Intelligent Service Composition System for Dynamic Network Configuration
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Solution Overview
Problem
Current cloud network technologies face challenges in efficiently creating and deploying personalized, adaptive, and dynamic network services that can scale and adapt to user needs, particularly for enterprise and small business customers, due to limitations in service granularity and human intervention requirements.
Innovation Solution
The system employs an intelligent service composition method using virtualized network function resources, expert systems, and machine learning to suggest and validate service compositions, enabling customers to create and deploy new network services through a graphical interface, leveraging NFV resources and standards like TOSCA for modeling and orchestration, and utilizing big data analytics for predictive and personalized services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If cloud networks utilize intelligent software systems and applications operating on general purpose commodity hardware, then capital and operating expenses decrease and network configuration requires less human intervention, but the ability to efficiently create and deploy personalized, adaptive, and dynamic network services is limited
Solution Approach 1:
The patent segments network services into modular network service modules that can be independently selected, configured, and deployed. This segmentation enables customers to compose personalized services by selecting specific modules (e.g., firewall, load balancer, web server) from a catalog, thereby achieving adaptability without requiring extensive human intervention in the overall service creation process.
Solution Approach 2:
The patent introduces an intermediary service composition system that acts as a mediator between customer requirements and network service deployment. This intermediary automatically composes personalized network services by selecting and configuring appropriate network service modules based on customer specifications, thus enabling service personalization while maintaining low human intervention levels.
2Adaptability or versatility
If network services are created with fine-grained functionality exposure, then service adaptability and customization improve, but service complexity and difficulty of composition increase
Solution Approach 1:
The patent divides complex network services into fine-grained, independently deployable network service modules. Each module encapsulates a specific function (e.g., authentication, routing, monitoring), allowing customers to select and compose only the modules they need. This segmentation reduces composition complexity by providing clear, modular building blocks with well-defined interfaces.
Solution Approach 2:
The patent creates a universal service composition framework that can handle diverse network service modules through standardized interfaces and a common deployment mechanism. This universal approach allows the same composition system to manage different service types (web services, microservices, legacy services) without increasing complexity, as the framework provides consistent abstractions for service selection, configuration, and deployment.
3Productivity
If cloud networks aim to scale and monetize intelligent services, then business opportunities increase, but the requirement for efficient service creation and deployment mechanisms becomes more critical
Solution Approach 1:
The patent pre-configures network service modules with standardized interfaces, metadata, and deployment templates before they are needed for service composition. This preliminary preparation allows the service composition system to rapidly assemble personalized services without complex real-time configuration, thereby enabling fast service creation and deployment that supports business scaling while keeping the deployment mechanism relatively simple.
Solution Approach 2:
The patent enables customers to autonomously compose and deploy their own network services through self-service interfaces. Customers can select from a catalog of network service modules, configure parameters, and deploy services without requiring complex manual intervention or deep technical expertise. This self-service approach accelerates service creation productivity while the underlying system handles the complexity of service composition and deployment automatically.
Data Source
AI summary
A cloud services composition system allows customers to interactively create service constructs from network function virtualization resources. The network function virtualization primitives are modeled using a standard modeling language. An expert system suggests network function virtualization resources for use in the service construct, based on an expert system learning algorithm. The customer uses a graphical user interface to interconnect the resources and create the service construct. The process may involve collaboration with the network provider. The resulting construct is validated for use in a communications network.