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  • Ubuntu 18.04
  • 8 vCPU
  • 16GB RAM
  • 160 GB Disk
  • Private Access (through the lab VPN)
    • Host Name: ealtedge.lfedge.iol.unh.edu
    • IPv4: 10.11.26.2
    • IPv6: 2606:4100:3880:3026::2
  • Public Access (specific ports only)
    • Host name: ealtedge.iol.unh.edu
    • IPv4: 132.177.125.234
    • IPv6: 2606:4100:3880:3026::2
    • Open Ports:
      • TCP/30091
      • TCP/30092
      • TCP/30093
      • TCP/30094
      • TCP/30095


Show Case details:

Overview:

Demo of LFEdge Cross projects(Akraino EALTEdge + EdgeGallery + eKuiper + Fledge) collaboration to deliver Edge computing platform with IOT stack.

Background:

EALTEdge (Enterprise applications on lightweight 5G telco edge) BP from Akraino, integrate various open source projects to build a MEC based edge computing platform.

EALTEdge BP along with its upstream project EdgeGallery, provide an IOT stack which leverages Fledge(for IOT protocol and data collection) and eKuiper(Data Filter). 


For using the EALTEdge Edge computing platform and  experience the profile based IOT solution, EALTEdge is deployed in LFEdge Lab.

User with right permission to lab, can connect and try it.


Details about use case:

In this demo, we use a sample simulated IOT device.

Data from Device is processed in pipeline in multiple stages like data collection from devices, data filtration and transformation then store in DB for offline scenarios. 

Now IOT applications can access this data. It support http exporter to get data by application. 

Application like grafana can get data from DB as well.


In this Demo, we are using simulated MQTT device which produce readings every seconds and processed data is visualise in Grafana to monitor the device.