In-Memory Charge Computation for Transport Management
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Solution Overview
Problem
Transportation management systems face inefficiencies in processing multiple orders simultaneously due to sequential database lookups and data conversions, leading to increased order processing time and user wait times.
Innovation Solution
Implementing a real-time in-memory charge computation using an in-memory database that stores data in a columnar format, allowing for parallel processing and reduced database round trips, and minimizing explicit data conversions by using implicit system-generated identifiers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If sequential database lookup is used to process multiple orders, then data accuracy is maintained, but order processing time increases significantly
Solution Approach 1:
The patent loads rate table data into memory before processing orders, performing the data retrieval action in advance. This preliminary loading eliminates repeated database lookups during order processing, significantly reducing processing time while maintaining data accuracy through controlled synchronization mechanisms.
Solution Approach 2:
The patent divides order processing into separate parallel threads, with each thread handling individual order calculations independently. This segmentation allows multiple orders to be processed simultaneously rather than sequentially, increasing throughput while maintaining data integrity through proper synchronization.
2Speed
If multiple database round trips are performed for each order, then data consistency is ensured, but processing speed decreases
Solution Approach 1:
The system performs preliminary loading of rate table data into memory before order processing begins. This upfront action reduces subsequent database interactions to minimal synchronization operations, dramatically improving computation speed while maintaining data consistency through controlled updates.
Solution Approach 2:
The patent introduces an in-memory cache as an intermediary between the database and order processing logic. This cache holds rate table data locally, allowing fast access during computations while a synchronization mechanism acts as a mediator to ensure data consistency when the underlying database data changes.
3Loss of time
If explicit data conversion is performed during order processing, then data accuracy is maintained, but processing time increases
Solution Approach 1:
The patent changes the data representation parameters by storing rate table data in a standardized format in memory that matches the expected input format for charge calculations. This parameter alignment eliminates the need for explicit conversion operations during processing, reducing time loss while maintaining data accuracy through proper type matching.
Data Source
AI summary
In an embodiment, a transport management application is executing in the application layer. User may place orders by specifying order data in a user interface of the transport management application, and initiate calculate charges to calculate transportation charges for the orders. Based on the initiation, the charge calculation function is invoked in the application layer. Charge calculation function reads the order data specified in the user interface, and invokes charge computation engine in an in-memory database. Orders are split and grouped based on number of dimensions in a rate table. Charge computation engine looks up master data and computes transportation charges for the grouped orders in parallel. After the charge computation engine determines the transportation charges for the orders, sum of the transportation charges is returned to the application layer.