PID Feedback Control for Content Selection Latency
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Solution Overview
Problem
Conventional online systems face a trade-off between content quality and system performance due to limited computing resources, where increasing the number of content items evaluated improves quality but worsens latency and user experience, and vice versa.
Innovation Solution
Implementing a feedback control mechanism that distributes content items for evaluation among available computing devices to maximize the number evaluated within a target latency period, using a PID controller to adjust the number based on measured latency periods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the number of content items evaluated is increased, then content quality improves, but latency period increases and system performance declines
Solution Approach 1:
The patent segments the content evaluation process by dividing content items into different priority levels (high-priority and low-priority content). High-priority content items are evaluated immediately with guaranteed computing resources, while low-priority content items are evaluated when computing resources are available. This segmentation resolves the contradiction by ensuring quality content is evaluated without uniformly increasing latency for all content types.
Solution Approach 2:
The system dynamically changes the parameter of computing resource allocation based on system load conditions. When computing resources are abundant, more content items are evaluated; when resources are constrained, the number of evaluated content items is reduced. This dynamic parameter adjustment allows the system to maintain content quality when possible while preventing latency increases during high-load periods.
2Manufacturing precision
If the number of content items evaluated is increased, then content quality improves, but system performance declines
Solution Approach 1:
The patent implements dynamic computing resource allocation where the system continuously monitors computing resource availability and adjusts the number of content items to evaluate accordingly. This dynamic approach allows the system to maintain high content quality when resources are available while preserving system performance during resource-constrained periods, resolving the static trade-off between quality and performance.
Solution Approach 2:
The system employs self-service mechanisms through automated content selection algorithms that independently determine which content items to evaluate based on current system conditions. The content selection system autonomously manages computing resource allocation without requiring external intervention, enabling the system to self-optimize between content quality and performance based on real-time conditions.
3Manufacturing precision
If computing resources are increased to evaluate more content items, then content quality improves, but resource constraints are violated
Solution Approach 1:
The system changes the parameter of content evaluation quantity based on available computing resources. Instead of allocating fixed resources or uniformly evaluating all content items, the system dynamically adjusts how many content items are evaluated based on current resource availability. This allows the system to maintain content quality within the constraints of limited computing resources.
Solution Approach 2:
The patent applies partial action by evaluating only a subset of content items rather than all available content. The system selectively evaluates content items based on priority levels and resource availability, performing partial evaluation that is sufficient to maintain quality without requiring excessive computing resources that would violate system constraints.
Data Source
AI summary
When an online system receives a request to present content items to a user, a content selection system included in the online system selects content items for presentation to the user during a latency period from the time the request was received until the time when the content items are sent. A feedback control mechanism communicates with each computing device of the content selection system to determine the latency period of each computing device. The feedback control mechanism also determines a target latency period in which content items are selected. By comparing the latency period of each computing device to the target latency period, an amount of information to be evaluated by each computing device is determined based on whether a computing device's latency period is greater than or less than the target latency period.