Dynamic Software Step Sequencing for Ad Bid Processing

Solution Overview

Problem

In the online advertising environment, existing systems face challenges in efficiently processing high volumes of advertisement bid requests while optimizing resource usage, leading to suboptimal performance and increased costs due to manual tuning difficulties and changing resource requirements.

Innovation Solution

Implementing an automated mechanism to dynamically optimize the order of software steps for processing advertisement bid requests based on tracked failure and resource metrics, allowing for adaptive sequencing to minimize resource usage and maximize filtering speed without human intervention.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If a fixed sequence of software steps is used for processing advertisement bid requests, then system simplicity is maintained, but resource usage efficiency deteriorates under varying load conditions

Engineering Contradiction:

Improvesoftware step sequencing mechanismVSAvoidbid request processing efficiency

Core Design Contradiction:

Device complexityVSProductivity

Solution Approach 1:

The patent implements dynamic reordering of software steps based on real-time performance metrics and resource conditions. The system transitions from a static fixed sequence to a dynamic adaptive sequence, where step ordering is adjusted continuously based on tracked failure rates and resource consumption patterns, resolving the contradiction between system simplicity and processing efficiency.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system incorporates feedback loops that monitor performance metrics (failure rates, resource usage) of each software step and use this feedback to automatically reorder steps. This closed-loop control mechanism enables the system to adapt its processing sequence based on actual performance data, improving efficiency without requiring complex manual configuration.

Inventive Principle:

Principle #23Feedback

2Manufacturing precision

If manual tuning of software step order is performed, then optimization for specific conditions is achieved, but adaptability to changing resource requirements deteriorates

Engineering Contradiction:

Improveprocessing optimization accuracyVSAvoidresource requirement adaptability

Core Design Contradiction:

Manufacturing precisionVSAdaptability or versatility

Solution Approach 1:

The system performs self-optimization by automatically monitoring its own performance metrics and reordering software steps without external intervention. The automated reordering mechanism tracks failure rates and resource consumption, then autonomously adjusts the step sequence to optimize processing efficiency, eliminating the need for manual tuning while maintaining adaptability to changing conditions.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent implements dynamic reordering of software steps based on real-time performance metrics and resource conditions. The system transitions from a static fixed sequence to a dynamic adaptive sequence, where step ordering is adjusted continuously based on tracked failure rates and resource consumption patterns, resolving the contradiction between system simplicity and processing efficiency.

Inventive Principle:

Principle #15Dynamics

3Manufacturing precision

If more software steps are executed to improve filtering accuracy, then advertisement filtering precision is improved, but processing time increases

Engineering Contradiction:

Improveadvertisement filtering accuracyVSAvoidbid request processing time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The system performs preliminary actions by executing software steps in an optimized sequence that places the most effective filtering steps first. By pre-determining the optimal order based on performance metrics, the system ensures that high-impact filtering occurs early in the processing pipeline, reducing overall processing time while maintaining filtering accuracy.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent implements dynamic reordering of software steps based on real-time performance metrics and resource conditions. The system transitions from a static fixed sequence to a dynamic adaptive sequence, where step ordering is adjusted continuously based on tracked failure rates and resource consumption patterns, resolving the contradiction between system simplicity and processing efficiency.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS10521829B2Dynamic ordering of online advertisement software steps

Publication Date: 2019.12.31 AMOBEE

AI summary

At a bid determination platform, an initial sequence having an initial order of software steps for filtering advertisements in response to receiving an advertisement bid request is selected. Until a trigger event occurs, the initial sequence of software steps is implemented in the initial order in response to receiving advertisement bid requests. Implementing the initial sequence comprises automatically tracking a failure (or success) metric and resource requirement metric for each of the software steps. After the trigger event occurs, a first optimum sequence of the software steps is automatically selected in a first optimum order so as to optimize a total resource usage for execution of the software steps. Selecting the first optimum sequence of the software steps in the first optimum order is based on the tracked failure (or success) metric and resource requirement metric for each of the software steps during implementation of the initial sequence.