AI Optimization Layer for Cloud Resource Bottlenecks

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Solution Overview

Problem

Cloud computing systems face challenges in enhancing performance without altering existing applications or code, particularly due to resource bottlenecks and inefficiencies in handling service requests, which can lead to suboptimal turn-around times and resource utilization.

Innovation Solution

An AI-based optimization layer is introduced that analyzes data paths within cloud computing environments to identify bottlenecks and implement dynamic adjustments, such as prioritizing thread access to locks and optimizing connection types, to enhance resource usage without modifying application code.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If cloud computing systems process service requests using conventional resource management methods, then system stability is maintained, but resource utilization efficiency deteriorates due to bottlenecks and suboptimal turn-around times

Engineering Contradiction:

Improveresource utilization efficiencyVSAvoidturn-around time

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system dynamically adjusts resource allocation and processing priorities based on real-time analysis of data paths and resource usage patterns. The optimization layer continuously monitors system state and adapts threading strategies, lock management, and connection handling to current conditions, transforming static resource management into a dynamic responsive system that improves both productivity and reduces time loss.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The invention changes key system parameters including thread priorities, lock acquisition strategies, connection types, and buffer sizes based on analyzed data paths. By modifying these parameters dynamically rather than using fixed configurations, the system optimizes resource utilization efficiency while minimizing turn-around times for service requests.

Inventive Principle:

Principle #35Parameter changes

2Productivity

If optimization actions are implemented to improve resource usage, then resource utilization efficiency improves, but system complexity increases due to the optimization layer

Engineering Contradiction:

Improveresource utilization efficiencyVSAvoidsystem architecture complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The optimization layer acts as an intermediary between the application layer and the operating system/kernel. It intercepts service requests, analyzes data paths, determines optimization actions, and implements them without requiring modifications to existing applications. This mediator approach enables improved resource utilization while isolating the added complexity within the optimization layer itself.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system performs self-optimization by automatically analyzing its own data paths and resource usage patterns, then implementing optimization actions without external intervention. The optimization layer monitors itself and continuously improves system performance autonomously, reducing the need for manual configuration and simplifying overall system management despite the added architectural layer.

Inventive Principle:

Principle #25Self-service

3Measurement precision

If data path analysis is performed to identify resource usage patterns, then optimization accuracy improves, but processing overhead increases

Engineering Contradiction:

Improveresource usage identification accuracyVSAvoidprocessing overhead

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The system performs partial analysis of data paths by focusing on critical resource usage points and bottlenecks rather than analyzing every aspect of system operation. By concentrating measurement efforts on the most impactful areas, the system achieves high optimization accuracy while minimizing the processing overhead associated with comprehensive monitoring.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS20240205113A1Enhancing performance in network-based systems

Publication Date: 2024.06.20 INTEL CORP

AI summary

A method, system, and computer program product, the method comprising: obtaining a data path representing flow of data in processing a service request within a network computing environment having system resources; analyzing the data path to identify usage of the system resources required by the service request processing; determining, based on the usage of the system resources, an optimization action expected to improve the usage of the system resources; and implementing the optimization action in accordance with the data path, thereby modifying operation of the cloud computing environment in handling future service requests.