The performance of a Wi-Fi network is key to ensuring smooth and uninterrupted connectivity, especially in scenarios with a high density of simultaneous connection requests.
Optimizing a network is not just about installing more access points (APs) or increasing bandwidth, but about analyzing the right metrics to detect problems and improvement opportunities. Connectivity analytics allows real-time evaluation of network health and the implementation of strategies to maximize its efficiency.
This article explains the essential metrics that should be monitored to ensure optimal network performance, highlighting how Galgus is able to achieve this with the help of artificial intelligence.
Overall network health: An overview
The first step in optimising a network is to understand its overall health. The Galgus Network Health platform provides a global view of the network through a health index with values between 0 and 100, allowing managers and owners to quickly detect any problems.
This index is calculated from five key metrics:
- Coverage: evaluates the signal distribution in the area covered by the APs.
- Capacity: measures the efficient use of network resources based on the number of connected devices.
- Airtime: represents the usage time of each wireless channel, which is key to avoiding congestion.
- Latency: measures the response time between the data request and reception, influencing the quality of the user experience.
- Hardware: analyzes the status of the APs, detecting possible equipment failures or overloads.
These parameters allow administrators to determine whether they need to take immediate action or whether the network is operating within optimal standards.
Essential KPIs for network optimization
1. Connected users and available memory
Monitoring the number of connected devices is essential to assess network load. Additionally, the memory available on each AP is a critical factor to avoid drops or interruptions.
2. CPU load and latency
APs are constantly processing data and connections, so CPU overload can lead to poor performance. Latency must also be kept low to ensure network fluidity.
3. Channel occupancy (2.4 GHz and 5 GHz)
Radio spectrum saturation is one of the main causes of performance degradation. Analyzing channel occupancy in both bands allows network configuration to be adjusted to minimize interference.
4. Modulation and Coding (MCS)
The Modulation and Coding Scheme (MCS) indicates the data transmission speed between devices and the network. A low MCS suggests interference, poor signal quality, or too many devices connected on the same channel.
5. Signal to Noise Ratio (SNR)
The signal-to-noise ratio is a key indicator of connection quality. A low SNR may mean that devices are too far away from an AP or that there are sources of interference in the environment.
6. Packet loss
Packet loss rate directly impacts user experience, causing interruptions in video calls, online gaming, or live streaming. Identifying the causes of this loss is key to correcting configuration issues or interference.
7. Uptime
The length of time an AP is up and running without interruptions is another key KPI. Unexpected reboots can indicate hardware issues or power failures.
Advanced diagnostics and anomaly detection thanks to connectivity analytics
One of the biggest benefits of connectivity analytics is early detection of problems. Through advanced tools such as:
Trend prediction with artificial intelligence
Galgus implements a Bayesian inference model that analyzes network data and predicts network behavior for the next seven days. This allows administrators to anticipate potential incidents and optimize resources before they affect connectivity.
Correlating data to identify patterns
Analyzing multiple metrics together helps uncover relationships between factors that affect performance. Some examples include:
- Number of devices and RAM usage.
- CPU vs. RAM (to identify if an AP is overloaded).
- MCS vs. SNR (to detect if the transmission speed is adequate to the signal quality).
These analyses allow you to adjust your network settings to maximize efficiency.
Identifying problematic devices
Sometimes the problem is not with the network infrastructure, but with specific devices that are causing interference or consuming excessive resources. By analyzing each connected client in detail, it is possible to detect which devices are causing problems and act accordingly.
Optimizing the network based on data
The key to an efficient network is not just identifying problems, but acting on them. Some recommended actions include:
- AP Reassignment: If areas with low coverage or high interference are detected, new APs can be installed or existing ones reconfigured.
- Channel Optimization: Automatically change AP settings to avoid congestion on certain frequencies.
- Traffic Prioritization: Assign priority to certain types of traffic (such as video conferencing or VoIP) to ensure their stability.
- Automation and self-optimization: With solutions like those from Galgus, the network can be adjusted in real time without manual intervention, always ensuring the best performance.
Connectivity analytics is a fundamental pillar for any modern network infrastructure. Monitoring key KPIs such as latency, packet loss, SNR, and CPU load allows you to maintain a stable network and also anticipate problems before they impact user experience.
Thanks to technologies like Galgus, network monitoring and optimization have become more accessible and automated. With tools like Network Health and its AI-based technology, administrators can gain a complete view of their network’s health and improve its performance without the need for advanced technical knowledge.
Optimizing a network is no longer a matter of trial and error: with the right analytics, it is possible to ensure robust, stable and efficient connectivity at all times. Shall we shape it together? Contact us.
