Client-Side Resource Estimation via Coarse Digital Rules
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Solution Overview
Problem
Existing computer systems face inefficiencies in estimating resources due to the need for network calls to online service providers, which can lead to latency and increased data transmission, especially under unfavorable network conditions.
Innovation Solution
The system employs client-side digital rules and coarse values to locally estimate resources, allowing for faster and more efficient calculations without relying on network calls, with the option to reconcile with more accurate estimates from the online service provider when conditions improve.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If network calls are made to online service providers for resource estimation, then measurement precision is improved, but loss of time increases due to network latency
Solution Approach 1:
The system pre-loads coarse values and digital rules from the online service provider to the client system in advance. This preliminary action enables the client to perform local resource estimations without requiring real-time network calls, thus resolving the contradiction by preparing estimation data beforehand while maintaining the option to update from the online service when needed.
2Measurement precision
If complete parameter sets are transmitted for accurate resource estimation, then measurement precision is improved, but loss of substance increases due to larger data package size
Solution Approach 1:
The system implements a two-tier data structure where coarse values (less precise but smaller) are transmitted frequently to the client, while complete parameter sets (more precise but larger) are transmitted less frequently or stored locally. This local quality approach allows the client to use appropriate data granularity based on needs, reducing overall data transmission while maintaining estimation capability.
Solution Approach 2:
Instead of transmitting complete parameter sets for all estimation scenarios, the system transmits only the necessary coarse values for immediate local estimation. Additional parameters are fetched from the online service provider only when higher precision is required or when network conditions permit, thus avoiding unnecessary data transmission while maintaining accuracy when needed.
3Productivity
If local estimation using coarse values is performed, then productivity is improved through faster calculations, but measurement precision deteriorates compared to online service estimates
Solution Approach 1:
The system implements a feedback mechanism where local estimation results are compared with online service provider estimates when available. The discrepancies are analyzed and used to adjust future local estimations, gradually improving the accuracy of coarse value-based estimations while maintaining the speed advantage of local processing.
Solution Approach 2:
The system dynamically selects between local estimation and online service estimation based on current needs, network conditions, and available data. When speed is critical and coarse values are sufficient, local estimation is used. When higher precision is required and network conditions permit, the system transitions to online service estimation, thus adapting the precision-speed tradeoff dynamically rather than statically.
Data Source
AI summary
Systems and methods electronically produce a local estimate of less-than-critical resources based on a client-side version of digital rules and coarse values received from an online service provider. Although using the client-side version of digital rules and the coarse values may not include all the parameters and values needed to provide a fully accurate estimate of the resource, the ability to locally estimate resources without having to make network calls to the online service provider, such as when there are unfavorable conditions or latency of the network, imminent overloading of the online service provider or other operating conditions or demands on the online service provider preventing it from producing a timely more accurate estimate, provides a faster and more efficient way of obtaining a potentially useful estimate of resources.