Dynamic Client-Server Adaptation for Mobile Fault Remediation
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Solution Overview
Problem
Current methods for fault detection and root cause analysis in web and mobile applications are often offline and manual, leading to resource and cost issues, as well as an inability to adapt mobile applications at runtime.
Innovation Solution
An analytics-based dynamic adaptation method that detects faults in client-server mobile applications by separating client devices into experimental and control groups, determining user controls related to faults, transmitting remote commands to disable or remediate these faults, and verifying fixes, using a pre-computed dependency graph to determine which user controls to enable or disable dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If fault detection and root cause analysis are performed offline and manually, then resource consumption is reduced, but productivity and adaptability deteriorate
Solution Approach 1:
The system performs fault detection, root cause analysis, and adaptive remediation automatically without manual intervention. The analytics engine continuously monitors application instances, identifies faults, determines affected user controls, and executes remediation actions autonomously, transforming manual offline processes into automated self-service operations.
Solution Approach 2:
The system pre-computes dependency graphs that map user controls to their dependencies before faults occur. This preliminary structuring of control relationships enables rapid fault analysis and automated remediation execution without manual intervention, improving productivity while managing complexity through pre-established frameworks.
2Reliability
If user controls are disabled to prevent futile transactions, then reliability is improved, but ease of operation deteriorates
Solution Approach 1:
The system selectively disables user controls only for specific application instances affected by detected faults, rather than globally disabling all controls. This localized approach maintains reliability for problematic transactions while preserving ease of operation for unaffected users and controls, implementing fine-grained quality differentiation.
Solution Approach 2:
The system dynamically adjusts the enabled/disabled state of user controls based on real-time fault detection and remediation status. Controls are temporarily disabled during faults and restored when remediation succeeds, creating a dynamic adaptation mechanism that balances reliability and ease of operation according to current system state.
3Loss of time
If manual fault analysis is used, then device complexity is reduced, but loss of time increases
Solution Approach 1:
The system replaces manual mechanical fault analysis with automated analytics processing. The analytics engine processes application logs, identifies patterns, determines fault causes, and executes remediation actions automatically, substituting human manual operations with computational mechanisms that operate continuously without time loss.
Solution Approach 2:
The system implements continuous feedback loops where fault detection results feed into automated remediation actions, which in turn provide feedback on resolution effectiveness. This closed-loop feedback mechanism rapidly resolves faults without manual intervention, reducing time loss while managing complexity through systematic feedback processing.
4Reliability
If all user controls are disabled during faults, then reliability is improved, but device complexity increases
Solution Approach 1:
The system applies differentiated quality treatment by disabling user controls only for specific application instances affected by detected faults, rather than globally disabling all controls. This localized approach maintains reliability for problematic transactions while preserving ease of operation for unaffected users and controls, implementing fine-grained quality differentiation.
Solution Approach 2:
The system segments user controls into distinct groups based on their dependency relationships and fault impact. By organizing controls into segments that can be independently managed and disabled, the system reduces overall complexity while maintaining comprehensive reliability coverage through targeted segmentation of affected controls.
Data Source
AI summary
Methods, systems, and computer program products for analytics-based dynamic adaptation of client-server mobile applications are provided herein. A computer-implemented method includes detecting faults arising from execution of application instances of a distributed mobile device application among multiple client devices; separating the multiple client devices into an experimental group and a control group; determining user controls of the distributed mobile device application related to the detected faults; transmitting commands to each application instance among the experimental group of client devices that disables the user controls; transmitting commands to each application instance among the experimental group and the control group of client devices that includes remedial actions pertaining to the detected faults; verifying that the remedial actions resolved the detected faults; and transmitting commands, subsequent to said verifying, to each application instance among the experimental group of client devices that enables the user controls.