Distributed Mobile Rewards Data Processing
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Solution Overview
Problem
Traditional distributed computing solutions for processing large amounts of data from customer rewards programs are cost-prohibitive, especially when scaling beyond hundreds of computer nodes due to hardware and software costs.
Innovation Solution
A system and method utilizing a distributed computing network where customer data is stored and queried, with a subset of data distributed to mobile devices acting as nodes, allowing for reduced hardware and software requirements, and enabling efficient processing and personalization of customer data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional distributed computing solutions are used to process large amounts of customer rewards data, then data processing capability is improved, but hardware and software costs increase significantly
Solution Approach 1:
The patent applies universality by enabling mobile devices to serve dual purposes: their original consumer functions plus distributed computing nodes for data processing. The mobile devices perform both their standard user-facing roles and computational tasks, eliminating the need for dedicated expensive hardware infrastructure while maintaining data processing capabilities.
Solution Approach 2:
The system enables self-service by allowing mobile devices to autonomously participate in distributed computing operations. The mobile devices independently execute computational tasks, store data locally, and communicate results back to the central server without requiring specialized infrastructure, thus reducing hardware and software costs while maintaining processing capability.
2Ease of manufacture
If cloud computing is used to lower costs compared to on-site distributed computing, then operational costs are reduced, but scaling beyond hundreds of nodes remains cost-prohibitive due to hardware, software licenses, and support costs
Solution Approach 1:
The patent applies segmentation by dividing the centralized cloud computing architecture into distributed segments located on individual mobile devices. Each mobile device becomes an independent node that processes data locally, eliminating the need for expensive centralized cloud infrastructure and enabling scalable growth without proportionally increasing costs.
Solution Approach 2:
The system uses copying by replicating data and computational capabilities across numerous mobile devices instead of concentrating resources in a centralized cloud infrastructure. This distribution of copied data and processing power enables scalable growth while reducing per-node costs compared to traditional cloud or on-site solutions.
3Device complexity
If a centralized database stores all customer rewards data, then data management is simplified, but data access speed and processing efficiency decrease
Solution Approach 1:
The patent applies segmentation by dividing the centralized database into distributed data segments stored across multiple mobile devices. Each mobile device maintains local copies of relevant data, enabling fast local access while the segmented architecture remains coordinated through the central server, thus improving data access speed without significantly increasing management complexity.
Solution Approach 2:
The system transitions from a single-dimensional centralized storage model to a multi-dimensional distributed architecture where data exists both centrally and locally across mobile devices. This dimensional change enables simultaneous data access from multiple locations, improving speed while maintaining manageable complexity through hierarchical coordination.
Data Source
AI summary
Systems and methods for implementing a rewards program for registered customers of a business make use of a central computer server and a database that is in communication with the central computer server and that stores data about the registered customers. Multiple mobile devices associated with the various registered customers communicate with the central computer server via a software application running on the mobile device, and a subset of the data from the database is thereby communicated to each of the multiple mobile devices from the central computer server. A query of the data about the registered customers is then initiated from the central computer server and communicated to each of the multiple mobile devices via the software application running on each of the multiple mobile devices, with a result of the query being processed on each of the multiple mobile devices then communicated back to the central computer server.