Orchestration Platform for Automated Container Deployment

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing wireless network systems face challenges in efficiently deploying containers that provide latency-sensitive and latency-insensitive services, as current methods require manual evaluation and selection by network operators, leading to suboptimal performance and user experience.

Innovation Solution

An automated deployment system that identifies and deploys sets of containers based on service attributes and container parameters, optimizing performance and network efficiency by selecting appropriate nodes for latency-sensitive services closer to devices and latency-insensitive services farther away, using an orchestration platform that communicates with a container repository and service information repository.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Extent of automation

If manual evaluation and selection of containers is used, then network operators can control deployment decisions, but service performance and user experience deteriorate due to suboptimal deployment

Engineering Contradiction:

Improvecontainer deployment automationVSAvoidservice performance

Core Design Contradiction:

Extent of automationVSReliability

Solution Approach 1:

The system enables self-service through an automated container selection and deployment mechanism. The orchestration platform automatically evaluates container attributes, matches them with service requirements, and deploys containers to appropriate nodes without human intervention, thereby improving both automation extent and service performance simultaneously

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the manual mechanical process of container selection with an automated computational system. The orchestration platform uses algorithmic matching between container attributes and service requirements, substituting human evaluation with automated decision-making that optimizes deployment based on latency sensitivity and node characteristics

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Loss of energy

If latency-sensitive services are deployed farther from devices, then infrastructure cost is reduced, but latency performance deteriorates

Engineering Contradiction:

Improvedeployment costVSAvoidservice latency

Core Design Contradiction:

Loss of energyVSLoss of time

Solution Approach 1:

The system applies local quality by differentiating deployment strategies based on service characteristics. Latency-sensitive services are deployed to nodes closer to devices with appropriate hardware resources, while latency-insensitive services can be deployed to more cost-effective remote nodes. This localized optimization ensures that each service type receives appropriate deployment treatment

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The deployment system is dynamic, allowing container reassignment between nodes based on changing conditions. The orchestration platform can relocate containers to optimize the balance between latency performance and deployment cost as network conditions, device locations, and service requirements evolve over time

Inventive Principle:

Principle #15Dynamics

3Productivity

If automated container selection is implemented, then deployment efficiency is improved, but system complexity increases

Engineering Contradiction:

Improvedeployment efficiencyVSAvoidorchestration system complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The orchestration platform is designed as a universal system that handles multiple container types, service requirements, and node configurations through a single automated framework. This multi-functional approach consolidates what would otherwise require multiple separate systems, managing complexity while maintaining high deployment efficiency across diverse scenarios

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system manages complexity by focusing on key parameters such as latency sensitivity, container attributes, and node characteristics. The automated selection process transforms complex deployment decisions into parameter-based matching, where the orchestration platform evaluates and compares containers and nodes based on defined parameters, simplifying the decision-making process

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20240086253A1Systems and methods for intent-based orchestration of a virtualized environment

Publication Date: 2024.03.14 VERIZON PATENT & LICENSING INC

AI summary

A system may select a set of containers to implement a requested service; identify parameters of the set of containers, and maintain information including parameters associated with a plurality of nodes of the virtualized environment. The parameters for one or more of the plurality of nodes may include information associating the one or more nodes with respective elements of the network. The system may compare the parameters of the one or more containers to the parameters of the one or more nodes, and select a set of nodes of the plurality of nodes on which to deploy the selected set of containers. The selecting may include selecting, for each container of the set of containers, a respective node of the set of nodes on which to deploy the each container. The system may deploy the selected set of containers to the set of nodes to implement the requested service.