Order-Deploy Algorithm Mitigates RF Outages in Wireless Networks
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Solution Overview
Problem
In enterprise WLAN deployments, high-risk configuration updates, such as channel changes or radio reinitializations, often lead to significant AP downtime and coverage holes due to RF network outages, causing disruptions in client connectivity.
Innovation Solution
The implementation of an order-deploy algorithm that identifies and flags high-risk AP configurations, determines a candidate deployment order, groups APs into batches, and performs a batch refinement process to ensure that neighbor APs are not deployed simultaneously, introducing configurable delays between batches to mitigate the impact of configuration updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If configuration updates are deployed to multiple APs simultaneously, then deployment efficiency is improved, but RF outages and coverage holes increase
Solution Approach 1:
The patent segments the configuration deployment process into batches of APs. Instead of deploying to all APs simultaneously, the system divides them into multiple deployment batches and executes deployments sequentially. This segmentation allows the network to maintain coverage continuity by ensuring that not all APs go down at once, while still achieving efficient bulk deployment across the network.
Solution Approach 2:
The patent implements preliminary actions by identifying high-risk APs before deployment and creating a refined deployment order that prioritizes certain APs over others. The system performs preliminary analysis of AP configurations, neighbor relationships, and potential outage impacts to establish an optimized deployment sequence that minimizes coverage holes before the actual deployment begins.
2Reliability
If configuration updates are deployed sequentially to individual APs, then RF outages are minimized, but deployment time increases
Solution Approach 1:
The patent segments the AP population into deployment batches that can be deployed in parallel groups rather than one at a time. This batched segmentation allows multiple APs to be updated simultaneously within each batch while maintaining enough spacing between batches to prevent network-wide outages, thus reducing total deployment time compared to strictly sequential deployment.
Solution Approach 2:
The patent dynamically adjusts deployment parameters such as batch size, delay intervals between batches, and deployment ordering based on network conditions and AP characteristics. By changing these parameters optimally, the system achieves a balance between deployment speed and outage minimization, avoiding both the inefficiency of slow sequential deployment and the problems of simultaneous deployment.
3Ease of operation
If high-risk configuration updates are deployed without refinement, then deployment simplicity is maintained, but AP downtime and coverage holes increase
Solution Approach 1:
The patent performs preliminary refinement of the deployment plan by analyzing AP configurations, identifying high-risk updates, and determining optimal deployment ordering before actual deployment begins. This preliminary analysis phase automates the complex work of planning, making the subsequent execution simpler and more reliable without requiring manual intervention during the deployment itself.
Solution Approach 2:
The patent introduces an intermediary refinement process that acts as a mediator between the simple deployment command and the complex network state. This intermediary layer automatically analyzes dependencies, identifies potential conflicts, and generates an optimized deployment plan, shielding operators from complexity while ensuring reliable deployment outcomes.
Data Source
AI summary
A set of AP radios to which configurations are to be deployed is identified. A candidate deployment order for deploying configurations to the set of AP radios is determined by an order-deploy algorithm. The algorithm seeks to spread out configuration deployments to AP radios both spatially and temporally such that APs that are located close to one another in the network receive their configuration updates as part of different deployment batches with delay periods introduced between consecutive batch deployments. The algorithm orders the set of APs by iterating through a network factor hierarchy to place APs that share certain network factors such as the same band or channel close to one another in the candidate deployment order and place APs that share certain other network factors (e.g., same switch, RF domain, and/or RF partition) far from one another in the order.