Load Balancer Latency Probes for Individualized Content Delivery
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Solution Overview
Problem
Existing content delivery systems, including advertisement delivery, face inefficiencies due to broad categorization of client devices, leading to inaccurate optimization and increased latency, which affects user experience and ad impression value.
Innovation Solution
Implementing individualized connectivity based request handling through proactive connectivity probes that measure current latency and bandwidth, allowing for tailored content delivery and ad auction timing adjustments based on precise device conditions, thereby optimizing content and ad delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If broad categorization of client devices is used, then device management is simplified, but optimization accuracy decreases and latency increases
Solution Approach 1:
The patent segments client devices from broad categories into individualized connections, creating unique session variables for each device based on specific connectivity metrics such as latency and bandwidth. This segmentation allows precise measurement and tailored optimization for each device while maintaining manageable complexity through automated session tracking.
Solution Approach 2:
The patent changes parameters by measuring specific connectivity metrics (latency, bandwidth) for each individual device connection and using these measured parameters to dynamically adjust content delivery optimization and ad auction timing, moving from static broad categorization to dynamic individualized parameter-based handling.
2Productivity
If individualized connectivity measurement is implemented, then content delivery optimization improves, but system complexity and processing load increase
Solution Approach 1:
The system implements self-service by automatically measuring connectivity metrics, creating individualized session variables, and adjusting content delivery parameters without manual intervention. The load balancer autonomously probes network conditions, tracks session state, and makes optimization decisions, reducing the perceived complexity for users while maintaining high productivity.
Solution Approach 2:
The patent implements feedback mechanisms where the load balancer continuously measures connectivity metrics, uses this feedback to adjust session variables and target node selection, and monitors the results to further optimize content delivery. This closed-loop feedback system improves productivity while managing complexity through automated adaptation.
3Loss of time
If session-based individualized handling is used, then latency optimization improves, but data center processing load increases
Solution Approach 1:
The patent applies preliminary action by measuring connectivity metrics and establishing individualized session variables before content delivery occurs. The load balancer probes network conditions upfront, creates optimized session parameters, and pre-selects target nodes based on measured latency, reducing actual delivery latency while spreading processing load over time.
Solution Approach 2:
The system uses dynamics by making session variables and target node selections adaptive based on real-time connectivity measurements. Rather than static processing for all devices, the system dynamically adjusts handling parameters for each session based on measured conditions, optimizing latency while processing load adapts to actual network states.
Data Source
AI summary
Individualized connectivity based request handling is disclosed. For example, a content source is accessed by a client device and a load balancer executes on a processor to receive a first request based on the client device accessing the content source. A first session variable is set to a first value in a first session and a first latency to the client device is measured. A first plurality of target nodes is selected based on the first session variable. A first plurality of messages is sent to the first plurality of target nodes. A second request is received from the client device after the first session expires, starting a second session. The first session variable is set to a different second value in the second session. A second plurality of messages is sent to a second plurality of target nodes different from the first plurality of target nodes.