wiki:GENIEducation/SampleAssignments/CCNAssignment/ExerciseLayout/Execute

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<CCN ASSIGNMENT>

Hello GENI index Hello GENI index Hello GENI index

STEPS FOR EXECUTING EXERCISE

Objectives

The objective of this assignment is to familiarize you with named data (sometimes called content-centric) networking. You will specifically learn about:

  • The Project CCNx named data networking overlay for IP networks
  • Architectural features of CCNx and other content-centric networking, such as publish-subscribe content distribution, caching at intermediate nodes, and intelligent request forwarding
  • Using named data networking (NDN) to fetch content from multiple sources
  • The effects of cache granularity on bandwidth requirements for content distribution in a named data network
  • The usage of intelligent forwarding to reduce bandwidth requirements in a collaborative environment

Tools

  • ccnd
    The ccnd daemon and its associated software is the reference implementation for the content-centric networking protocol proposed by Project CCNx. This assignment uses release 0.6.1 of the ccnx software package. More information on this package can be found at the Project CCNx web site, http: www.ccnx.org/. The CCN protocol embodied in CCNx is an attempt at a clean-slate architectural redesign of the Internet.
  • Atmos
    The Atmos software package from the NetSec group at Colorado State University will provide named data for your network in the form of precipitation measurements. The Atmos tools are installed in /opt/ccnx-atmos.
  • NetCDF Tools
    NetCDF (Network Common Data Form) is “a set of software libraries and self-describing, machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data.” The NetCDF tools package provides several tools for manipulating NetCDF data, including ncks, a tool for manipulating and creating NetCDF data files; ncdump, a similar tool used for extracting data from NetCDF data files; and ncrcat, a tool for concatenating records from multiple NetCDF data files.
  • Flack
    Flack is a graphical interface for viewing and manipulating GENI resources. It is available on the web at http://www.protogeni.net/trac/protogeni/wiki/Flack. You may use either Omni or Flack to create and manipulate your slices and slivers, but there are certain operations for which you will probably find one or the other easier to use. You will have to use the Flack client to Instrumentize your slices, as you will be directed some exercises.

Exercises


  • 3.1 Routing in a Named Data Network
    In this exercise, you will build a named data network using the Project CCNx networking daemon ccnd and transfer scientific data in the NetCDF format between data providers and data consumers using routing based on content names. For the purpose of this exercise, the network will use static routes installed at slice setup. Content will be served and consumed by the Atmos software package.
    Create a GENI experiment using the precip.rspec file downloaded from here. It will allocate a network such as that depicted in the above figure, with ccnd running on every host and an Atmos server running on the hosts datastore1 and datastore2.
    Routing in named data networks takes place using the namespace under which data is stored. In the case of CCNx, the data namespace is a doc/technical/URI.html URI, so it looks similar to the familiar http:// and ftp:// URLs of the World Wide Web. CCNx URIs are of the form ccnx:<path>, where <path> is a typical URI slash-delimited path. The components of the URI path are used by the network to route requests for data from consumers to the providers of that data. Routes have been installed on all of the machines in the network except researcher2, a data consumer node with two connections to the rest of the named data network.
    • Task 1.1: Finalize Configuration In this task, you will observe the effects of the missing static routes, and restore them.
      Log into the host researcher1. Run the command ccninitkeystore. Issue the command ccndstatus to print the status of the ccnd daemon on the local host. Note the number of content items stored on this host (which should be zero, if you have not yet fetched any content) and the number of interests accepted (under “Interest totals”).
      On researcher1, issue a request for precipitation data from 1902/01/01 through 1902/01/02. To do this, use the Atmos tools by invoking:
      /opt/ccnx-atmos/client.py
      
      Answer the date questions appropriately, and observe that a .nc NetCDF file is created in the current directory containing precipitation data for the specified dates.
      Run ccndstatus again, and look at the statistics on the local ccnd. You should see both that a substantial number of content items are cached on this machine (this is the meaning of the “stored” field under “Content items”) and that many more Interests have been seen.
      Next, log into researcher2 and issue the same command. Observe that it takes much longer at each step, does not terminate, and no .nc file is created. This is because the ccnd on researcher1 had routes to the precipitation data requested by Atmos, but researcher2 does not. Issue the following command to install the appropriate routes:
      ccndc add ccnx:/ndn tcp router
      
      Note that the ccndc command takes a content path (ccnx:/ndn) and binds it to a network path (in this case, the host router, which is a valid hostname on the experiment topology, resolving to an IP address on the router machine). It can also be used to delete routes with the del subcommand.
      • Question 1.1 A:
        From researcher2, fetch the same data again (from 1902/01/01 to 1902/01/02), and record the fetch times reported by client.py. It prints out the time take to pull each temporary file along with the concatenation and write time. Then fetch 1902/02/03 to 1902/02/04, and record those fetch times. Fetch 1902/02/03 to 1902/02/04 a second time, and record the new times. Which transfer was longest, and which was shortest? Knowing that each ccnd caches data for a short period of time, can you explain this behavior?
      • Question 1.1 B:
        Browse the content caches and interests seen on various hosts in the network by loading their ccnd status page on TCP port 9695 in your browser (see Section 5, Hints, below). Which hosts have seen interests and have content cached, and why?
    • Task 1.2: Intent Propagation
      This task will demonstrate the behavior of Intent filtering during propagation.
      Log into the machine datasource1 and run the command tail -f /tmp/atmos-server.log. Next, run /opt/ccnx-atmos/client.py on both of the hosts researcher1 and researcher2. Enter 1902/01/15 as both start and end date on both hosts, and press <ENTER> on both hosts as close to the same time as possible.
      • Question 1.2 A:
        What intents show up at datasource1 for this request? (Use the timestamps in the server log to correlate requests with specific intents.) Will you observe unique or duplicate intents when both researcher1 and researcher2 fetch the same data at precisely the same time? Why?

    • Task 1.3: Explore traffic patterns
      For this task, you will start network monitoring services on your slice and observe the data traffic passing between hosts as you fetch various content.
      Instrumentize your experiment using GEMINI following the instructions here: GENIDesktop Tutorial.
      Log into the host collaborator1 and use the Atmos client to fetch data from 1902/01/28 to 1902/02/03. Look at the GEMINI data usage, and observe that data is pulled from both datasource1 and datasource2, through router to researcher1 and ultimately to collaborator1. Record or remember the data rates and volumes from this transaction. On the GEMINI web interface (GENIDesktop), show real-time graphs from datasource1, datasource2, router, researcher1 and collaborator1, record the throughput numbers or screenshot the graphs.
      • Question 1.3 A:
        Log into collaborator2 and fetch the same dates. Which hosts transfer data? why?
      • Question 1.3 B
        Now fetch 1902/01/25 to 1902/01/31 from researcher2. How does this transfer differ from the previous two? why?
  • 3.2 Choosing Content Names -- Files to download: ccn-naming-pc.rspec, ccnx-atmos.tar.gz
    This exercise will demonstrate the importance of naming in named data networking. As the term suggests, and as you saw in Task 1.1, routing in named data networking is performed based on content names. This means that content naming has a large impact on how consumers fetch the data they require, and naming structure can heavily influence how simple and efficient data requests may be.
    The Atmos package uses content names in the namespace /ndn/colostate.edu/netsec to serve NetCDF data. The data is sliced by time, with the suffix pr_<year>/<month>/<day>/00 added to represent data for the specified date. Thus, clients can request precipitation data for a given day in history, or a range of days, by issuing an interest for the dates in question. The complete path for data relating to January 3, 1902 would be: /ndn/colostate.edu/netsec/pr_1902/01/03/00
    • Task 2.1: Granularity of naming
      This task will require you to change granularity of content names used by the Atmos client and server for different use cases, and measure the resulting traffic changes.
      Create an experimental network using the ccn-naming-pc.rspec RSpec HERE (Note: this experiment does not require using GEMINI to monitor the network). This RSpec creates a network of the same topology as the network used in Exercise 3.1, but does not start or install the Atmos server or client. You will be modifying and installing this software yourself.
      Fetch the Atmos source from http://www.gpolab.bbn.com/experiment-support/CCNExampleExperiment/ccnx-atmos.tar.gz. You may fetch it directly to the testbed nodes you will be using, or to a local machine, as you prefer. You will have to copy the source code to the GENI nodes to build and run it in your experiment.
      Build the Atmos source on hosts datasource1 and datasource2, as well as a collaborator or researcher node of your choice by entering the source directory and running make. On datasource1 and datasource2, you will find a NetCDF data file in /tmp, named pr_19020101_060000.nc and pr_19020201_060000.nc, respectively. On each of these hosts run the command ccninitkeystore and start the Atmos server with the following commands:
      cd /tmp
      $HOME/ccnx-atmos/server $DATAFILE
      
      Substitute $HOME/ccnx-atmos for your actual Atmos build directory, and $DATAFILE for the appropriate filename as described above.
      On the client host you chose, run ./client.py from the data directory and select a few dates from January and February of 1902 for date ranges. Make note of what interests are received at the server, and how long the transfers take.
      Change the client and server programs to use this URI, restricting CCNx transfers to a granularity of one month, but preserving the ability of users to retrieve at one day granularity: /ndn/colostate.edu/netsec/pr_<year>/<month>
      Implementation Hints: It is important understand how script.py uses NetCDF commands to extract relevant dimensions in the data files. The client (client.py) breaks up a user’s request into a collection of URIs (one for each day) and fetches them sequentially. For each URI, script.py generates a list of timestamps (a floating point number indicating the number of days elapsed since January 1, 1901). From the NetCDF data files, script.py extracts the fields that lie within these timestamps. The server side changes are minimal. Once a month’s granularity of data is received at the client side, it should be filtered to match the specific days requested by the user.
      Retrieve a variety of dates in the January to February 1902 date range, and note again what interests are received at the server and how long the transfers take.
      • Question 2.1 A
        What general difference do you see in network behavior between these solutions?
      • Question 2.1 B
        Which URI scheme is more efficient in time and network resources if the user only wants a few days of data? What if the user wants a full calendar month of data?
  • 3.3 Exploring the Impact of Caching -- Files to download: ccn-cache-pc.rspec
    For this exercise you will manipulate various caching parameters for the ccnd daemon and observe the effects on network efficiency.
    A property of named data networking is that multiple requests for the same names may return the same data. This allows intermediate nodes to cache data from one request for a given name and return it for future requests of the same name, from the same client or even a different client. When multiple clients located near each other but far from the server in the network want the same data, a node near the clients may be able to service some clients without contacting the server.
    Caching behavior can be controlled by the client, the server, or the individual ccnd nodes between the two. Servers can optionally specify the recommended cache lifetime of data they generate, clients can optionally request that their data is fetched from the server itself (bypassing caching), and ccnd nodes can define their default and maximum cache lifetimes. Caches may also be affected by the available cache space and volume of interests or data items passing through the cache.
    • Task 3.1: Opportunistic caching
      This task will demonstrate the benefit of opportunistic caching for static data used repeatedly.
      Create a GENI slice using ccn-cache-pc.rspec from Here (Note: this experiment does not require using GEMINI to monitor the network). This slice has only two hosts, a data source and a data consumer. The data source serves historical precipitation data using the Atmos server, which is static information. It has a long cache timeout for this reason — five minutes. The data consumer uses a shorter cache timeout of 60 seconds, and the link between the two emulates a moderate consumer broadband link.
      • Question 3.1 A:
        From the host consumer run /opt/ccnx-atmos/client.py to fetch data from 1902/01/21 through 1902/01/24, and time the total transaction. Within 60 seconds, fetch the same data again, and time it. After 60 seconds (but before 300 seconds have passed), fetch it a third time, and time that. What is the benefit of local caching (the second fetch)? Is there perceptible benefit from server-side caching (the third fetch) when data takes some time to generate?

4. Other Projects

The following are ideas for deeper projects into named data/content-centric net- working or the implementation embodied in CCNx.

  • Design and implement a cache coherence or cache management protocol for content subscribers or content providers to communicate with intermediate nodes to improve caching strategies in the presence of data with dissimilar caching requirements.
  • Develop an application-specific caching mechanism for some data type (perhaps NetCDF) and deploy it in CCNx.
  • Design and implement a protocol for ccnd to communicate directly with other ccnd instances via raw Ethernet frames without IP, ARP, or the rest of the TCP/IP stack.

5. Hints

These hints and answers to common questions may help you debug problems you encounter while performing the exercises in this assignment.

  • Remember that you must run ccninitkeystore before invoking any commands that use ccnd. If CCNx commands don’t seem to be “doing anything”, make sure you have the file .ccnx/.ccnx keystore in your home directory. If it is not present, you have forgotten to initialize the keystore!
  • If you are told that CCNx-related commands such as ccndc are not found, make sure that /opt/ccnx-0.6.1/bin is in your shell’s path.
  • The status of ccnd can be queried either by logging into a host and running ccndstatus, or by loading the web page served by ccnd on port 9695. For example, if your researcher2 node is on pc308.emulab.net and you want to query its forwarding table, you can point your web browser at http://pc308.emulab.net:9695/.
  • If the GENI Desktop portal shows a blank page, and you are running the Chrome browser, click the shield icon at the right of the URL bar and select “Load Anyway”.

Next: Teardown Experiment

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