Latency-Aware Workload Generation Using Resource Device Pool Analysis

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Current computing systems face inefficiencies in managing workloads across resource devices, leading to suboptimal performance and compliance with latency, security, and data compliance requirements due to inadequate resource allocation and monitoring.

Innovation Solution

A method and system for managing workloads by identifying available resource devices, performing latency analysis, and selecting optimal device combinations based on total latency cost, while ensuring security and data compliance through resource allocation and remediation processes.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If resource devices are allocated to workloads without latency analysis, then resource allocation speed is improved, but workload performance deteriorates due to suboptimal resource combinations

Engineering Contradiction:

Improveresource allocation speedVSAvoidworkload performance

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system performs latency analysis and identifies optimal resource device combinations in advance before workload execution. The management module pre-calculates latency costs for different resource combinations and selects the optimal configuration beforehand, ensuring both fast allocation and high performance.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system skips unnecessary resource allocation steps by directly selecting pre-identified optimal resource combinations. The latency analysis enables the system to quickly determine the best resource configuration without iterative testing, accelerating the allocation process while maintaining performance.

Inventive Principle:

Principle #21Skipping (Rushing through)

2Measurement precision

If latency analysis is performed on all available resource devices, then resource allocation accuracy is improved, but processing time increases

Engineering Contradiction:

Improveresource allocation accuracyVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system applies latency analysis selectively to specific resource device combinations that are most relevant to the workload requirements. Instead of uniformly analyzing all possible combinations, the management module focuses on locally optimal configurations that match the workload's resource needs, reducing processing time while maintaining accuracy.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system changes the analysis parameters by focusing on latency cost metrics specific to each resource combination. The management module adjusts the depth and scope of latency analysis based on workload characteristics, performing detailed analysis only where necessary to achieve accurate resource allocation.

Inventive Principle:

Principle #35Parameter changes

3Reliability

If optimal resource device combinations are selected based on latency cost, then workload performance is improved, but system complexity increases

Engineering Contradiction:

Improveworkload performanceVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The management module autonomously performs latency analysis and selects optimal resource combinations without requiring complex external orchestration. The system self-manages the complexity of evaluating multiple resource configurations by implementing its own latency cost calculation and selection logic, simplifying the overall system architecture.

Inventive Principle:

Principle #25Self-service

4Productivity

If resource devices are dynamically allocated based on latency analysis, then resource utilization efficiency is improved, but monitoring and management complexity increases

Engineering Contradiction:

Improveresource utilization efficiencyVSAvoidmonitoring complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system implements feedback mechanisms where the management module continuously monitors workload performance and resource latency. Based on this feedback, the system dynamically adjusts resource allocations to maintain optimal efficiency. The feedback loop automates the monitoring process, reducing manual management complexity while improving utilization.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS11507486B2Method and system for generating latency aware workloads using resource devices in a resource device pool

Publication Date: 2022.11.22 DELL PROD LP

AI summary

A method for managing data includes obtaining, by a management module, a workload generation request, wherein the workload generation request specifies a plurality of resource devices, identifying available resource devices in a resource device pool based on the plurality of resource devices, performing a latency analysis on the available resource devices to obtain a plurality of resource device combinations and a total latency cost of each resource device combination, and selecting a resource device combination of the plurality of resource device combinations based on the total latency cost of each resource device combination, wherein the resource device combination comprises a second plurality of resource devices and wherein each of the second plurality of resource devices is one of the plurality of resource devices.