Dynamic Server Selection for Network Service Latency
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Solution Overview
Problem
User experience in cloud-based services, such as media conferencing, is hindered by latency issues due to the geographical location of hosting servers relative to participants, leading to inconsistent performance across different user locations.
Innovation Solution
A system that evaluates and selects hosting servers based on geographic locations of participants, performance metrics like Round-Trip Time (RTT), operational constraints, and user preferences to ensure optimal user experience, using a graphical user interface and machine learning models to dynamically choose the best hosting servers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If hosting servers are located in a single geographic location (e.g., West Coast), then the service provider can simplify server management and deployment, but participants in distant locations (e.g., Europe) experience high latency and poor user experience
Solution Approach 1:
The patent divides the server infrastructure into multiple geographic regions, with hosting servers distributed across different locations (e.g., West Coast, East Coast, Europe). This segmentation allows participants in different regions to connect to nearby servers, reducing latency while maintaining simplified centralized management through the service provider's coordination system.
Solution Approach 2:
The service provider acts as an intermediary that automatically selects and manages hosting servers based on participant locations. This mediator coordinates between participants and multiple server locations, reducing the complexity of direct participant-server location matching while minimizing latency through intelligent server selection.
2Loss of time
If hosting servers are distributed across multiple geographic locations, then participants experience lower latency and improved user experience, but the service provider faces increased complexity in server selection and management
Solution Approach 1:
The system implements automated self-service mechanisms where the server selection and management processes occur automatically without manual intervention. The service provider's system autonomously evaluates participant locations, server availability, and performance metrics to make optimal server selections, reducing operational complexity despite the distributed architecture.
Solution Approach 2:
The patent dynamically changes selection parameters based on real-time conditions, including participant geographic location, server load, and network performance metrics. This parameter-based dynamic selection simplifies the complexity by providing clear, measurable criteria for server choice rather than requiring complex manual decision-making processes.
3Ease of operation
If the location of hosting servers is determined by the organizer's location, then the organization process is simplified, but participants in distant locations experience degraded service quality
Solution Approach 1:
The patent transitions from a static server location determination (based solely on organizer location) to a dynamic selection process that considers real-time factors including all participant locations, server availability, and network conditions. This dynamic approach maintains operational simplicity while significantly improving service quality for all participants regardless of geographic distribution.
Data Source
AI summary
Implementations for selecting hosting server(s) in a particular availability zone for a network service involving a plurality of participants is described. A request for a network service involving a plurality of nodes is received from a computing device associated with an organizer. Geographic locations of the plurality of nodes involved in the network service, the type of the network service, performance of a plurality of servers, and operational constraints of the plurality of servers are evaluated. At least two of the plurality of servers are located in different geographical locations. One or more of the plurality of servers to host the network service are selected based on the evaluation.