Client Update Server Using User Preference Analysis
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Solution Overview
Problem
Conventional client update processes waste network resources and decrease update efficiency by updating all packages, even if only a subset of functions are regularly used, leading to longer update times in congested network environments.
Innovation Solution
The server determines user preferences by analyzing usage patterns and releases only the update packages required for the user's preferred functions, conserving network resources and improving update efficiency by using a version tree comparison technique and update table management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all update packages are released to update the client, then the client is fully updated with all functions, but network resources are wasted and update time is substantially lengthened
Solution Approach 1:
The update packages are segmented into multiple categories including preferred function packages, non-preferred function packages, and dependent packages. The server analyzes user behavior to identify which function packages are actually used by the user, then selectively releases only those necessary update packages rather than all packages, thereby reducing update time while maintaining update completeness for used functions.
2Reliability
If all update packages are released to update the client, then the client is fully updated with all functions, but network resources are wasted
Solution Approach 1:
The server extracts and identifies the subset of update packages that are actually necessary for the user based on analysis of user behavior data. By taking out only the preferred function packages and necessary dependent packages that the user actually uses, the system avoids transmitting unnecessary update packages, thereby conserving network resources while ensuring complete updates for all used client functions.
3Reliability
If conventional update process updates all packages, then all client functions are updated, but update efficiency decreases
Solution Approach 1:
The update process is made dynamic by analyzing user behavior patterns to adaptively determine which update packages are necessary. The server dynamically identifies preferred function packages based on actual user usage, rather than using a static approach of updating all packages. This dynamic adaptation increases update efficiency by focusing resources on actually used functions while maintaining completeness of updates for those functions.
Data Source
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AI summary
Embodiments of the present application relate to a method for updating a client, a device for updating a client, and a computer program product for updating a client. The method includes determining whether the client is to be updated, in the event that the client is to be updated, determining update packages for the client, determining a user's preferred functions from among functions offered by the client based on saved record of operations of the user corresponding to the client, determining update packages, from among the determined update packages, on which the user's preferred functions depend to serve as preferred packages, and releasing the preferred packages to the client to be updated.