Mesh Access Point Reboot Tracking to Reduce Node Scanning
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Solution Overview
Problem
In mesh networks, frequent reboots of access points lead to network connectivity loss and increased power consumption for battery-powered devices, as they need to frequently scan for new access points, depleting battery resources and reducing operational life.
Innovation Solution
Access points maintain and update a reboot time metric indicating the average time between reboots, which nodes use to select a parent node with lower reboot frequency, reducing the need for frequent scanning and power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If access points frequently reboot, then network maintenance and updates can be performed, but network connectivity loss increases and battery-powered devices consume more power
Solution Approach 1:
The access point performs preliminary actions by maintaining a reboot time metric that predicts future reboot behavior. Nodes use this metric to proactively select parent nodes with lower reboot frequencies, preventing connectivity issues before they occur rather than reacting after reboots happen.
Solution Approach 2:
The system implements feedback by having access points transmit their reboot time metrics to nodes, which then use this information to make informed parent node selection decisions. This closed-loop feedback mechanism allows the network to adapt its topology based on actual reboot patterns observed in the field.
2Adaptability or versatility
If nodes frequently scan for new access points, then they can adapt to reboots, but power consumption increases
Solution Approach 1:
Nodes perform preliminary action by using the reboot time metric to predict whether an access point is likely to reboot soon. This allows nodes to make informed decisions about whether to actively monitor or passively accept connectivity, avoiding unnecessary scanning and power consumption when reboots are unlikely.
Solution Approach 2:
The system applies dynamics by adjusting node behavior based on the reboot time metric. When the metric indicates high reboot probability, nodes become more active in monitoring and switching. When the metric indicates low reboot probability, nodes enter a more passive state, reducing energy consumption while maintaining adaptability when needed.
Data Source
AI summary
Various embodiments set forth a method comprising detecting, by an access point, that the access point has obtained network connectivity after a first reboot event; in response to detecting that the access point has obtained network connectivity after the first reboot event: determining, by the access point, a first amount of time between a first reboot time associated with the first reboot event and a second reboot time associated with a second reboot event that occurred prior to the first reboot event; updating, by the access point, a reboot time metric associated with the access point based on the first amount of time; and transmitting, by the access point, the reboot time metric to one or more nodes of a mesh network.