Community networks are a vital alternative for connecting rural populations overlooked by traditional operators due to low profitability. However, unlike mobile networks with broad reach, community nodes have limited range, and their placement does not always guarantee optimal coverage since user distribution is often unpredictable.
Furthermore, network administrators struggle to improve the Quality of Experience (QoE) without precise, user-side Quality of Service (QoS) data. Existing tools like Fing, nPerf, or Speedtest often fall short because they lack automated scheduling, do not provide a real-world view of client-side traffic, or are proprietary and data-heavy.
Project Solution: MetricTect
This work introduces a native Android application designed to provide a comprehensive, user-centric view of network performance while remaining significantly more resource-efficient than existing solutions.
Key Monitoring Metrics
The tool captures and displays essential performance indicators directly from the user's device:
Latency: The time delay in data transmission.
Packet Loss: The percentage of data packets that fail to reach their destination.
Jitter: The variation in time delay between data packets.
Throughput: Real-time measurement of both Download (Downlink) and Upload (Uplink) speeds.
Advantages and Efficiency
The primary innovation of this tool lies in its ability to deliver accurate diagnostics while minimizing resource consumption:
Low Data Footprint: While standard speed tests can consume hundreds of megabytes, this tool uses an average of only 50.4 MB per test sequence.
Automated Measurements: Unlike tools that require manual triggers, this system allows for scheduled, background performance tracking.
Professional Utility: Beyond community networks, mobile operators can use the app to assess network availability in specific zones to build technical dossiers for infrastructure expansion.
Strategic Impact
By providing a "view from the ground," this tool enables network administrators to make data-driven adjustments to node placement and configuration. It transforms the management of community networks from a guessing game into a precise engineering task, ensuring that limited resources are deployed where they provide the most benefit to the end-user.