SDN Rule Engine for Dynamic Path Computation
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Solution Overview
Problem
Current Software Defined Networking (SDN) systems lack dynamic feedback mechanisms to adapt to changing network conditions, such as external factors like weather and infrastructure changes, leading to inefficient resource utilization and potential service disruptions.
Innovation Solution
Implementing a rule engine that analyzes Operations, Administration, and Maintenance (OAM) data, including alarms and performance monitoring data, to dynamically adjust path computation in SDN networks, avoiding stressed nodes and links, and incorporating external data to assess risks from events like construction and weather, thereby optimizing network resource allocation and service provisioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a static view of the network is used with conventional path computation algorithms, then the system is simpler to implement, but the network cannot dynamically adapt to changing conditions leading to service disruptions
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors network conditions (alarms, performance data, events) and uses this information to dynamically adjust path computation. The feedback loop enables the system to adapt to changing network states by incorporating real-time data into routing decisions, resolving the contradiction between static simplicity and dynamic adaptability
Solution Approach 2:
The system performs preliminary actions by proactively identifying at-risk network elements before failures occur. By analyzing historical and real-time data to predict potential issues, the system can pre-compute alternative paths and prepare mitigation strategies, enabling dynamic adaptation without reacting only after problems arise
2Extent of automation
If historical network data is collected and analyzed, then better diagnostic capabilities are achieved, but the system cannot automatically respond to issues requiring manual intervention
Solution Approach 1:
The system implements self-service by automatically responding to detected network issues without requiring manual intervention. When the system identifies problems through data analysis, it autonomously executes predefined responses such as computing alternative paths, adjusting routing policies, and mitigating service disruptions, thereby achieving high automation while fully utilizing collected data
3Reliability
If path computation focuses only on constraint optimization, then routing efficiency is improved, but external factors like weather and construction are not considered in risk assessment
Solution Approach 1:
The patent merges multiple data sources and consideration factors into a unified path computation framework. It combines traditional constraint optimization with external factors (weather, construction, events) and historical performance data into a single comprehensive system that simultaneously evaluates multiple criteria, achieving improved reliability without proportionally increasing complexity through integration
4Productivity
If services are provisioned on high-utilization network elements, then resource efficiency is improved, but the network becomes more vulnerable to single points of failure
Solution Approach 1:
The system dynamically changes the parameters used in path computation based on real-time network conditions. When network elements show signs of stress or failure risk, the system adjusts weighting parameters and constraints to avoid these elements, even if they have available capacity. This dynamic parameter adjustment allows the system to balance resource utilization with reliability by adapting to changing network states
Data Source
AI summary
A method and server to detect, diagnose, and mitigate issues in a network include receiving Operations, Administration, and Maintenance (OAM) data related to the network, the OAM data related to current operation of the network; instantiating a rule engine to evaluate one or more rules based on any one of the OAM data, an event, policy, and an anomaly; and performing one or more actions based on the evaluating the one or more rules. A Software Defined Networking (SDN) controller is also described.