Entity-Specific Throttling Mechanism for Retail Data Request Management
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Solution Overview
Problem
Legacy retail management systems face processing capacity limitations, leading to performance slowdowns when handling large volumes of data requests from multiple sources, such as stores and websites, which can overwhelm the system and result in decreased response times.
Innovation Solution
Implementing a throttling mechanism that periodically resets counters for each entity, allowing only a limited number of data requests within a set threshold to prevent system overload, enabling efficient handling of increased data volumes by controlling processing power allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the retail management system processes all data requests from multiple entities, then the system handles larger data volumes, but the system becomes overloaded and response times slow down
Solution Approach 1:
The patent applies partial action by implementing a throttling mechanism that selectively processes only a limited number of data requests from each entity within a time window. Instead of processing all requests, the system processes a controlled subset (up to a threshold N requests per entity), which prevents system overload while still handling significant data volumes. This resolves the contradiction by sacrificing complete request processing to maintain acceptable response times.
2Adaptability or versatility
If the retail management system accepts requests from multiple entities, then the system supports more sales channels, but the processing capacity is exceeded and performance degrades
Solution Approach 1:
The patent applies local quality by implementing entity-specific throttling limits. Each entity (store, website, supplier) is assigned its own request counter and threshold N, allowing different processing rates for different entities. This enables the system to support multiple sales channels with varying request volumes while preventing any single entity from overwhelming the system, thus maintaining both adaptability and processing capacity.
Solution Approach 2:
The patent segments the incoming data requests by entity and processes them separately using individual counters and thresholds. By dividing the request stream into entity-specific queues and applying independent throttling control to each, the system can manage multiple sales channels effectively without exceeding overall processing capacity. This segmentation allows granular control over resource allocation to different entities.
3Productivity
If the system processes large volumes of data requests, then more item information is serviced, but the system load increases and response times decrease
Solution Approach 1:
The patent implements periodic action through time-window-based throttling. The system monitors the number of requests from each entity within a defined time window and resets the counters periodically. This periodic control mechanism allows the system to process large volumes of requests during low-load periods while automatically throttling during high-load periods, thus maintaining both high productivity and system reliability over time.
Data Source
AI summary
This application relates to apparatus and methods for automatically servicing item data requests in data management systems, such as in retail management systems. The apparatus and methods employ a throttling technique to service data requests from one or more entities. In some examples, a computing device initializes assigns a counter for each entity, and initializes each counter with an initial value. The computing device also occasionally (e.g., periodically) resets each counter to the initial value. The computing device may receive a data request from one of the entities, and determines whether the counter corresponding to the entity identifies a count that is beyond a threshold. If the counter identifies a count beyond the threshold, the computing device adjusts the counter, and processes the data request. If the counter does not identify a count beyond the threshold, the computing device responds to the entity with an error.