Dynamic Resource Allocation in Cluster Systems
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Solution Overview
Problem
Computer clusters face challenges in efficiently managing resources across multiple nodes, leading to performance degradations and resource underutilization due to lack of real-time monitoring and dynamic allocation of resources, which affects job completion times and overall cluster efficiency.
Innovation Solution
A dynamic resource monitoring and allocation system that continuously monitors resource utilization across nodes and adjusts resource allocation in real-time to ensure user-defined goals are met, using a supervisor controller and agent controller to manage CPU, network, and disk I/O resources, allowing for efficient distribution of tasks and sub-jobs across nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a software layer is employed to manage the activities of various computing nodes, then the operational complexities of vast numbers of nodes can be managed, but performance degradations and resource underutilization occur due to lack of real-time monitoring and dynamic allocation
Solution Approach 1:
The patent implements dynamic resource allocation by continuously monitoring resource utilization metrics (CPU, memory, disk I/O, network) and adjusting resource distribution in real-time based on current cluster conditions and job priorities, transforming static resource allocation into a dynamic adaptive system
Solution Approach 2:
The system employs feedback mechanisms where resource utilization data is collected from nodes, analyzed by the software layer, and used to generate control decisions that adjust resource allocation, creating a closed-loop control system that responds to actual cluster state
2Ease of operation
If static resource allocation is used to simplify management, then ease of operation is improved, but resource underutilization and performance degradation occur
Solution Approach 1:
The system enables nodes to self-monitor their resource utilization and automatically adjust resource allocation based on predefined policies and priorities, allowing the cluster to self-optimize without constant human intervention while maintaining operational simplicity
3Productivity
If real-time monitoring and dynamic allocation are implemented to improve productivity, then job completion time and cluster efficiency are improved, but device complexity increases due to additional controllers and monitoring mechanisms
Solution Approach 1:
The software layer is segmented into distinct functional components: supervisor controllers that manage overall resource allocation policies and agent controllers that execute local monitoring and adjustment tasks on individual nodes, distributing complexity across multiple specialized modules
4Loss of energy
If dynamic resource allocation is implemented to maximize resource utilization, then resource utilization is improved, but difficulty in detecting and measuring resource states increases
Solution Approach 1:
The agent controllers are designed as universal multi-functional components that simultaneously perform multiple tasks: collecting resource metrics, enforcing allocation policies, adjusting resource distribution, and reporting cluster state, consolidating diverse functions into unified controllers that simplify detection and measurement
Data Source
AI summary
In an embodiment, the systems, methods, and devices disclosed herein comprise a computer resource monitoring and allocation system. In an embodiment, the resource monitoring and allocation system can be configured to allocate computer resources that are available on various nodes of a cluster to specific jobs and/or sub-jobs and/or tasks and/or processes.