Load Adaptive Master Node Selection in Extended Bridge Networks
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Solution Overview
Problem
In extended bridge networks, the master control node is often overloaded with management tasks, leading to suboptimal traffic forwarding and resource wastage due to static traffic distribution methods, which can result in service quality degradation and inefficient network resource utilization.
Innovation Solution
Implement an intelligent, load-adaptive, and self-optimizing system for selecting the master control node based on real-time configuration and runtime parameters, ensuring that the node with the most resources and lowest traffic load is elected to manage and distribute traffic efficiently across the network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a single master CB node is designated for configuration management of all PE nodes, then centralized control and management is achieved, but the master CB node becomes heavily loaded with management tasks leading to suboptimal traffic forwarding
Solution Approach 1:
The patent implements dynamic master node selection where any CB node can become the master based on real-time load conditions. The system continuously monitors management task loads and dynamically elects the most suitable CB node as master, transforming the static single-master architecture into a dynamic multi-master capable system that adapts to changing network conditions.
Solution Approach 2:
The system changes the operational parameters of CB nodes by introducing load threshold parameters and management task count parameters. When a CB node's management task load exceeds a predefined threshold, it can relinquish master status, allowing parameter-based adaptation of the master node selection to maintain optimal traffic forwarding performance.
2Reliability
If the master CB node handles all configuration management tasks for PE nodes, then single point of management is ensured, but resource wastage occurs due to static traffic distribution methods
Solution Approach 1:
The patent segments the configuration management responsibilities by allowing multiple CB nodes to potentially serve as masters depending on load conditions. Instead of one CB node handling all management tasks indefinitely, the management function is segmented and redistributed to the CB node currently best positioned to handle it, reducing resource wastage through load-based segmentation of management duties.
Solution Approach 2:
CB nodes autonomously monitor their own management task loads and can self-determine when to relinquish or assume master status based on predefined thresholds. This self-service mechanism allows the network to automatically rebalance management loads without external intervention, preventing resource wastage by enabling CB nodes to self-adjust their management responsibilities.
3Device complexity
If static traffic distribution methods are used, then simple control is maintained, but service quality degrades due to overloaded master node
Solution Approach 1:
The system implements feedback mechanisms where CB nodes continuously monitor management task loads and traffic conditions. This feedback information is used to dynamically adjust master node selection, creating a closed-loop control system that maintains service quality by responding to actual network conditions while preserving relatively simple control through predefined threshold-based decision rules.
Data Source
AI summary
Techniques for intelligent, load adaptive, and self optimizing master node selection in an extended bridge are provided. According to one embodiment, a controlling bridge (CB) node that is part of a plurality of CB nodes in the extended bridge can determine a set of local configuration parameters and a set of local runtime parameters. The CB node can further broadcast the set of local configuration parameters and the set of local runtime parameters to other CB nodes in the plurality of CB nodes. The CB node can also receive a set of configuration parameters and a set of runtime parameters from each of the other CB nodes in the plurality of CB nodes. The CB node can then determine a particular CB node in the plurality of CB nodes to be a master CB node of the extended bridge based on the set of local configuration parameters, the set of local runtime parameters, the received sets of configuration parameters, and the received sets of runtime parameters.