In-Memory Data Grid Load Balancer Reallocation Controller
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Solution Overview
Problem
Conventional in-memory data management (IMDM) systems face issues with uneven data distribution across nodes, leading to performance imbalances and quality of service degradation, as the load balancer does not effectively reallocate data, resulting in some nodes becoming overloaded and slower than others.
Innovation Solution
An optimized reallocation process is implemented, where a reallocation process controller determines actionable load imbalances and relocates data elements from source nodes to target nodes based on predefined criteria, such as data usage, time thresholds, and predictive analytics, ensuring balanced node loads without impacting client requests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a conventional load balancer distributes data to the least-loaded node, then new data allocation is simplified, but existing data becomes unevenly distributed causing performance imbalance
Solution Approach 1:
The system separates the load balancing function into two distinct components: (1) a load balancer that handles new data allocation to least-loaded nodes, and (2) a reallocation process that periodically redistributes existing data elements to maintain uniform distribution. This segmentation allows each component to specialize in its function without compromising the other.
Solution Approach 2:
The reallocation process operates periodically in the background to preemptively correct distribution imbalances before they significantly impact performance. By performing preliminary redistribution actions, the system prevents performance degradation rather than reacting to it after it occurs.
2Speed
If data is maintained in-memory without reallocation, then access speed is maximized, but data distribution becomes uneven over time
Solution Approach 1:
The system implements periodic reallocation cycles that temporarily suspend normal operations to redistribute data elements across nodes. These periodic actions occur at predetermined intervals or when imbalance thresholds are exceeded, ensuring that in-memory access speed is maintained during normal operation while distribution uniformity is restored periodically.
Solution Approach 2:
The reallocation process acts as an intermediary mechanism between the load balancer and the data nodes. It monitors distribution patterns and intervenes to redistribute data elements, serving as a mediator that reconciles the conflict between maintaining fast in-memory access and preserving uniform distribution.
3Reliability
If the load balancer queues requests to heavily loaded nodes, then service continuity is maintained, but quality of service deteriorates and financial penalties may occur
Solution Approach 1:
The reallocation process performs preliminary data redistribution to prevent heavily loaded nodes from becoming bottlenecks. By proactively balancing data distribution before service degradation occurs, the system avoids the need to queue requests, thereby maintaining both service continuity and high quality of service.
Solution Approach 2:
The system implements feedback mechanisms where the load balancer and reallocation process continuously monitor node load conditions. When imbalances are detected, the reallocation process is triggered to correct the distribution, creating a closed-loop control system that prevents service quality deterioration while maintaining continuity.
Data Source
AI summary
An in-memory data management (IMDM) system is described that includes an IMDM cluster, a load balancer, and a reallocation processor controller. The IMDM cluster includes a plurality of nodes. The controller determines whether there is an actionable load imbalance of existing data elements, stored among the plurality of nodes, based on a predefined criteria or rule. The controller further identifies a source node from which at least one data element is to be deleted and a target node to which the at least one data element that is to be deleted is to be added. The source node and target node contribute to the actionable load imbalance. The controller copies the at least one data element that is to be deleted from the source node into the target node, and deletes the at least one data element that is to be deleted from the source node.