Intelligent Mobile App Update Scheduling via Device Parameters
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Solution Overview
Problem
Existing mobile application update systems often overwhelm application distribution platforms due to high volumes of requests, leading to inefficient processing and delayed updates for users.
Innovation Solution
A method and system that utilize an intelligent mobile application update program to assess the mobile device's parameters, such as location, network connection, and security settings, to determine the optimal time and location for updating mobile applications, thereby managing the update process to avoid overwhelming the distribution platform and ensure timely delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If mobile applications update continuously without scheduling control, then users receive timely updates, but application distribution platforms become overwhelmed by high volumes of requests
Solution Approach 1:
The system performs preliminary actions by assessing device parameters (location, network connection type, security settings) before initiating updates. This pre-evaluation allows the system to schedule updates strategically, ensuring devices are ready to receive updates without overwhelming the distribution platform, thus preventing platform overload while maintaining reliable update delivery.
Solution Approach 2:
The update scheduling system dynamically adjusts update timing and frequency based on real-time device conditions and platform load. By making the update process adaptive rather than static, the system can respond to changing network conditions, device states, and platform capacity, preventing overwhelming the platform while ensuring timely updates reach users.
2Speed
If update requests are processed immediately without assessment, then update speed increases, but device-specific conditions are not considered leading to suboptimal update timing
Solution Approach 1:
The system applies local quality by tailoring update scheduling to specific device characteristics such as location, network connection type (Wi-Fi, cellular, WPAN), and security settings. Each device receives customized update timing based on its unique conditions, ensuring optimal update delivery for that particular device while maintaining overall system efficiency.
Solution Approach 2:
The system incorporates feedback mechanisms where device information (location, network status, security state) is continuously assessed and used to adjust update scheduling decisions. This feedback loop ensures that update timing is continuously optimized based on actual device conditions, balancing update speed with adaptability to device-specific requirements.
3Ease of operation
If updates are scheduled frequently to ensure timely delivery, then user experience improves, but the load on distribution platforms increases
Solution Approach 1:
The system applies partial action by scheduling updates based on specific triggering conditions rather than continuously. Updates are initiated only when device parameters indicate readiness (appropriate network connection, security settings, location) and platform capacity allows, reducing unnecessary update requests while ensuring timely delivery when conditions are favorable.
Solution Approach 2:
The system changes scheduling parameters dynamically based on device state and platform load conditions. By adjusting update frequency, timing, and triggering mechanisms according to real-time parameter changes in device conditions and platform capacity, the system optimizes the balance between user experience and platform load management.
Data Source
AI summary
In an approach for managing updates of a mobile software application, a computer receives information regarding a mobile computing device and a mobile software application on the mobile computing device, wherein the information regarding the mobile computing device comprises at least one or more of a location of the mobile computing device, a network connection type, a security bit associated with the mobile computing device, and a checksum associated with the at least one mobile software application. The computer determines whether the mobile software application matches a stored mobile software application on a computing device. Responsive to determining that the mobile software application does not match the stored mobile software application on the computing device, the computer determines an update policy for scheduling an update to the mobile software application on the mobile computing device.