Webpage Data Caching to Reduce Server Calls and Power
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Solution Overview
Problem
The existing methods for processing computing calls for webpages result in significant power consumption and carbon emissions due to repetitive server calls and data loading events, leading to inefficiencies and increased carbon footprints.
Innovation Solution
An algebraic graph theory-based solution is employed to identify and optimize navigation flows, merging repetitive data loading events and webpages to reduce power usage and carbon emissions by creating state diagrams and applying reducing factors to eliminate redundant data loading.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If server calls are executed for every webpage navigation, then data freshness and service reliability are improved, but power consumption and carbon emissions increase significantly
Solution Approach 1:
The system performs preliminary actions by caching webpage data locally on client devices before it is needed. When a user navigates to a webpage, the system checks if the data is already cached and serves it directly without executing a server call, thus maintaining service reliability while avoiding unnecessary power consumption from repeated server communications.
Solution Approach 2:
The patent implements local quality by storing webpage data locally on individual client devices rather than centrally on the server. This allows each device to have its own local copy of frequently accessed webpages (such as dashboards and checkout interfaces), enabling fast local retrieval without consuming additional server resources or generating carbon emissions from repeated data transmission.
2Reliability
If webpages are reloaded multiple times after viewing less commonly visited pages, then service availability is maintained, but resource efficiency deteriorates
Solution Approach 1:
The patent merges the functionality of multiple webpage loads into a single cached copy. When a user views a less commonly visited webpage and then returns to a frequently visited one (such as a dashboard), the system combines the cached data with any updates from the intermediate pages, eliminating the need to reload the entire frequently visited webpage and thus improving resource efficiency while maintaining service availability.
Solution Approach 2:
The system discards redundant data loading operations by utilizing previously cached webpage data. Instead of reloading complete webpages that are already stored locally, the system recovers and reuses the cached content, only fetching updates when necessary, thereby significantly improving resource efficiency without compromising service availability.
3Measurement precision
If database or cached resources are retrieved for each navigation, then data accuracy is improved, but processing time increases
Solution Approach 1:
The system performs preliminary data retrieval and caching operations so that when a user navigates to a webpage, the data is already available locally in cached form. This eliminates the need for time-consuming server calls and database queries at the moment of navigation, significantly reducing processing time while maintaining data accuracy through periodic cache updates.
Solution Approach 2:
The patent segments data retrieval into two distinct phases: an initial comprehensive data fetch that populates the cache, and subsequent lightweight update checks. This segmentation allows the system to achieve fast local data access (improving processing time) while periodically verifying and updating data accuracy from the server, thus resolving the contradiction between data accuracy and processing time.
Data Source
AI summary
There are provided systems and methods for reducing computing calls for webpage load times and resources to reduce power usage and/or carbon footprints caused by repetitive navigations. A service provider, such as an online transaction processor, may provide computing services to users, which require computing devices of the users to interact with the service provider and load data on the computing devices, including webpages and application interfaces. Each of data loading event may have a cost, where repeating events may lead to unnecessary power usage, carbon emissions and/or a carbon footprint. A graph algorithmic process may utilize state diagrams of processing flows for data loading events with attributes for each data loading event to identify problematic repeated events. Once the problematic events are identified, the service provider may identify corrective actions to avoid or reduce the repetitive events, such as by merging data into one or more events.