Edge Containerized Tax Engine for Latency Reduction
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Solution Overview
Problem
Current transaction tax engines in the cloud face connectivity issues and high latency, leading to delayed or failed tax calculations, which can result in lost sales and increased tax burdens for companies due to the reliance on internet connectivity for tax calculations.
Innovation Solution
Implementing an edge-provisioned containerized transaction tax engine that extracts and deploys a subset of tax rate and rule data to local edge databases on client devices, enabling fast and reliable tax calculations without relying on internet connectivity, thereby reducing latency and downtime.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a cloud-based transaction tax engine is used, then tax calculation can be offloaded to a third-party specialist, but internet connectivity issues cause tax calculation failures and increased latency
Solution Approach 1:
The patent segments the centralized cloud-based tax engine into distributed edge computing nodes deployed at client locations. Each edge node contains a local containerized tax engine with embedded tax rules and rate data, enabling autonomous tax calculation without requiring continuous connectivity to the central cloud service. This segmentation eliminates the single point of failure and reduces latency by processing taxes locally.
Solution Approach 2:
The patent implements preliminary action by pre-provisioning containerized tax engines at edge locations before connectivity issues occur. These edge nodes are pre-configured with tax rules, rates, and calculation logic, allowing them to immediately process transactions without waiting for cloud connectivity. The system proactively deploys these containers to edge devices in advance, ensuring tax calculation capability is always available locally.
2Measurement precision
If all tax rate and rule data is stored centrally in the cloud, then data accuracy is maintained, but data extraction and synchronization to edge devices increases complexity
Solution Approach 1:
The patent uses copying by creating accurate replicas of the central tax engine and its data in containerized formats at edge locations. These containers contain copies of tax rules, rates, and calculation logic that mirror the central cloud service. The copying mechanism ensures data accuracy is maintained at edge nodes while eliminating the need for complex real-time synchronization, as each container is a self-contained, versioned copy.
Solution Approach 2:
The patent applies parameter changes by transforming the central tax engine into a containerized format with specific parameters optimized for edge deployment. This includes packaging tax data in standardized container formats, setting appropriate cache sizes, and configuring synchronization intervals. These parameter changes enable the system to maintain data accuracy while reducing synchronization complexity through standardized, version-controlled container images.
3Productivity
If a containerized edge solution is deployed, then transaction latency is reduced and connectivity dependence is minimized, but initial deployment and container management complexity increases
Solution Approach 1:
The patent implements universality by designing a multi-functional containerized tax engine that can operate in multiple modes: connected mode (synchronizing with cloud), offline mode (autonomous calculation), and hybrid mode (batch synchronization). The same container infrastructure serves multiple purposes including tax calculation, data caching, and synchronization management. This universal design simplifies deployment by using a single standardized container solution rather than requiring separate systems for different operational modes.
Solution Approach 2:
The patent applies self-service through automated container provisioning and management. The system automatically pulls container images from a registry, deploys them to edge devices, monitors their health, and performs self-healing operations. Configuration and updates are managed through self-service APIs that automatically handle container lifecycle management, reducing manual intervention and simplifying deployment complexity.
Data Source
AI summary
A computer system includes a container deployment and management server for executing a container builder. The container builder is configured to generate and deploy a transaction tax engine container. The container builder is configured to extract from client configuration settings a subset of multiple products and a subset of multiple geographic regions applicable to transactions processed by a client, identify a subset of the tax rate and rule data applicable to each of the subset of products in each of the subset of geographic regions, and create a local edge database including the subset of tax rate and rule data and excluding a reminder of the tax rate and rule data. The container builder is further configured to create a transaction tax engine container image and transmit the tax engine container image to an edge computing device.