LLN PAN Enrollment Priority Control for Load Balancing
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Solution Overview
Problem
Existing methods for load balancing in Low-power and Lossy Networks (LLNs) fail to prevent oscillating saturations between wireless data networks without algebra-based compute solutions, which are computationally complex and inefficient.
Innovation Solution
A centralized controller device determines network loads and sends enrollment priorities to root network devices to manage migration between PANs, ensuring balanced load distribution by adjusting enrollment priorities in a coordinated manner.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing load balancing methods are used in LLNs, then load distribution is attempted, but oscillating saturations occur between wireless data networks
Solution Approach 1:
The patent implements a feedback mechanism where the centralized controller continuously monitors network load metrics from multiple PANs and dynamically adjusts enrollment priorities based on observed saturation levels. This closed-loop control prevents oscillating saturations by responding to actual network conditions rather than using fixed or reactive load balancing rules.
Solution Approach 2:
The centralized controller acts as an intermediary between multiple PANs, coordinating enrollment priorities across the entire network. This mediator prevents direct oscillations between PANs by centralizing the decision-making process and smoothing load transitions through controlled enrollment priority adjustments.
2Reliability
If algebra-based compute solutions are used for load balancing, then load distribution is achieved, but computational complexity and inefficiency increase
Solution Approach 1:
The patent extracts the complex computational load balancing calculations from the constrained LLN devices and relocates them to a centralized controller with sufficient computational resources. This extraction allows simple enrollment priority adjustments at the network edge while maintaining complex optimization centrally, resolving the contradiction between effectiveness and device complexity.
Solution Approach 2:
The centralized controller serves as an intermediary that performs complex algebra-based computations remotely, allowing constrained LLN devices to benefit from optimal load balancing without bearing the computational burden. This mediator approach achieves load balancing effectiveness while keeping device complexity low.
3Ease of manufacture
If nodes are not evenly distributed to different PANs, then network setup is simpler, but packet loss due to congestion increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and distributing enrollment priorities that guide nodes to join PANs in a load-balanced manner. This preventive approach ensures even node distribution from the outset, avoiding congestion and packet loss before they occur, while maintaining simple network operation through automated enrollment guidance.
Data Source
AI summary
In one embodiment, a method comprises: first determining, by a controller, a target load for each of at least first and second wireless data networks rooted by respective first and second root network devices; second determining, by the controller, that at least a prescribed minimum number of network devices attached within the first wireless data network need to migrate from the first wireless data network to the second wireless data network based on the respective target loads; and causing, by the controller, the prescribed minimum number of network devices to migrate from the first wireless data network to the second wireless data network, based on the controller sending to the first and second root network devices enrollment priorities to be advertised by the first and second root network devices, respectively.