Dynamic Load Balancing for Enterprise Services Bus
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Static load balancing in Enterprise Services Bus (ESB) systems is not responsive to the dynamic needs of the underlying system, leading to inefficient traffic distribution as it does not adapt to changes in application instance metrics such as queue load and transaction times.
Innovation Solution
A dynamic load balancing method that adjusts distribution weights in real-time based on a load factor calculated from queue usage and average transaction times, using customizable weights and a Bresenham algorithm for efficient message routing, allowing for throttling during system overload by disregarding low-priority messages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static load balancing weights are used for routing messages, then the routing configuration is simple and stable, but the system cannot adapt to dynamic changes in application instance metrics such as queue load and transaction times
Solution Approach 1:
The patent implements dynamic load balancing by continuously adjusting routing weights based on real-time application instance metrics. The system monitors queue loads, transaction times, and other performance indicators, then dynamically recalculates distribution weights to optimize message routing. This transforms the static routing configuration into a dynamic system that adapts to changing conditions without requiring complex manual reconfiguration.
Solution Approach 2:
The system establishes a feedback loop where application instance metrics are continuously collected, processed, and used to adjust routing weights. The load balancer receives performance data from destinations, processes this information through weight calculation algorithms, and applies the updated weights to subsequent message routing decisions. This closed-loop feedback mechanism enables automatic adaptation to system conditions.
2Productivity
If dynamic weight adjustment based on multiple metrics is implemented, then message routing efficiency is optimized, but the calculation and processing overhead increases
Solution Approach 1:
The system performs preliminary actions by pre-calculating and caching weight adjustments based on metric thresholds and historical patterns. When metrics change, the system checks against pre-defined rules and cached calculations to determine weight adjustments, rather than performing full recalculations from scratch. This reduces processing time while maintaining routing optimization.
Solution Approach 2:
The system applies partial action by selectively updating only those routing weights that need adjustment based on current metric conditions, rather than recalculating all weights. The patent implements threshold-based triggers that activate weight adjustments only when metrics cross significant boundaries, reducing unnecessary processing overhead while maintaining routing efficiency during critical transitions.
3Measurement precision
If real-time monitoring of application instance metrics is performed, then load distribution accuracy is improved, but the system resource consumption increases
Solution Approach 1:
The system merges the monitoring and load balancing functions into a unified mechanism. The same infrastructure used for collecting application instance metrics is leveraged for both performance monitoring and weight calculation purposes. By combining these functions, the system avoids duplicating monitoring efforts and reduces overall resource consumption while maintaining accurate load distribution.
Solution Approach 2:
The patent implements multi-functionality by designing the metric collection infrastructure to serve multiple purposes: performance monitoring, weight calculation, and routing optimization. The same data collection mechanisms and processing pipelines are used across different functions, eliminating redundant resource usage and enabling accurate load distribution with minimized system overhead.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A method and system is provided for routing data in a system. The method includes determining an initial fixed distribution pattern, determining a queue parameter based on at least a current amount of system use and a maximum potential system use, determining a time parameter based on the time that a message in the application has been waiting for its processing, determining a load parameter based on at least the time parameter and the queue parameter, and modifying the distribution pattern based on at least the load parameter.