Adaptive Failover Threshold for Dual-Mode Network Node
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Solution Overview
Problem
Dual-mode Customer Premises Equipment (CPE) systems face challenges in setting optimal failover thresholds for switching between DSL and cellular networks, as current methods either fail to trigger failover when faults are severe or trigger it excessively, leading to inefficient use of backup networks.
Innovation Solution
A method where a network node monitors fault-indicative events, adjusts failover and failback thresholds dynamically based on the rate of these events per unit time, allowing for a more reactive and adaptive switching strategy between DSL and cellular networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If a high failover threshold is set, then the backup network is used less frequently reducing cost, but the failover may not be triggered despite severe faults affecting user experience
Solution Approach 1:
The patent applies dynamics by making the failover threshold adaptive rather than static. The system dynamically adjusts the threshold based on the observed rate of fault-indicative events. When the fault rate exceeds a predetermined threshold, the system automatically lowers the failover threshold, enabling more responsive failover during periods of poor connection quality while maintaining higher thresholds during normal operation to avoid unnecessary backup network usage.
Solution Approach 2:
The patent implements parameter changes by modifying the failover threshold parameter based on the rate of fault-indicative events. The system monitors the frequency of faults and adjusts the threshold parameter accordingly - lowering it when fault rates are high and maintaining or raising it when fault rates are low, thereby optimizing both cost efficiency and reliability under different operating conditions.
2Reliability
If a low failover threshold is set, then failover is triggered frequently improving user experience during faults, but the backup network is overused increasing cost and reducing bandwidth availability
Solution Approach 1:
The system dynamically adjusts the failover threshold based on real-time monitoring of fault rates. Instead of using a permanently low threshold that would cause excessive backup network usage, the system only lowers the threshold temporarily when the rate of fault-indicative events exceeds a predetermined rate, thereby triggering failover only when genuinely needed while avoiding unnecessary backup network consumption during normal operation.
Solution Approach 2:
The failover threshold parameter is changed adaptively based on the observed fault rate. The system monitors the frequency of fault-indicative events and modifies the threshold parameter in response - decreasing it when fault rates are high to improve responsiveness, and maintaining or increasing it when fault rates are low to prevent overuse of the backup network.
3Ease of operation
If a fixed threshold is used, then the system is simple to operate, but it cannot adapt to varying fault rates affecting both user experience and network resource optimization
Solution Approach 1:
The system implements self-service by automatically monitoring the rate of fault-indicative events and adjusting the failover threshold without requiring manual intervention. The network node itself performs the adaptation by comparing the observed fault rate against a predetermined threshold and automatically modifying the failover trigger condition, thereby maintaining ease of operation while achieving adaptability to varying fault rates.
Solution Approach 2:
The system uses feedback by continuously monitoring the rate of fault-indicative events and using this information to adjust the failover threshold. The observed fault rate feeds back into the decision-making process, allowing the system to adaptively optimize the threshold based on actual network conditions rather than relying on fixed predetermined values.
Data Source
AI summary
This disclosure provides a network node, and a method of operating the network node, having one or more communications interfaces connectable to a first communications network and to a second communications network, the method including the network node accessing a service using the first communications network; analyzing data relating to the first communications network to identify a plurality of fault-indicative events; determining a rate of the plurality of fault-indicative events per unit time; and the network node accessing the service using the second communications network in response to a first trigger, wherein the first trigger is based on the rate of the plurality of fault-indicative events per unit time.