Middle Tier Server Bulk Data Push for Mobile Devices
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Solution Overview
Problem
Conventional database systems face inefficiencies in processing queries and delivering data, especially when the number of queries is high or when a large number of users access the system concurrently, leading to slow data retrieval and delivery.
Innovation Solution
Implementing mechanisms to push data in bulk to multiple devices by using a middle tier server that filters and updates data, reducing the workload on the database system and ensuring secure, transparent data transfer to user devices, including mobile devices, by comparing query results with state and permission information to determine what data to send.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional database systems process queries for each user individually, then data retrieval accuracy is maintained, but system efficiency deteriorates when the number of queries is high or users access concurrently
Solution Approach 1:
The patent segments the data retrieval process into two phases: (1) bulk query execution for the entire organization to retrieve all relevant data, and (2) client-side filtering to extract only the specific data needed by each user. This segmentation allows the database system to process data in bulk efficiently while maintaining accurate data retrieval for individual users, resolving the contradiction between system efficiency and data retrieval time.
Solution Approach 2:
The patent applies preliminary action by pre-retrieving all organization-level data in bulk before individual user requests are processed. The data is fetched once at the organization level, then cached and filtered client-side for each user. This preliminary bulk retrieval eliminates the need for repeated database queries for each user, significantly improving system efficiency while maintaining fast data retrieval for individuals.
2Productivity
If data is pushed in bulk to multiple devices, then data transfer efficiency is improved, but device complexity increases due to filtering and update mechanisms
Solution Approach 1:
The patent introduces an intermediary component—a dedicated server or service layer—that handles the complex filtering and data preparation logic. This intermediary receives bulk data from the database, applies organization-level and user-level filters, and pushes processed data to multiple devices. By placing filtering logic in this intermediary layer rather than in each client device or directly in the database system, the patent achieves efficient bulk data transfer while managing complexity in a centralized, maintainable location.
3Loss of information
If all query results are returned to each organization, then data completeness is improved, but security deteriorates due to unauthorized access to other organizations' data
Solution Approach 1:
The patent applies local quality by implementing context-dependent data filtering where the same bulk query result is selectively filtered based on the specific organization's authorization context. When data is retrieved for Organization A, only Organization A's authorized data fields and records are included, even though the underlying query may retrieve data for multiple organizations. This ensures each organization receives complete data relevant to its needs while maintaining security by excluding unauthorized organization data through context-aware filtering.
Solution Approach 2:
The patent implements dynamic filtering where the data subset returned to each organization is determined at runtime based on the requesting organization's identity and authorization level. The filtering logic dynamically adapts to each organization's specific permissions, ensuring that Organization A receives only its authorized data while Organization B receives its own authorized data, even though both query the same database. This dynamic approach maintains data completeness for each organization while enforcing security constraints.
Data Source
AI summary
Mechanisms and methods for pushing data to a plurality of devices of a plurality of organizations are provided. Queries are handled in bulk for a group of users of an organization or the entire organization, and limited results are sent to a middle tier server between the database system and the user devices. These mechanisms and methods for pushing data to a plurality of devices enable an efficient and transparent transfer of data to user devices. This efficient and transparent transfer of data can enable mobile devices of many organizations to seamlessly have the data that is required to perform business.