Dynamic Network Configuration via Analytics-Driven Service Chaining
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Solution Overview
Problem
Operators face challenges in efficiently configuring network infrastructure to direct traffic through the right inline service paths based on service policies and requirements, especially when multiple service chains are involved, due to high throughput and packet inspection demands of services like DPI, Firewall, and NAT.
Innovation Solution
An analytics-driven dynamic network design and configuration method that uses a data analytics platform to generate a dynamic situation profile, determining a similarity index with a characteristic profile to trigger control signals for dynamic design changes in the network, allowing for real-time optimization of service function placement and chaining in virtualized infrastructure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple inline services (DPI, Firewall, NAT, IDP) are deployed to manage subscriber traffic with high throughput and packet inspection requirements, then service functionality and security are improved, but network configuration complexity and difficulty of directing traffic through the right service paths increase
Solution Approach 1:
The patent segments the network configuration management into multiple independent components: service chain templates define service functions, policies define routing rules, and the system dynamically assembles these segments based on traffic requirements. This allows complex service functionality to be achieved while keeping configuration manageable through modular decomposition.
Solution Approach 2:
The patent implements dynamic service chain configuration where the network automatically adapts service paths based on real-time policies, traffic characteristics, and service requirements. Instead of static manual configuration, the system dynamically selects and configures service chains, reducing configuration complexity while maintaining high adaptability to different service scenarios.
2Reliability
If service chains are configured to direct traffic through multiple inline services, then comprehensive service processing is improved, but convergence time to optimized service function placement increases
Solution Approach 1:
The patent pre-configures service chain templates with common service function combinations and policies before they are needed. When traffic requires service processing, the system rapidly selects from these pre-prepared templates rather than configuring service chains from scratch, significantly reducing convergence time while ensuring complete service processing through comprehensive template coverage.
Solution Approach 2:
The system implements feedback mechanisms that monitor service chain performance and traffic patterns, using this information to continuously optimize service function placement. This feedback loop enables the system to learn from operational data and improve convergence speed over time while maintaining reliable service processing through data-driven optimization decisions.
3Manufacturing precision
If operators manually configure network infrastructure to direct traffic through the right inline service paths, then configuration accuracy is improved, but operational efficiency and speed of deployment deteriorate
Solution Approach 1:
The patent implements self-service automation where the network system automatically configures service chains based on predefined policies and traffic characteristics, eliminating the need for manual operator configuration. The system autonomously selects appropriate service functions, determines optimal paths, and applies configurations, maintaining high accuracy through policy enforcement while dramatically improving operational efficiency through automation.
Solution Approach 2:
The system uses parameter-based policy definitions that automatically translate high-level service requirements into specific configuration parameters. By changing from manual parameter setting to automated parameter derivation based on policy rules and traffic analysis, the system maintains configuration accuracy while enabling rapid automated deployment across the network infrastructure.
Data Source
AI summary
A system and method for dynamically (re)configuring a service network based on profile information obtained from a Big Data Analytics platform. Received dynamic situation profiles relative to network states, subscriber states, etc. may be compared against corresponding characteristic situation profiles. If there is a similarity, a dynamic design change action may be effectuated for changing configuration of at least a part of the service network, e.g., a service chaining mechanism, operating to service user data flows of the subscribers.