Load Balancer for Database Availability
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Solution Overview
Problem
Existing server systems face challenges in maintaining constant uptime and minimizing errors due to sudden surges in network queries and the need for periodic maintenance, which can lead to server crashes and reduced availability.
Innovation Solution
A computer-implemented system and method that monitor utilization rates of multiple network-connected databases, select a target database based on load sharing ratios, and route data queries to optimize load distribution across servers, allowing for intelligent traffic routing and minimizing the load on individual servers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple servers are implemented to share load, then server availability is improved, but device complexity increases due to routing algorithm requirements
Solution Approach 1:
The patent introduces a load balancer as an intermediary component that sits between user devices and multiple servers. The load balancer receives incoming requests, applies routing algorithms to determine optimal server selection based on utilization rates, and forwards requests to appropriate servers. This mediator approach maintains high server availability through intelligent load distribution while keeping user devices simple without requiring them to implement complex routing logic.
Solution Approach 2:
The load balancer continuously monitors server utilization rates and uses this feedback information to dynamically adjust request routing decisions. By implementing real-time monitoring of server load and using this feedback to guide traffic distribution, the system optimizes server availability and performance without increasing device complexity, as all intelligence is centralized in the load balancer rather than distributed to user devices.
2Device complexity
If load is concentrated on fewer servers, then device complexity is reduced, but server reliability deteriorates due to higher failure risk
Solution Approach 1:
The patent segments the server infrastructure into multiple independent server instances that can be individually managed and monitored. By dividing the overall service capacity across multiple segmented servers rather than relying on a single server or simple load distribution, the system reduces the failure risk associated with any single server while maintaining manageable complexity through the load balancer's centralized control.
3Reliability
If servers are taken offline for maintenance, then server reliability is improved through maintenance, but service availability deteriorates
Solution Approach 1:
The patent merges multiple server instances into a unified service architecture where the load balancer distributes traffic across available servers. This combination allows the system to maintain service availability during maintenance by routing traffic to healthy servers while degraded or maintained servers are temporarily excluded from the active pool. The merged architecture ensures that maintenance activities on individual servers do not result in service interruptions.
4Productivity
If intelligent routing is implemented, then productivity is improved through optimized load distribution, but device complexity increases
Solution Approach 1:
The load balancer serves as an intermediary that centralizes all intelligent routing logic and load distribution algorithms. By placing this functionality in a dedicated intermediary component rather than distributing complexity across multiple devices or requiring changes to user devices, the system achieves high productivity through optimized load distribution while minimizing the complexity impact on the overall system architecture.
Data Source
AI summary
Systems and methods for monitoring utilization rates of a plurality of network-connected databases; receiving a first data read request from a first user device for a data element stored in the plurality of network-connected databases; selecting a first target database among the plurality of network-connected databases based on the utilization rates and a load sharing ratios; generating a first data query for a copy of the data element stored in the first target database; and forwarding the copy of the data element from the first target database to the first user device in response to the first data read request.