18433291. MULTI-NODE SERVICE RESILIENCY simplified abstract (Intel Corporation)
Contents
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 18433291 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 reliability metric
- Utilization of response from microservices to determine processing
- Reliability metric includes memory health and computational accuracy indicators
- Potential Applications:**
This technology could be applied in various industries where data processing reliability is crucial, such as healthcare, finance, and telecommunications.
- Problems Solved:**
This technology addresses the challenge of determining whether to process data based on its reliability, ensuring accurate and efficient processing.
- Benefits:**
- Improved decision-making based on reliability metrics
- Enhanced data processing accuracy
- Increased efficiency in processing operations
- Commercial Applications:**
Potential commercial applications include data analytics platforms, cloud computing services, and IoT devices that require reliable data processing capabilities.
- Prior Art:**
Readers can explore prior art related to reliability metrics in data processing, decision-making algorithms, and microservices integration.
- Frequently Updated Research:**
Stay informed about the latest advancements in reliability metrics for data processing, decision-making algorithms, and microservices technology.
- Questions about the Technology:**
1. How does the reliability metric impact the decision-making process for data processing? 2. What are the key indicators of memory health and computational accuracy in the reliability metric?
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.
