QoS Determination Using Preliminary Data Storage
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing IT infrastructure management systems face challenges in accurately determining quality of service (QoS) due to delayed data from data sources, which can lead to inaccurate real-time indications and non-compliance with service level agreements (SLAs), especially during data-source unavailability.
Innovation Solution
A method and system that calculate real-time QoS indications using regular data and recalculate using stored and delayed data to provide a more accurate indication, ensuring compliance with SLAs by storing regular information and recalculating affected results once delayed data is received.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If real-time QoS indication is calculated using only regular data without waiting for delayed data, then real-time monitoring capability is improved, but measurement precision deteriorates due to incomplete data
Solution Approach 1:
The system performs preliminary storage of regular QoS data before delayed data arrives. When delayed data is received, the previously stored regular data is retrieved and combined with the delayed data to recalculate accurate QoS indications, thereby resolving the contradiction between real-time monitoring and measurement precision
Solution Approach 2:
The system implements a feedback mechanism where delayed data is continuously monitored and integrated into the QoS calculation process. When delayed data arrives, it triggers a recalculation of QoS indications using both regular and delayed data, ensuring accuracy while maintaining real-time monitoring capability
2Measurement precision
If QoS determination waits for delayed data to ensure accuracy, then measurement precision is improved, but productivity deteriorates due to delays in QoS indication
Solution Approach 1:
The system prepares by storing regular QoS data in advance before delayed data arrives. This preliminary action enables immediate recalculation upon receipt of delayed data, thus improving both accuracy and maintaining determination speed
Solution Approach 2:
The system dynamically adjusts its operation mode based on data availability. It continuously provides real-time QoS indications using regular data, and automatically switches to recalculation mode when delayed data arrives, optimizing both speed and accuracy dynamically
3Productivity
If real-time QoS calculation proceeds without detecting data-source unavailability, then productivity is improved, but reliability deteriorates due to undetected data delays
Solution Approach 1:
The system implements a feedback mechanism that continuously monitors data-source availability. When unavailability is detected or delayed data arrives, the system triggers a recalculation process using stored regular data combined with the delayed data, thus maintaining both productivity and reliability
Solution Approach 2:
The system introduces an intermediary availability detection layer between the data sources and the QoS calculation process. This intermediary monitors data completeness and coordinates the integration of delayed data, ensuring reliable QoS determination without compromising calculation efficiency
Data Source
AI summary
A method of determining quality of service (QoS) in an IT infrastructure on the basis of QoS-related data received from data sources for these QoS-related data, wherein the data from the data sources regularly arrive in real-time, but data from one or more of the data sources may occasionally be delayed. On the basis of the regular data, a real-time indication of the quality of service is calculated in a first process. This indication is possibly inaccurate since delayed data is not included. After the receipt of delayed data, a delayed, but more accurate indication of the quality of service is calculated in a second concurrent process on the basis of regular information, which comprises at least one of regular data and information derived from it, and the delayed data.