17969676. COMPUTING SERVICES ARCHITECT simplified abstract (Dell Products, L.P.)
Contents
COMPUTING SERVICES ARCHITECT
Organization Name
Inventor(s)
Nisanth Mathilakath Padinharepatt of Palakkad District (IN)
Pratika Dola of Bangalore (IN)
Ashish Gupta of Bangalore (IN)
COMPUTING SERVICES ARCHITECT - A simplified explanation of the abstract
This abstract first appeared for US patent application 17969676 titled 'COMPUTING SERVICES ARCHITECT
The computing system module described in the patent application helps in designing cloud computing services applications that combine various cloud computing services from different sources, vendors, or platforms.
- The description of the desired functionality of the application is converted into a context vector.
- A trained supervised learning model analyzes the context vector to determine the relative probability of including each available computing service based on probability thresholds.
- The learning model generates a recommendation report identifying which services should be included in the application based on specific criteria.
- Edges are determined from the context vector and analyzed to recommend an architecture of services.
- The recommended architecture can be visualized as a diagram based on the edges.
- The learning model can be updated with information from actual use to improve its training.
Potential Applications: - Designing complex cloud computing applications with multiple services - Optimizing the selection of cloud computing services based on specific criteria
Problems Solved: - Streamlining the process of designing cloud computing applications with multiple services - Improving the efficiency of selecting the most suitable cloud computing services for an application
Benefits: - Enhanced decision-making in selecting cloud computing services - Increased efficiency in designing cloud computing applications - Improved performance and functionality of cloud computing services applications
Commercial Applications: Title: "Enhanced Cloud Computing Service Selection System" This technology can be used in various industries such as e-commerce, finance, healthcare, and more to optimize cloud computing service selection for applications, leading to improved performance and cost-effectiveness.
Questions about the technology: 1. How does the learning model determine the relative probability of including each computing service? 2. What are the key criteria used by the learning model to recommend services for the application?
Original Abstract Submitted
A computing system module facilitates designing a cloud computing services application that comprises multiple disparate cloud computing services available from multiple sources, vendors, or platforms. A description, in textual or verbal form, of desired functionality of the application is converted into a context vector. A trained supervised learning model having a number of nodes corresponding to a number of available computing services, analyzes the context vector and determines a relative probability for each node with respect to probability thresholds. The learning model identifies in a recommendation report that the application should include a service if a probability corresponding to the service satisfies a respective criterion. Edges may be determined from the context vector and analyzed by the learning model to determine an architecture of recommended services. The architecture may be rendered as a visual diagram based on the edges. Information from actual use may update training of the learning model.
