Distributed Computing Workload Distribution via CPU Capacity Utilization

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Solution Overview

Problem

In distributed computing systems, unused CPU capacity is not fully utilized, leading to underutilization of resources and the need for additional computing entities to execute workload entities, which increases computing resource requirements.

Innovation Solution

The system identifies unused CPU units in computing entities and uses them to compress memory data, network traffic, or storage traffic, allowing additional workload entities to be executed within the defined resource limits, thereby optimizing resource usage.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If additional computing entities are added to execute more workload entities, then workload execution capacity is improved, but computing resource requirements and system cost increase

Engineering Contradiction:

Improveworkload execution capacityVSAvoidcomputing resource requirements

Core Design Contradiction:

ProductivityVSQuantity of substance

Solution Approach 1:

The patent changes the parameter of data representation by introducing compressed data structures that reduce the memory footprint of workload entities. This allows more workload entities to be executed within the same memory constraints, thereby increasing productivity without proportionally increasing computing resource requirements

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent implements a hierarchical data structure where compressed data structures are nested within the workload entity memory allocation. This nesting allows efficient space utilization by placing compressed data representations within the existing memory framework, enabling more workloads to fit within fixed resource limits

Inventive Principle:

Principle #7Nested doll (Nesting)

2Productivity

If computing entities are added to handle increased workload, then system throughput is improved, but infrastructure complexity and management burden increase

Engineering Contradiction:

Improvesystem throughputVSAvoidinfrastructure complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent implements self-service through automatic compression of workload entity data structures by the system itself. The compression mechanism operates autonomously within the existing computing entities, converting data representations to reduce memory usage without requiring manual intervention or additional management overhead, thus improving throughput while maintaining infrastructure simplicity

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS12288100B2Workload distribution by utilizing unused central processing unit capacity in a distributed computing system

Publication Date: 2025.04.29 RED HAT INC

AI summary

A technique for improving workload distribution by utilizing unused resources in a distributed computing system is described. In one example of the present disclosure, a system can determine that a computing entity of a distributed computing system includes an unused portion of a CPU capacity. The computing entity can have a first defined limit of the CPU capacity. The system can use the unused portion of the CPU capacity to improve a usage of a resource of the computing entity. The computing entity can have a second defined limit of the resource.