Multi-Level Load Balancer Combining Algorithm Results
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Solution Overview
Problem
Current load balancing systems lack sophistication and granularity in distributing client requests across servers, as they rely on single algorithms and modules, which can lead to inefficient resource utilization and potential server overload.
Innovation Solution
A multi-level load balancing system that combines the results from multiple load balancing modules and algorithms, using a configuration matrix to weight and combine rankings from different modules, allowing for more nuanced and precise selection of resource nodes based on various operational factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a single load balancing module and algorithm are used, then the system is simple and easy to operate, but the load balancing lacks sophistication and granularity leading to inefficient resource utilization
Solution Approach 1:
The load balancing system is segmented into multiple independent modules (round robin module, business module, data transfer module, response time module), each handling a specific aspect of load balancing. This segmentation allows the system to achieve sophisticated multi-factor load balancing while maintaining operational simplicity through modular design, where each module can be independently configured and executed.
Solution Approach 2:
The system transitions from single-dimension load balancing (one algorithm) to multi-dimensional load balancing by combining multiple algorithms that operate on different dimensions or aspects of server performance. The configuration module orchestrates these multi-dimensional approaches to achieve comprehensive resource optimization.
2Productivity
If multiple load balancing modules are combined, then load balancing granularity and sophistication are improved, but the device complexity increases
Solution Approach 1:
The configuration module serves as a universal orchestrator that manages multiple load balancing modules, providing a single point of control for complex multi-factor load balancing decisions. This multi-functional configuration approach simplifies the overall system architecture by centralizing the complexity management.
Solution Approach 2:
The system performs preliminary actions by pre-configuring multiple load balancing modules and their execution sequences before actual load balancing operations. This allows the complex multi-module system to operate efficiently without real-time complexity management, as the execution order and parameters are predetermined.
3Device complexity
If a single load balancing algorithm is used, then the system is simple, but it cannot consider multiple operational factors simultaneously leading to potential server overload
Solution Approach 1:
Multiple load balancing algorithms (round robin, business, data transfer, response time) are merged into a unified execution framework where the configuration module coordinates their combined results. This merging allows the system to consider multiple operational factors simultaneously while maintaining a relatively simple overall structure through unified management.
Solution Approach 2:
The load balancing system uses a composite approach by combining different algorithms with different strengths and weaknesses, similar to using composite materials. Each algorithm contributes specific capabilities (round robin for distribution, business for busy-ness assessment, data transfer for bandwidth optimization, response time for performance tuning), and their composite combination provides comprehensive server overload prevention.
Data Source
AI summary
The multi-level load balancing system receives requests for resources provided by any of a plurality of resource nodes. The multi-level load balancing system receives a first result from a first load balancing module that orders each of the plurality of nodes that are available to service the request based on a first algorithm. The multi-level load balancing system then receives a second result from a second load balancing module that orders each of the plurality of nodes that are available to service the request based on a second algorithm. The multi-level load balancing system combines the first result and the second result to form a third result that is uses to select one of the plurality of resources nodes to service the request.