CCN-lite and NFN Tutorial

CCN-lite is a forth implementation: It is a lightweight and cross-compatible implementation of Content Centric Networking which "speaks" all three dialects. It is written in pure C and (optionally) runs in the Linux kernel space. Moreover, it contains an extension to CCN called Named-Function-Networking, which is also covered in this tutorial.

alt text

The first three scenarios of this tutorial demonstrate static content lookup in a CCN network. We let a client send interests into a network that consists of heterogeneous CCN implementations (our CCN-lite as well as the NDN testbed). The interest will be fulfilled by either a content store within the network or a producer of content. Note that although CCN-lite handles all packet formats, the client has to pick one format and can only access content that is encoded (and made routable) in that chosen format.

Scenario 4 and 5 issue function calls to the network for dynamic content creation in a NFN network. The chosen setup is shown below where the NFN-enhanced CCN-lite router manipulates computation names and distributes computations, for example to the external compute environment which is responsible to carry out the actual computations.

scenario function call

## Scenario 1: Simple content-lookup

content-lookup-simple

This scenario consists of a topology of two nodes A and B each running an instance of the CCN-lite relay. The cache of relay B is populated with some content and a forwarding rule is setup from node A to node B. Interests are send to node A.

0. Installing CCN-lite

Install CCN-lite by following the Unix readme.

1. Producing content

ccn-lite-mkC creates an (unsigned) content object in a specified wire format, subject to the maximum packet size of 4 KiB. ccn-lite-mkC currently supports five wire formats. We use ndn2013 in the following, ccnb, ccnx2015, cisco2015 and iot2014 are also available. ccn-lite-mkC converts input from stdin, so type something and press Enter after executing the following line:

$CCNL_HOME/bin/ccn-lite-mkC -s ndn2013 "/ndn/test/mycontent" > $CCNL_HOME/test/ndntlv/mycontent.ndntlv

2. Starting `ccn-lite-relay` for node `A`

ccn-lite-relay is a ccn network router (or forwarder). Type ccn-lite-relay -h to see all available options. We will use the following:

-v indicates the loglevel.
-u sets the relay to listen on UDP port 9998.
-x sets up a Unix socket, we will use this socket to send management commands to the relay.

$CCNL_HOME/bin/ccn-lite-relay -v trace -s ndn2013 -u 9998 -x /tmp/mgmt-relay-a.sock

3. Starting `ccn-lite-relay` for node `B`

We start the relay for B similarly to relay A but on a different port. Additional, with -d we add all content objects from a directory to the cache of the relay. Currently the relay expects all files to have the file extension .ndntlv, .ccnb, .ccntlv, .cistlv or .iottlv respectively. Open a new terminal window for relay B:

$CCNL_HOME/bin/ccn-lite-relay -v trace -s ndn2013 -u 9999 -x /tmp/mgmt-relay-b.sock \
  -d $CCNL_HOME/test/ndntlv

4. Add a forwarding rule

The two relays are not yet connected to each other. We want to add a forwarding rule from node A to node B which is a mapping of a prefix to an outgoing face. Thus, we first need to create the face on relay A followed by defining the forwarding rule for /ndn.

ccn-lite-ctrl provides a set of management commands to configure and maintain a relay. These management commands are based on a request-reply protocol using interest and content objects. Again, type ccn-lite-ctrl -h to see all available options.

Currently the ctrl tool is hardwired for the ccnb format (but the relay still handles packets in all other formats, too). To decode the reply of the ctrl tool we use ccn-lite-ccnb2xml.

Finally, because faces are identified by dynamically assigned numbers, we need to extract the face id from the reply of the create face command. When defining the forwarding rule we can then refer to this face id.

For creating the face at node A, open a new terminal window:

FACEID=`$CCNL_HOME/bin/ccn-lite-ctrl -x /tmp/mgmt-relay-a.sock newUDPface any 127.0.0.1 9999 \
  | $CCNL_HOME/bin/ccn-lite-ccnb2xml | grep FACEID | sed -e 's/^[^0-9]*\([0-9]\+\).*/\1/'`

For defining the namespace that should become reachable through this face, we have to configure a forwarding rule. We choose /ndn as namespace (prefix) pattern because our test content as well as all objects in ./test/ndntlv have a name starting with /ndn. Later, all interest which match with the longest prefix on this name will be forwarded to this face.

In other words: Relay A is technically connected to relay B through the UDP face, but logically, relay A does not yet have the necessary forwarding state to reach B. To create a forwarding rule (/ndn ---> B), we execute:

$CCNL_HOME/bin/ccn-lite-ctrl -x /tmp/mgmt-relay-a.sock prefixreg /ndn $FACEID ndn2013 \
  | $CCNL_HOME/bin/ccn-lite-ccnb2xml

You might want to verify a relay's configuration through the built-in HTTP server. Just point your browser to http://127.0.0.1:6363/.

This ends the configuration part and we are ready to use the two-node setup for experiments.

5. Send Interest for Name `/ndn/test/mycontent/` to `A`

The ccn-lite-peek utility encodes the specified name in a interest with the according suite and sends it to a socket. In this case we want ccn-lite-peek to send an interest to relay A. Relay A will receive the interest, forward it to node B which will in turn respond with our initially created content object to relay A. Relay A sends the content objects back to peek, which prints it to stdout. Here, we pipe the output to ccn-lite-pktdump which detects the encoded format (here ndn2013) and prints the wire format-encoded packet in a somehow readable format.

$CCNL_HOME/bin/ccn-lite-peek -s ndn2013 -u 127.0.0.1/9998 "/ndn/test/mycontent" \
  | $CCNL_HOME/bin/ccn-lite-pktdump

If you want to see only the content use the -f 2 output format option:

$CCNL_HOME/bin/ccn-lite-peek -s ndn2013 -u 127.0.0.1/9998 "/ndn/test/mycontent" \
  | $CCNL_HOME/bin/ccn-lite-pktdump -f 2

## Scenario 2: Content lookup from NDN Testbed

content-lookup-NDNTestbed

Similar to Scenario 1, but this time the network consists of the NDN Testbed instead of a set of CCN-lite relays.

Peek sends the interest directly to a node in the NDN Testbed. -w sets the timeout of peek to 10 seconds.

$CCNL_HOME/bin/ccn-lite-peek -s ndn2013 -u 192.43.193.111/6363 -w 10 "/ndn/edu/ucla/ping" \
  | $CCNL_HOME/bin/ccn-lite-pktdump

Note: /ndn/edu/ucla/ping dynamically creates a new content packet with a limited lifetime and random name extension. Due to the network level caching, repeating the above command might return a copy instead of triggering a new response. Try it out!

## Scenario 3: Connecting a CCN-lite relay to the NDN Testbed

content-lookup-CCNL-NDNTestbed

Scenario 3 combines Scenario 1 and 2 by connecting a (local) CCN-lite relay to the NDN Testbed and sending interests to it. The relay will forward the interests to the testbed.

1. Shutdown relay `B`

To properly shutdown a relay we can use ccn-lite-ctrl:

$CCNL_HOME/bin/ccn-lite-ctrl -x /tmp/mgmt-relay-b.sock debug halt | $CCNL_HOME/bin/ccn-lite-ccnb2xml

2. Remove face to `B`

To see the current configuration of the face, use:

$CCNL_HOME/bin/ccn-lite-ctrl -x /tmp/mgmt-relay-a.sock debug dump | $CCNL_HOME/bin/ccn-lite-ccnb2xml

Now we can destroy the face:

$CCNL_HOME/bin/ccn-lite-ctrl -x /tmp/mgmt-relay-a.sock destroyface $FACEID \
  | $CCNL_HOME/bin/ccn-lite-ccnb2xml

Check again if the face was actually removed.

3. Connecting node `A` directly to the NDN Testbed

Connect to the NDN testbed server of the University of Basel by creating a new UDP face to the NFD of Basel and then registering the prefix /ndn:

FACEID=`$CCNL_HOME/bin/ccn-lite-ctrl -x /tmp/mgmt-relay-a.sock newUDPface any 192.43.193.111 6363 \
  | $CCNL_HOME/bin/ccn-lite-ccnb2xml | grep FACEID | sed -e 's/^[^0-9]*\([0-9]\+\).*/\1/'`

$CCNL_HOME/bin/ccn-lite-ctrl -x /tmp/mgmt-relay-a.sock prefixreg /ndn $FACEID ndn2013 \
  | $CCNL_HOME/bin/ccn-lite-ccnb2xml

4. Send interest to `A`

Request data from the Testbed system of the UCLA. The interest will be transmitted over the Testbed server of the University of Basel to the Testbed system of the UCLA:

$CCNL_HOME/bin/ccn-lite-peek -s ndn2013 -u 127.0.0.1/9998 -w 10 "/ndn/edu/ucla" \
  | $CCNL_HOME/bin/ccn-lite-pktdump

## Scenario 4: simple Named Function Networking (NFN) demo

This scenario consists of a single NFN node A. In this demo, we will request the network to execute a simple built-in operation: add 1 2. A slightly more complex numeric expression is also shown.

1. Start a NFN-relay

To build a CCN-lite relay with NFN functionality, export the variable and rebuild the project:

cd $CCNL_HOME/src
export USE_NFN=1
make

or build it directly:

cd $CCNL_HOME/src
make ccn-nfn-relay

The ccn-nfn-relay can be started similar to the ccn-lite-relay:

$CCNL_HOME/bin/ccn-nfn-relay -v trace -u 9001 -x /tmp/mgmt-nfn-relay-a.sock

2. Send a NFN request

To send a NFN request, we can use the ccn-lite-simplenfn tool instead of ccn-lite-peek. This tool is very similar, but instead of fetching the content for a static name it returns the result of a dynamic NFN computation.

$CCNL_HOME/bin/ccn-lite-simplenfn -s ndn2013 -u 127.0.0.1/9001 "add 1 2" \
  | $CCNL_HOME/bin/ccn-lite-pktdump -f 3

Try out more complex expression evaluations, for example mult 23 (add 4 456).

## Scenario 5: Named Function Networking (NFN) demo

In this scenario we run a full implementation of the compute server: NFN-scala. A precompiled binary is available in the release downloads of release v0.1.0 of nfn-scala.

0. Prerequisites

In order to run the compute server, Java needs to be installed:

Ubuntu: sudo apt-get install openjdk-7-jre
OS X: Java 7 should already be available. If not, download and install directly from Oracle.

Additionally, the Java binary is also needed:

wget https://github.com/cn-uofbasel/nfn-scala/releases/download/v0.1.0/nfn.jar

1. Start a NFN-relay

Start a ccn-nfn-relay. We again add the content you produced in the first scenario.

$CCNL_HOME/bin/ccn-nfn-relay -v trace -u 9001 -x /tmp/mgmt-nfn-relay-a.sock -d $CCNL_HOME/test/ndntlv

2. Start the Scala compute server

Start the compute server with:

java -jar nfn.jar --mgmtsocket /tmp/mgmt-nfn-relay-a.sock \
  --ccnl-port 9001 --cs-port 9002 --debug --ccnl-already-running /node/nodeA

There is quite a lot going on when starting the compute server. Since the application has the name of the management socket, it is able to setup the required face: a UDP face from the relay on 9001 named /COMPUTE to the compute server on 9002. It then publishes some data by injecting it directly into the cache of CCN-lite. There are two documents named /node/nodeA/docs/tiny_md (single content object) and /node/nodeA/docs/tutorial_md (several chunks). There are also two named functions (or services) published: /node/nodeA/nfn_service_WordCount and /node/nodaA/nfn_service_Pandoc. We explain later how they can be used.

3. Send a NFN expression with a word count function call

We are going to invoke the WordCount service. This function takes a variable number of arguments of any type (string, integer, name, another call expression, ...) and returns an integer with the number of words:

call 3 /ndn/ch/unibas/nfn/nfn_service_WordCount /name/of/doc 'foo bar'

To invoke this service over NFN we send the following NFN expression to the relay A:

$CCNL_HOME/bin/ccn-lite-simplenfn -s ndn2013 -u 127.0.0.1/9001 -w 10 \
  "call 2 /node/nodeA/nfn_service_WordCount 'foo bar'" | $CCNL_HOME/bin/ccn-lite-pktdump

The result of this request should be 2.

You can also count the number of words of the document /ndn/test/mycontent that you produced in the first scenario:

$CCNL_HOME/bin/ccn-lite-simplenfn -s ndn2013 -u 127.0.0.1/9001 -w 10 \
  "call 2 /node/nodeA/nfn_service_WordCount /ndn/test/mycontent" | $CCNL_HOME/bin/ccn-lite-pktdump

Below are more examples that include counting tiny_md and combine WordCount with add:

$CCNL_HOME/bin/ccn-lite-simplenfn -s ndn2013 -u 127.0.0.1/9001 -w 10 \
  "call 2 /node/nodeA/nfn_service_WordCount /node/nodeA/docs/tiny_md" | $CCNL_HOME/bin/ccn-lite-pktdump

$CCNL_HOME/bin/ccn-lite-simplenfn -s ndn2013 -u 127.0.0.1/9001 -w 10 \
  "call 3 /node/nodeA/nfn_service_WordCount 'foo bar' /node/nodeA/docs/tiny_md" \
  | $CCNL_HOME/bin/ccn-lite-pktdump

$CCNL_HOME/bin/ccn-lite-simplenfn -s ndn2013 -u 127.0.0.1/9001 -w 10 \
  "add (call 2 /node/nodeA/nfn_service_WordCount 'foo bar') 40" | $CCNL_HOME/bin/ccn-lite-pktdump

4. Invoke the pandoc service

The example compute server also includes the Pandoc service. To make use of it, you have to install Pandoc itself:

Ubuntu: sudo apt-get install pandoc
OS X: brew install pandoc

This function reformats a document from one format (e.g. GitHub flavored Markdown) to another format (e.g. HTML) using Pandoc. It takes 3 parameters:

the document to transform,
the initial document format and
the target format.

In NFN, this could look like this:

call 4 /ndn/ch/unibas/nfn/nfn_service_Pandoc /doc/mydocument 'markdown' 'latex'

A list of all supported formats can be found on the Pandoc homepage.

To invoke the Pandoc sevice in our NFN network, type:

$CCNL_HOME/bin/ccn-lite-simplenfn -s ndn2013 -u 127.0.0.1/9001 -w 10 \
  "call 4 /node/nodeA/nfn_service_Pandoc /node/nodeA/docs/tiny_md 'markdown_github' 'html'" \
  | $CCNL_HOME/bin/ccn-lite-pktdump -f 2

Since tiny_md is only a small document, the generated HTML document will also fit into a single content object.

5. Invoke the pandoc service with a large document

So far, all results of NFN computations were small and fit into single content objects. Next we test what happens if the result is larger by transforming tutorial_md:

$CCNL_HOME/bin/ccn-lite-simplenfn -s ndn2013 -u 127.0.0.1/9001 -w 10 \
  "call 4 /node/nodeA/nfn_service_Pandoc /node/nodeA/docs/tutorial_md 'markdown_github' 'html'" \
  | $CCNL_HOME/bin/ccn-lite-pktdump -f 3

The result of this computation will not be a document, but a redirect name in the form of redirect:/node/nodeA/call 2 %2fndn%2fch.... When the result is too large to fit into one content object it has to be chunked. Since chunking of computation does not make too much sense, the result is a redirect address under which the chunked result was published by the compute server. Note that in the redirect name slashes / have to be escaped as %2f in order to avoid that the components are being split up.

To get the result, we have to use ccn-lite-fetch because ccn-lite-peek can only retrieve a single content object. ccn-lite-fetch returns a stream of data of the fetched content object chunks instead of wire format encoded packets. Therefore ccn-lite-pktdump is not necessary.

Call ccn-lite-fetch with the redirect name without the prefix redirect::

$CCNL_HOME/bin/ccn-lite-fetch -s ndn2013 -u 127.0.0.1/9001 \
  "/node/nodeA/call 4 %2fnode%2fnodeA%2fnfn_service_Pandoc %2fnode%2fnodeA%2fdocs%2ftutorial_md 'markdown_github' 'html'" \
  > tutorial.html

Open the tutorial.html file in the browser - it is the HTML page of this tutorial without pictures.

6. Function chaining

One last example shows the chaining of functions. For example, we can convert tutorial_md into HTML and count the number of words of the result:

$CCNL_HOME/bin/ccn-lite-simplenfn -s ndn2013 -u 127.0.0.1/9001 -w 10 \
  "call 2 /node/nodeA/nfn_service_WordCount (call 4 /node/nodeA/nfn_service_Pandoc \
  /node/nodeA/docs/tutorial_md 'markdown_github' 'html')" | $CCNL_HOME/bin/ccn-lite-pktdump

## Scenario 6: Creating and Publishing your own Named Function

So far, we have been using a binary of the compute server with predefined services. In this scenario, we are first going to look at the compute server start script as well as how an implemented service looks like. Then, we are going to implement a new service called revert.

0. Installing NFN-scala

Follow the installation instructions of nfn-scala.

1. Compile and start the Scala compute server

To run the Scala compute server from source, call sbt with runnables.production.ComputeServerStarter:

sbt 'runMain runnables.production.ComputeServerStarter --mgmtsocket /tmp/mgmt-nfn-relay-a.sock \
  --ccnl-port 9001 --cs-port 9002 --debug --ccnl-already-running /node/nodeA'

2. Explaining StandaloneComputeServer

Currently all running targets exist within the project itself in the runnables package. We will only discuss StandaloneComputeServer found in src/main/scala/runnables/production. You might be able to understand what is going on even if you do not know any Scala. First, there is some basic parsing of the command-line arguments. The important part are the following lines:

// Configuration of the router, so far always ccn-lite
// It requires the socket to the management interface
// "isCCNOnly = false" indicates that it is a NFN node
// "isAlreadyRunning = true" tells the system that it should not have to start ccn-lite
val routerConfig = RouterConfig(config.ccnLiteAddr,
                                config.ccnlPort,
                                config.prefix,
                                config.mgmtSocket.getOrElse(""),
                                isCCNOnly = false,
                                isAlreadyRunning = config.isCCNLiteAlreadyRunning)

// This configuration sets up the compute server
// "withLocalAm" indicates whether it should start an abstract machine alongside the compute server
val computeNodeConfig = ComputeNodeConfig("127.0.0.1",
                                          config.computeServerPort,
                                          config.prefix,
                                          withLocalAM = false)

// Abstraction of a node which runs both the router and the compute server on localhost over UDP
val node = LocalNode(routerConfig, Some(computeNodeConfig))

// Publish services
// This will internally get the Java bytecode for the compiled services,
// put them into jar files and put the data of the jar into a content object.
// The name of this service is inferred from the package structure of the service
// as well as the prefix of the local node.
// In this case the prefix is given with the command line argument 'prefixStr'
// (e.g. /node/nodeA/nfn_service_WordCount)
node.publishServiceLocalPrefix(new WordCount())
node.publishServiceLocalPrefix(new Pandoc())
node.publishServiceLocalPrefix(new PDFLatex())
node.publishServiceLocalPrefix(new Reverse())

// Publishes the content of the CCN-lite tutorial
node += PandocTestDocuments.tutorialMd(node.localPrefix)
// Publishes a very small two-line markdown file
node += PandocTestDocuments.tinyMd(node.localPrefix)

3. Introduction to service implementation

We now take a closer look to an exemplary service implementation that reverses a given String, found in /src/main/scala/nfn/service/Reverse.scala. You should be able to grasp what it does even without knowing Scala.

package nfn.service

// ActorRef is the reference to an Akka Actor where you can send messages to
// It is used to have access to the client-library style interface to CCN where
// you can send interests to and receive content from. Additionally it is used
// to access the management interface and more.
// This service import is required for the signature function. However, it does not use it.
import akka.actor.ActorRef

// NFNService is a trait, which is very similar to a Java interface
// It requires the implementation of one method called 'function'
class Reverse extends NFNService {

  // This method has two parameters:
  //   args: a list of NFNValues
  //   ccnApi: a reference to the actor providing the CCN interface
  // It returns a NFNValue.
  override def function(args: Seq[NFNValue], ccnApi: ActorRef): NFNValue = {

    // Match the arguments to the expected or supported types
    // It is only implemented on a list with exactly one parameter of type string ('foo bar')
    args match {
      case Seq(NFNStringValue(str)) =>

        // Return a NFNStringValue, a sub-type of NFNValue
        // NFNValue is a trait with a 'toDataRepresentation', which will be called on the result of the
        // function invocation to get the result to put into the final content object
        NFNStringValue(str.reverse)

      // ??? is a Scala construct, it throws a NotImplementedExeption
      case _ => ???
    }
  }
}

In the following is a more complete implementation of WordCount, demonstrating how several arguments and different argument types can be handled:

package nfn.service

import akka.actor.ActorRef

class WordCount() extends NFNService {
  override def function(args: Seq[NFNValue], ccnApi: ActorRef): NFNValue = {
    def splitCount(s: String) = s.split(" ").size

    NFNIntValue(
      args.map({
        // Corresponds to a name or another expression in the call expression
        // The compute server will fetch the data from the network before invoking this function
        case doc: NFNContentObjectValue => splitCount(new String(doc.data))
        case NFNStringValue(s) => splitCount(s)
        case NFNIntValue(i) => 1
        case _ => {
          val str = s"$ccnName can only be applied to values of type NFNBinaryDataValue and not $args"
          throw new NFNServiceArgumentException(str)
        }
      }).sum
    )
  }
}

4. Implementing and publishing a custom service

If you want to use an IDE (e.g. IntelliJ IDEA or Eclipse with Scala plugin) you can generate a fully fledged project by invoking sbt: sbt gen-idea or sbt eclipse.

Create a .scala file in the service folder src/main/scala/nfn/service in the package nfn.service. An example is to implment an service that converts all characters to upper case, e.g. ToUpper.scala. Implement your service accordingly - a Scala String has the function .toUpperCase. It is up to you on what types the service is defined and how many arguments the service supports.

To publish this service, simply add the line node.publishServiceLocalPrefix(new ToUpper()) to the StandaloneComputeServer. If you used the above mention package, you do not have to import anything. If you choose a different place you need to import the class accordingly.

5. Test your service

After rerunning both the ccn-nfn-relay as well as the compute server, you should be able to call your service. Run the according peek with the name of your service being /node/nodeA/nfn_service_ToUpper. If you have chosen a different package, replace every . of the package name with _, e.g. /node/nodeA/my_package_ToUpper.

Optionally you can send us a pull request or an email with the code of your service and we will publish it to the testbed.

6. Uninstall sbt and downloaded libraries

Use the following to uninstall NFN-scala and its dependencies:

Delete the local NFN-scala repository
Uninstall sbt (and remove ~/.sbt if it still exists)
Remove ~/.ivy2 (this will of course also delete all your cached Java jars if you are using ivy)

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tutorial.md

tutorial.md

CCN-lite and NFN Tutorial

Table Of Contents:

0. Installing CCN-lite

1. Producing content

2. Starting `ccn-lite-relay` for node `A`

3. Starting `ccn-lite-relay` for node `B`

4. Add a forwarding rule

5. Send Interest for Name `/ndn/test/mycontent/` to `A`

1. Shutdown relay `B`

2. Remove face to `B`

3. Connecting node `A` directly to the NDN Testbed

4. Send interest to `A`

1. Start a NFN-relay

2. Send a NFN request

0. Prerequisites

1. Start a NFN-relay

2. Start the Scala compute server

3. Send a NFN expression with a word count function call

4. Invoke the pandoc service

5. Invoke the pandoc service with a large document

6. Function chaining

0. Installing NFN-scala

1. Compile and start the Scala compute server

2. Explaining StandaloneComputeServer

3. Introduction to service implementation

4. Implementing and publishing a custom service

5. Test your service

6. Uninstall sbt and downloaded libraries

Files

tutorial.md

Latest commit

History

tutorial.md

File metadata and controls

CCN-lite and NFN Tutorial

Table Of Contents:

0. Installing CCN-lite

1. Producing content

2. Starting ccn-lite-relay for node A

3. Starting ccn-lite-relay for node B

4. Add a forwarding rule

5. Send Interest for Name /ndn/test/mycontent/ to A

1. Shutdown relay B

2. Remove face to B

3. Connecting node A directly to the NDN Testbed

4. Send interest to A

1. Start a NFN-relay

2. Send a NFN request

0. Prerequisites

1. Start a NFN-relay

2. Start the Scala compute server

3. Send a NFN expression with a word count function call

4. Invoke the pandoc service

5. Invoke the pandoc service with a large document

6. Function chaining

0. Installing NFN-scala

1. Compile and start the Scala compute server

2. Explaining StandaloneComputeServer

3. Introduction to service implementation

4. Implementing and publishing a custom service

5. Test your service

6. Uninstall sbt and downloaded libraries

2. Starting `ccn-lite-relay` for node `A`

3. Starting `ccn-lite-relay` for node `B`

5. Send Interest for Name `/ndn/test/mycontent/` to `A`

1. Shutdown relay `B`

2. Remove face to `B`

3. Connecting node `A` directly to the NDN Testbed

4. Send interest to `A`