Behavioral Intelligence for Cloud Native Edge Software Disaggregation
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Solution Overview
Problem
Current cloud native edge computing systems face challenges in efficiently deploying and managing software components across diverse infrastructure, leading to increased time, cost, and complexity, as they often require all components to be deployed on the same platform, regardless of resource intensity.
Innovation Solution
The implementation of behavioral intelligence facilitates the deployment of software components by assessing and disaggregating functions, determining optimal infrastructure, and dynamically adapting them to run on different platforms, allowing expensive resources to be utilized only for critical functions while less expensive resources handle less demanding tasks, thereby reducing deployment complexity and cost.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all software components are deployed on the same platform, then system reliability is improved, but deployment complexity and cost increase
Solution Approach 1:
The patent segments software components into different deployment categories based on their resource intensity and criticality. Critical functions requiring high reliability are deployed on standardized expensive infrastructure, while non-critical functions are deployed on diverse less expensive infrastructure. This segmentation allows the system to maintain reliability for essential operations while reducing overall deployment complexity and cost through selective platform usage.
2Reliability
If all software components are deployed on the same platform, then system reliability is improved, but deployment cost increases
Solution Approach 1:
The patent applies local quality by assigning different deployment qualities to different software components based on their specific requirements. Critical functions receive the quality of standardized expensive infrastructure ensuring high reliability, while non-critical functions utilize diverse less expensive infrastructure. This localized quality assignment optimizes the balance between reliability and cost by matching infrastructure quality to functional requirements rather than applying uniform deployment across all components.
3Productivity
If behavioral intelligence is implemented to disaggregate functions, then resource allocation efficiency is improved, but system complexity increases
Solution Approach 1:
The patent introduces behavioral intelligence as an intermediary layer between software components and infrastructure. This intermediary automatically assesses resource intensity, determines optimal deployment targets, and manages the disaggregation process. By offloading the complex decision-making to this specialized intermediary, the system achieves improved resource allocation efficiency while the complexity is encapsulated within the behavioral intelligence module rather than propagating through the entire system.
Data Source
AI summary
Behavioral intelligence can be used with cloud native computing to enhance software deployment for various infrastructures by analyzing and deploying software functions according to the various infrastructures. Because different providers can have their own systems and controls for managing their infrastructures, it is costly to deploy software functions that are coupled together. However, if the software functions are disaggregated and translated according to the systems and controls relative to the various infrastructures, then the software functions can be failed and scaled independently of one another, thereby generating efficiencies.