Dynamic Traffic Shaping for Electronic Marketplace Server Stress Reduction
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Solution Overview
Problem
Conventional solutions for managing high traffic volumes in electronic environments, such as online marketplaces, often result in suboptimal resource utilization and increased risk of system failures due to hard limits on request rates, which can lead to user dissatisfaction and system crashes.
Innovation Solution
Implementing dynamic traffic shaping features, including sampling and shifting levers, to adjust and prioritize traffic requests based on actual and predicted velocities, thereby reducing stress on components and optimizing resource use without hard limits, while maintaining user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional hard limits on request rates are implemented, then system resource protection is improved, but user experience and service quality deteriorate due to request rejections and timeouts
Solution Approach 1:
The patent implements dynamic traffic shaping that continuously adjusts request processing capacity based on real-time system conditions. Instead of static hard limits, the system dynamically modulates the rate of request processing to match available server capacity, preventing resource exhaustion while maintaining smooth user experience without abrupt rejections
Solution Approach 2:
The system changes the parameter of request processing rate dynamically based on system load conditions. By monitoring server stress levels and adjusting the throughput parameter in real-time, the system adapts to varying conditions to protect resources while maintaining service quality, avoiding the fixed threshold approach that causes user experience degradation
2Productivity
If the number of users and requests increases, then service coverage and productivity are improved, but system stability deteriorates due to exceeding maximum allowable request rates
Solution Approach 1:
The patent implements a feedback mechanism that continuously monitors system load and request velocity, then uses this information to adjust traffic shaping parameters. This closed-loop control enables the system to handle increased request volumes while maintaining stability by automatically reducing processing rate when thresholds are approached, preventing system crashes
Solution Approach 2:
The system dynamically adapts its request processing capacity to match incoming traffic patterns and system conditions. By continuously adjusting the throughput parameter based on real-time monitoring, the system can scale handling capacity with user growth while maintaining stability through automatic rate modulation when load thresholds are approached
3Reliability
If conventional throttling with hard limits is applied, then resource protection is improved, but resource utilization efficiency deteriorates due to premature request rejections
Solution Approach 1:
The patent changes the approach from fixed parameter thresholds to dynamic parameter adjustment. By continuously monitoring system state and adjusting the request processing rate parameter in real-time, the system maximizes resource utilization up to capacity limits while providing smooth protection, avoiding the waste associated with premature rejections under hard limits
Data Source
AI summary
Techniques described herein include systems and methods for throttling requests for content to reduce stress on a check out pipeline associated with an electronic marketplace thereby avoiding overstressing a server to the point of no longer processing requests from users. In embodiments, first information may be maintained that identifies a ranking for a plurality of items based on a score. A predicted velocity of content requests about the plurality of items may be maintained and second information about an actual velocity of content requests about the plurality of items may be received. In response to a request for content, a portion of items may be identified based on the scores associated with said portion and partition the portion into a number of groups or partitions based on the predicted velocity and the second information. A data object that comprises the portion of items associated with a partition may be generated.