additionally trained. Based at least in part on a negative determination further execution of the machine learning algorithm is transferred from the cloud platform to an edge platform.
