documenation for metaserver

Documentation for using metaserver will allow users to run examples with a local broker.
This decreases the chances of any job ID collisions.

Modifications to the config.json for the mnist example were made in order to make it easier to switch to a local broker.
The readme does indicate how to do this for other examples now.

docs/08-flame-sdk.md

@@ -20,9 +20,44 @@ make install
 ## Quickstart
 
 ### Configuring Brokers
-As the flame system uses MQTT brokers to exchange messages during federated learning, to run the python library locally, you could either 1) install a local MQTT broker 2) use a public MQTT broker. Here we'll illustrate the second option.
+Since the flame system uses MQTT brokers to exchange messages during federated learning, to run the python library locally, you could either 1) install a local MQTT broker 2) use a public MQTT broker.
 
-Go to any examples that you wish to run locally in `examples` directory, change the `host` from `"flame-mosquitto"` to `broker.hivemq.com` in the `config.json` files of both the trainer and aggregator.
+Your choice should be specified in the section of the config file shown below.
+
+```json
+    "backend": "p2p",
+    "brokers": [
+        {
+            "host": "broker.hivemq.com",
+            "sort": "mqtt"
+        },
+	{
+	    "host": "localhost:10104",
+	    "sort": "p2p"
+	}
+    ]
+```
+
+If you wish to pursue the second option, you may go to any examples that you wish to run locally in `examples` directory and change the `host` from `"flame-mosquitto"` to `broker.hivemq.com` in the `config.json` files of both the trainer and aggregator.
+Make sure that `backend` matches the `sort` of one of the brokers (for the mnist example, we already include `mqtt` and `p2p`).
+Then, proceed to the next section to run the example.
+However, this is not the best option since there may be job ID collisions with other users.
+In order to avoid this, follow the first option's instructions below.
+
+To start a local broker, go to the top `/flame` directory and run `make install`
+After this, you can use `cd ~` to go to the HOME directory.
+Now, to start metaserver, run `sudo ./.flame/bin/metaserver`.
+
+After changing the two config files in `mnist/trainer` and `mnist/aggregator` so that `backend` is set to `p2p`, continue to the next section.
+
+For future reference, you may have to add this to the list of brokers in the config file in order to use `metaserver`.
+
+```json
+	{
+	    "host": "localhost:10104",
+	    "sort": "p2p"
+	}
+```
 
 ### Running an Example
 
@@ -31,6 +66,7 @@ In order to run this example, you will need to open two terminals.
 In the first terminal, run the following command:
 
 ```bash
+conda activate flame
 cd examples/mnist/trainer
 
 python keras/main.py config.json

lib/python/flame/examples/mnist/aggregator/config.json

@@ -1,11 +1,15 @@
 {
     "taskid": "49d06b7526964db86cf37c70e8e0cdb6bd7aa742",
-    "backend": "mqtt",
+    "backend": "p2p",
     "brokers": [
         {
             "host": "broker.hivemq.com",
             "sort": "mqtt"
-        }
+        },
+	{
+	    "host": "localhost:10104",
+	    "sort": "p2p"
+	}
     ],
     "channels": [
         {

lib/python/flame/examples/mnist/trainer/config.json

@@ -1,11 +1,15 @@
 {
     "taskid": "505f9fc483cf4df68a2409257b5fad7d3c580370",
-    "backend": "mqtt",
+    "backend": "p2p",
     "brokers": [
         {
             "host": "broker.hivemq.com",
             "sort": "mqtt"
-        }
+        },
+	{
+	    "host": "localhost:10104",
+	    "sort": "p2p"
+	}
     ],
     "channels": [
         {