Intel corporation (20240214279). MULTI-NODE SERVICE RESILIENCY simplified abstract
Contents
- 1 MULTI-NODE SERVICE RESILIENCY
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 MULTI-NODE SERVICE RESILIENCY - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about Reliability-Based Data Processing
- 1.13 Original Abstract Submitted
MULTI-NODE SERVICE RESILIENCY
Organization Name
Inventor(s)
Matthew J. Adiletta of Bolton MA (US)
Susanne M. Balle of Hudson NH (US)
Patrick Connor of Beaverton OR (US)
MULTI-NODE SERVICE RESILIENCY - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240214279 titled 'MULTI-NODE SERVICE RESILIENCY
Simplified Explanation
The patent application discusses a method for determining whether to process data based on a reliability metric, such as memory health and computational accuracy.
Key Features and Innovation
- Decision-making process based on a reliability metric.
- Utilization of multiple microservices for data processing.
- Incorporation of memory health and computational accuracy indicators in the reliability metric.
Potential Applications
This technology can be applied in various industries such as healthcare, finance, and telecommunications for efficient data processing and decision-making based on reliability metrics.
Problems Solved
- Ensures data processing based on reliable metrics.
- Improves overall system performance and accuracy.
- Enhances decision-making processes in real-time applications.
Benefits
- Increased reliability in data processing.
- Improved system efficiency and accuracy.
- Enhanced decision-making capabilities based on reliable metrics.
Commercial Applications
- "Reliability-Based Data Processing System for Real-Time Applications": Implementing this technology in real-time applications can improve decision-making processes and overall system performance.
Prior Art
Further research can be conducted in the field of reliability metrics for data processing to explore existing technologies and innovations.
Frequently Updated Research
Stay updated on advancements in reliability metrics for data processing to enhance the efficiency and accuracy of decision-making processes.
Questions about Reliability-Based Data Processing
How does the reliability metric impact the decision-making process in data processing?
The reliability metric determines whether to process data based on indicators like memory health and computational accuracy, ensuring more reliable outcomes.
What are the potential implications of utilizing multiple microservices for data processing based on reliability metrics?
By using multiple microservices, the system can efficiently process data and make decisions in real-time applications, improving overall performance and accuracy.
Original Abstract Submitted
examples described herein relate to determining whether to process or not process data based on a reliability metric. for example, based on receiving a response to a request to a first microservice, with the reliability metric, from one or more servers, a decision can be made of whether to process, by a second microservice, a result associated with the response based on the reliability metric. in some examples, the reliability metric comprises an indicator of memory health and computational accuracy.
