IoT with MQTT & Akka Actor Systems v.2
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README.md

IoT & Akka Actor Systems v.2

This is a Scala-based application using Akka Actor systems and MQTT Pub-Sub messaging on a scalable fault-tolerant distributed platform to simulate individual IoT (Internet of Things) devices, each maintaining its own internal state and setting. It's an expanded version (hence v.2) of another Akka-IoT application. For an overview of the application, please visit Genuine Blog.

Running on a single JVM

To run the application on a single JVM with the default 20 devices, simply git-clone the repo to a local disk, open up a command line terminal, run the following command and observe the console output:

  1. Start a Redis server accessible to the master cluster to serve as the persistence journal:
$ redis-server [/path/to/conf]
  1. Launch the master cluster with 2 seed nodes, IoT actor system and Worker actor system:
$ {project-root}/bin/sbt "runMain akkaiot.Main"

Running on separate JVMs

To run the application on separate JVMs with a given number of devices, please proceed as follows:

git-clone the repo to a local disk, open up separate command line terminals and launch the different components on separate terminals:

  1. Start the Redis server which serves as the persistence journal accessible to the master cluster:
$ redis-server [/path/to/conf]
  1. Launch the master cluster seed node with persistence journal:
$ {project-root}/bin/sbt "runMain akkaiot.Main 2551"
  1. Launch additional master cluster seed node:
$ {project-root}/bin/sbt "runMain akkaiot.Main 2552"
  1. Launch the IoT node:
$ {project-root}/bin/sbt "runMain akkaiot.Main 3001 [numOfDevices]"
  1. Launch a Worker node:
$ {project-root}/bin/sbt "runMain akkaiot.Main 0"
  1. Launch additional Worker node:
$ {project-root}/bin/sbt "runMain akkaiot.Main 0"

The optional numOfDevices parameter, if not provided, defaults to 20.

To scale up work processing service for the IoT devices, start up additional worker (and/or master) nodes.

To test fault tolerance in the master cluster, stop a master node and observe how the cluster fails over to the next oldest master node.