Cloud Wi-Fi Controller Load Balancing by Local Conditions
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Solution Overview
Problem
Cloud-based monitoring services for WLANs face overwhelming processing power and bandwidth issues due to simultaneous connection requests from thousands of devices, leading to potential system failure.
Innovation Solution
Implementing a load balancing system that prioritizes and schedules connection requests based on local conditions such as network security, latency, and congestion, using a cloud-based Wi-Fi controller with a load balancer, connection priority module, and scheduling engine to manage connections across multiple Wi-Fi devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cloud-based monitoring services monitor all WLAN devices simultaneously, then monitoring coverage is improved, but processing power and network bandwidth are overwhelmed
Solution Approach 1:
The patent segments the monitoring task by dividing WLAN devices into different priority groups (high priority and low priority). The cloud-based controller monitors high priority devices continuously while using load balancing techniques to manage connections from low priority devices, thereby maintaining comprehensive monitoring coverage without overwhelming processing resources.
Solution Approach 2:
The patent changes the parameter of monitoring frequency and connection timing based on device priority. High priority devices receive continuous monitoring with guaranteed connection slots, while low priority devices are monitored periodically with scheduled connection slots during off-peak times. This parameter adjustment allows the system to maintain broad monitoring coverage while controlling processing power consumption.
2Loss of information
If all devices connect simultaneously for monitoring, then data collection completeness is improved, but network bandwidth is overwhelmed
Solution Approach 1:
The patent implements periodic action by scheduling connection slots for low priority devices at different times rather than simultaneously. The load balancer distributes connection requests across multiple time periods, ensuring that data from all devices is collected over time while preventing bandwidth overload at any single moment.
Solution Approach 2:
The patent applies preliminary action by pre-assigning connection slots and priority levels to devices before monitoring begins. The system proactively manages connection scheduling based on device priority, ensuring that high priority devices are monitored immediately while low priority devices are scheduled in advance during periods of lower network load, thus maintaining data completeness without overwhelming bandwidth.
3Device complexity
If connection requests are handled in FIFO order, then system simplicity is maintained, but response time for critical devices increases
Solution Approach 1:
The patent applies local quality by assigning different connection handling qualities to different devices based on their priority. High priority devices receive preferential treatment with immediate connection handling and guaranteed slots, while low priority devices are handled according to scheduled slots. This creates a differentiated connection handling approach that maintains system relatively simple while significantly improving response time for critical devices.
4Adaptability or versatility
If the system accepts all connection requests, then service availability is improved, but system stability deteriorates under overload
Solution Approach 1:
The patent implements dynamics by making the connection acceptance policy adaptive rather than static. The load balancer dynamically adjusts which connection requests are accepted based on current system load, device priority, and available capacity. High priority devices are always accepted, while low priority devices are accepted only when capacity permits. This dynamic approach maintains high service availability for critical devices while preserving system stability under overload conditions.
Data Source
AI summary
Load balancing for cloud-based monitoring of Wi-Fi devices on local access networks is based on local conditions. Requests for connection are received from Wi-Fi devices of the plurality of WLANs exceed a threshold. An indication of at least one condition for each of the WLANs is also received either with the connection request or separately. Example conditions include, without limitation, a number of local connections, network security breaches, guaranteed service levels, local latency or congestion, power outages or reboots, and the like. In response, at least one Wi-Fi device is prioritized and scheduled based on a corresponding at least one condition.