Client-Side Resource Estimation Using Sample Dots

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Solution Overview

Problem

Existing computer network systems face inefficiencies in estimating resources due to reliance on online service platforms, which can lead to high latency and increased network traffic, especially under unfavorable conditions such as network overload or downtime.

Innovation Solution

Implementing a client-side system that uses client-side versions of digital rules and coarse values to generate sample dots and estimate resources locally, reducing the need for network calls and minimizing data package size, thereby enabling faster and more efficient resource estimation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If the system uses online service platform to estimate resources, then the accuracy of resource estimation is improved, but the network latency and network traffic increase

Engineering Contradiction:

Improveresource estimation accuracyVSAvoidnetwork latency

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system pre-distributes coarse values and cataloged data to client devices before they are needed for estimation. This preliminary action enables the client to perform local resource estimation without real-time network access, significantly reducing latency while maintaining acceptable accuracy for less-than-critical resources.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates simplified copies of the resource estimation model (coarse values and cataloged data) that reside locally on client devices. These copies enable fast local computation without requiring continuous connection to the online service platform, thus reducing network latency and traffic.

Inventive Principle:

Principle #26Copying

2Measurement precision

If the system distributes complete parameter sets for accurate resource estimation, then the estimation accuracy is improved, but the data package size increases

Engineering Contradiction:

Improveresource estimation accuracyVSAvoiddata package size

Core Design Contradiction:

Measurement precisionVSQuantity of substance

Solution Approach 1:

The system extracts only the essential coarse values and cataloged data needed for approximate resource estimation, leaving out the complete parameter sets. This extraction reduces data package size significantly while still providing useful estimation capability for less-than-critical resources.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system provides different data quality levels to different clients based on their needs. Clients receiving coarse values and cataloged data get a lighter data package suitable for quick local estimation, while the online platform retains the complete parameter sets for situations requiring full accuracy.

Inventive Principle:

Principle #3Local quality

3Measurement precision

If the system makes network calls to the online service platform for resource estimation, then the estimation accuracy is improved, but the processing efficiency decreases

Engineering Contradiction:

Improveresource estimation accuracyVSAvoidprocessing efficiency

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The system segments resource estimation into two types: local estimation using coarse values and cataloged data for less-than-critical resources, and platform-based estimation using complete parameter sets for critical resources. This segmentation allows the system to optimize for speed in common cases while maintaining accuracy when needed.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system enables client devices to perform resource estimation independently using locally stored coarse values and cataloged data. This self-service capability eliminates the need for network calls in many cases, dramatically improving processing efficiency for local operations.

Inventive Principle:

Principle #25Self-service

4Reliability

If the system uses comprehensive parameter sets for resource estimation, then the reliability of estimation is improved, but the device resource requirements increase

Engineering Contradiction:

Improveestimation reliabilityVSAvoidprocessing requirements

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system applies partial action by using only the necessary coarse values and cataloged data for local resource estimation, rather than requiring complete parameter sets. This approach provides sufficient reliability for less-than-critical resources while keeping device processing requirements low.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS11762811B2Computation module configured to estimate resource for target point from known resources of dots near the target point

Publication Date: 2023.09.19 AVALARA INC

AI summary

Systems and methods electronically generate sample dots, produce resources associated with the dots and estimate a resource for a target point from known resources of dots near the target point based on client side version of digital rules, cataloged data and coarse values previously received from the online service platform. A client receives cataloged data of a cataloged domain in which the cataloged data includes data representing a plurality of dots and a respective computed resource value for each of the dots and each dot of the plurality of dots represents a point in the cataloged domain. In response to confirming a target point is in the cataloged domain, the system discovers a closest one or more dots to the target point based on the cataloged data, estimates a statistic for a resource for the target point based on the respective computed resource values of the closest one or more dots, stores the estimated statistic in a memory, and produces the local estimate based on the estimated statistic.