Filtering Rule Download Algorithm for Mobile Devices
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Solution Overview
Problem
Mobile devices face resource constraints and performance issues when downloading large volumes of filtering rules, leading to a trade-off between user experience and detection rate, as existing solutions struggle to handle numerous rules without causing application crashes or slowing down the device.
Innovation Solution
An algorithm that prioritizes and fragments filtering rules for delayed downloading, adjusting parameters based on mobile device conditions, such as reducing part size and increasing time intervals during critical situations, to manage resource burden and ensure reliable rule deployment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a large volume of filtering rules is loaded onto the mobile device, then the detection rate of undesirable content is improved, but the user experience deteriorates due to slowed device performance and increased crash risk
Solution Approach 1:
The patent divides the complete set of filtering rules into multiple smaller groups that can be downloaded and applied in sequential batches. This segmentation allows the system to load rules incrementally rather than all at once, reducing the immediate resource burden on the mobile device while still achieving comprehensive coverage over time. The rules are segmented into manageable portions that can be processed without causing crashes or excessive slowdown.
Solution Approach 2:
The patent implements preliminary action by downloading and preparing filtering rules in advance during periods of low device usage or in background processes. This allows the rules to be ready for immediate application when needed, without forcing the user to wait for large rule sets to download in real-time. The system proactively prepares filtering capabilities before they are required, reducing the impact on user experience when filtering is actually needed.
2Reliability
If a large volume of filtering rules is downloaded, then the detection rate is improved, but the downloading time increases and application crashes become more likely
Solution Approach 1:
The patent segments the rule download process into multiple smaller, manageable batches that can be downloaded in parallel or sequentially without overwhelming the device. Each batch contains a limited number of rules that can be processed within acceptable timeframes, avoiding the need to wait for entire large rule sets to download before seeing any filtering effect.
Solution Approach 2:
The patent implements periodic action by scheduling rule downloads and applications at regular intervals rather than continuously. The system can download rules during off-peak times, apply them in batches, and pause between operations to allow the device to process and stabilize with each batch before proceeding to the next one. This periodic approach prevents continuous resource consumption and reduces crash risk.
3Reliability
If the number of filtering rules is increased, then the detection rate is improved, but the resource burden on the mobile device increases
Solution Approach 1:
The patent segments the filtering rules into smaller groups that can be loaded and processed in batches, reducing the immediate memory and processing requirements on the device. Instead of loading all rules at once, the system manages them in manageable segments that fit within the device's available resources, extending the time before all rules must be simultaneously present in memory.
Solution Approach 2:
The patent uses preliminary action to download and prepare rules in advance during periods when device resources are less constrained, such as during idle times or when the device is in a low-power state. This allows the system to accumulate rules before they are actually needed for filtering, reducing the immediate resource burden at the moment of application while still achieving comprehensive filtering capability.
Data Source
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AI summary
Disclosed are techniques for downloading of filtering rules onto a mobile device. The described technique includes determining, from among at least two lists of filtering rules intended for downloading onto a mobile device, a priority sublist with a high indicator of frequency of actuation of the filtering rules from the list. The priority list is downloaded onto the mobile device. Each of the remaining non-downloaded lists of filtering rules is broken up into parts of a certain size, and a set of groups of filtering rules is formed, in each of whose groups is placed not more than one part of each remaining non-downloaded list of filtering rules. The groups of filtering rules are downloaded onto the mobile device with a certain interval of time until said formed set of groups is fully downloaded.