Distributed Computing Task Management via Dynamic Load Monitoring
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Solution Overview
Problem
Conventional distributed computing systems face limitations due to uneven processing loads across resources, fixed resource allocations, and inefficient utilization of resources, leading to suboptimal performance in handling large data processing tasks.
Innovation Solution
A distributed computing task management system that monitors and adjusts the performance of resources in a virtual computing environment, dynamically allocating virtual objects and resources based on processing load characteristics to ensure optimal performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If fixed resource allocations are used in distributed computing systems, then device complexity is reduced and ease of operation is improved, but productivity deteriorates due to uneven processing loads and inefficient resource utilization
Solution Approach 1:
The patent implements dynamic resource allocation by continuously monitoring processing loads across multiple resources and automatically adjusting resource assignments based on current system state. The system transitions from static fixed allocations to dynamic adaptive allocations, where resources are reassigned to tasks based on real-time load conditions, thereby improving processing efficiency without requiring complex manual intervention
Solution Approach 2:
The system incorporates feedback mechanisms by monitoring processing loads on various resources and using this information to make informed decisions about resource allocation. The monitoring component continuously collects data on resource utilization, and this feedback drives the dynamic adjustment of task-to-resource assignments, creating a closed-loop control system that optimizes productivity automatically
2Productivity
If dynamic resource adjustment is implemented, then productivity is improved through optimal resource utilization, but device complexity increases due to monitoring and adjustment mechanisms
Solution Approach 1:
The system implements self-service by enabling resources to automatically monitor their own processing loads and participate in their own reassignment decisions. Each resource reports its current load state, and the system automatically reallocates tasks based on this self-reported information, eliminating the need for external manual management and reducing operational complexity despite the dynamic nature of the system
Solution Approach 2:
The system performs preliminary actions by pre-establishing monitoring capabilities and automated decision-making rules before load imbalances occur. The monitoring infrastructure is built in advance, and allocation algorithms are pre-configured to respond to specific load conditions, allowing the system to dynamically adjust resources proactively rather than reactively, thereby managing complexity through advance preparation
Data Source
AI summary
A distributed computing task management system includes an application for monitoring a processing load of multiple resources that are used to execute a distributed computing task. The resources include at least one hardware resource and one or more virtual objects executed on the hardware resources in a virtual computing environment. Using the monitored processing load, the application adjusts a performance of the resources to compensate for changes in the processing load incurred by the resources due to execution of the distributed computing task.