This page describes the key components and the measurement workflow of the WiFiMon system.
A mobile user is any user's device connected to the WiFi network. WiFiMon can be deployed in any WiFi network, but is optimized to be used in the Eduroam environment, as through the analysis of the Eduroam logs very detailed performance assessments can be obtained. If the Eduroam is used, the mobile user will be authenticated at the home organisation (IdP) and authorized at the end-user's location (SP) on an IEEE 802.1X based WiFi network.
WiFiMon admin is the network administrator managing the WiFi network and the WiFiMon system. Using the WiFiMon UI, he/she can perform queries to the Elastic ELK Cluster and get the performance of the wireless network.
WiFiMon uses ELK cluster for measurement data processing and visualization. Elasticsearch, a full-text, distributed NoSQL search engine. Elasticsearch uses documents rather than schema or tables (used in SQL databases), thus allowing leveraging and accessing data at very high speeds and making it appropriate for WiFiMon.
Exported Raw Data after filtered at Logstash, and the results of correlating them with the Collected Raw Data processed at WiFiMon Agent, are stored in the cluster. Part of Elastic ELK is also the Kibana platform (accessible from the browser) which provides cluster management and powers the WiFiMon UI. Another component of Elastic Stack is the Filebeat, which is installed as an agent in the severs holding the Exported Raw Data.
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WiFiMon respects the privacy of data. All the traffic in WiFiMon is encrypted with SSL/TLS certificates. Furthermore, sensitive data such as mobile users IP or MAC address is hash-ed before stored in the ELK Cluster. The correlation procedure mentioned at WiFiMon Agent above, is performed over the hash-ed data.
The WiFiMon test server includes configured templates from NetTest, Boomerang and SpeedTests (HTML5), which provide information about RTTs and ping (ICMP) network relevant data like bandwidth and latency (represented in Figure 2 as lines marked as 2.1, 2.2, and 2.5). A standard image size is downloaded for NetTest, and for Boomerang it can be customisable to a maximum of 5 MByte size. The location of the WTS and its topological distance from the monitored WiFi network has a major impact on the crowdsourced measurement accuracy and reliability. You can read more about this here.
The WiFiMon Software Probe takes the form of JavaScript integrated in often visited web pages. It includes the domain of the WiFiMon agent (e.g., wifimon.switch.ch), the listening agent port (8443) and the image location/path (e.g. https://eipa19.eipa.ttu.ee/wifimon/images/) as well as the cookie expiration time. The default value of this cookie is 1.5 min (currently) if it is not explicitly set in the WiFiMon test server.
The WiFiMon hardware probes are set up on small form factor devices - such as the Raspberry Pi. The HW probe may be viewed as an end user logged in to the eduroam wireless network, but monitoring continuously from a fixed point. It measures bandwidth, latency, the average values of bit rate, the signal level, the link quality and the transmission power. The WiFiMon team recommends to set up a WHP on Raspberry Pi’s v3 Model B+ or v4
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The Analysis Server includes the WiFiMon agent, Elasticsearch, Logstash and the WiFiMon UI with Kibana for customizing reports and their visualization. The WiFiMon agent checks the subnet (2.3, 2.4) of a monitored device visiting the website that includes the JavaScript lines and downloads available images from the WiFiMon Test server (2.5). Network performance metrics are calculated and streamed from the end user to the WiFiMon Analysis Server (2.6). Furthermore, the WAS correlates performance data with client IPs and AP-IDs (2.7/2.8).