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An integrated Experimental Environment for Distributed Systems and Networks

B. White, J. Lepreau, L. Stoller, R. Ricci, S. Guruprasad, M. Newbold, M. Hibler, C. Barb, A. Joglekar. An integrated Experimental Environment for Distributed Systems and Networks. Presented by Sunjun Kim Jonathan di Costanzo 2009/04/13. Outline. Motivation Netbed structure

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An integrated Experimental Environment for Distributed Systems and Networks

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  1. B. White, J. Lepreau, L. Stoller, R. Ricci, S. Guruprasad, M. Newbold, M. Hibler, C. Barb, A. Joglekar An integratedExperimentalEnvironment for Distributed Systems and Networks Presented by Sunjun Kim Jonathan di Costanzo 2009/04/13

  2. Outline Motivation Netbed structure Validation and testing Netbed contribution Conclusion

  3. Outline Motivation Netbed structure Validation and testing Netbed contribution Conclusion

  4. Background • Researchersneed a platform in whichtheycandevelop, debug, and evaluate their systems • One labis not enough, lack of resources • Need more computers • Scalability in terms of distance and number of nodescan’tbereached • Requires a hugeamount of time to develop large scaleexperiments

  5. Previousapproaches • Simulation: NS • Live networks: PlanetLab • Emulation: Dummynet, NSE controlled, repeatable environment Loses accuracy due to abstraction • Achieves realism Not easy to repeat the experimentagain controlled packet loss and delay • Manual configuration is boring

  6. Netbedideas • Derives from “Emulab Classic” • A universally-available time- and space-shared network emulator • Automatic configuration from NS script • Add Virtual topologies for network experimentations • Integrates simulation, emulation, and live-network with wide-area nodes experimentation in a single framework

  7. Netbed goals • Accuracy • Provide artifact-free environment • Universality • Anyonecan use anything the wayhewants conservative policy for the resource allocation • No multiplexing (virtual machine) • The resource of one node can be fully utilized

  8. Resources • Local-Area Resources • Distributed Resources • Simulated Resources • Emulated Resources • WAN emulator (integratedyet) • PlanetLab • ModelNet (still in work)

  9. Outline Motivation Netbed structure Validation and testing Netbed contribution Conclusion

  10. Netbed structure Resource Life cycle

  11. Local-Area resources • 3 clusters • 168 in Utah, 48 PCs in Kentucky & 40 in Georgia • Eachnodecanbeused as • Edgenode, router, traffic-shapingnode, trafficgenerator • Exclusivity of a machine during an experiment • The OS isgiven but entirelyreplaceable

  12. Local-Area resources

  13. Distributed resources • Alsocalledwide-area resources • 50-60 nodes in approximatively 30 sites • providescharacteristic live network • Very few nodes • Thesenodes are sharedbetweenmanyusers • FreeBSDJailmechanism (kind of Virtual machine) • Non-rootaccess

  14. Distributed resources

  15. Simulated resources • Based on nse (NS-emulation) • Enables interaction with real traffics • Providesscalabilitybeyondphysical resources • Manysimulatednodescanbemultiplexed

  16. Emulated resources • VLANs • Emulatewide-area links within a local-area • Dummynet • Emulates queue & bandwidth limitation , introducing delays and packet loss betweenphysicalnodes • nodes act as Ethernet bridges • transparent to experimental traffic

  17. Netbed structure Resource Life cycle

  18. Life cycle

  19. A B DB Life cycle Global Resource Allocation Node Self-Configuration Experiment Control Specification Swap Out Parsing Swap In $ns duplex-link $A $B 1.5Mbps 20ms A B A B

  20. AccessingNetbed • Experimentcreation • A project leader propose a project on the web • A netbed staff accept or reject the project • All the experimentwillbe accessible from the web • Experimentmanagment • Log on allocatednodes or on the usershost (fileserver) • The fileserversend the OS images, home and project directories to the othernodes

  21. AccessingNetbed

  22. Specification • Experimenters use ns scripts withTcl • can do as manyfunctions & loops as theywant • Netbeddefines a small set of ns extension • Possibility of chosing a specfic hardware • simultation, emulation, or real implementation • Program objectscanbedefinedusing a Netbed-specificns extension • Possibility of usinggraphical UI

  23. Parsing • Front-end Tcl/ns parser • Recognizessubset of ns relevant to topology & trafficgeneration • Database • Store an abstraction of everything about the exeriment • Fixedgeneratedevents • Information about Hardwares , users & experiments • procedures

  24. Parsing

  25. Global Resource Allocation • Binds abstractions from the database to physical or simulatedentities • Best effort to match withspecifications • On-demand allocations (no reservations) • 2 differentalgorithms for local and distributednodes (differentconstraints) • Simulatedannealing • Geneticalgorithm

  26. Global Resource Allocation • Over-reservation of the bottleneck • inter-switchbandwithis to small (2 Gbps) • Againsttheir conservative policy • Dynamic changes of the topology are allowed • Add and removenodes • Consistent namingacrossinstantiations • Virtualization of IP addresses and host names

  27. NodeSelf-Configuration • Dynamiclinking and loadingfrom the DB • Let have the propercontext (hostname, disk image, script to start the experiment) • No persistent configuration states • Only volatile memory on the node • If requiered, the current soft state canbestored in the DB as a hard state • Swap out / Swap in

  28. NodeSelf-Configuration • Local Nodes • All nodes are rebooted in parallel • Contact the masterhostwhichloads the kerneldirected by the database • A second level boot mayberequiered • Distributednodes • Boot from a CD-ROM then contact the masterhost • A new FreeBSDJailisinstantiated • Tested Master Control Client

  29. Experiment Control • Netbed supports dynamicexperiment control • Start, stop and resumeprocesses, trafficgenerators and network monitors • Signalsbetweennodes • Used of a Publish/Subscribeeventrouting system • The staticevents are retrievedfrom the DB • Dynamics events are possible

  30. Experiment Control • ns configuration files isonlyhigh-level control • Experimenterscan made somelow-levelcontrols • On local node: rootprivileges • Kernel modification & access to raw sockets • On distributed: Jail-restrictedrootprivileges • Access to raw socket with a specific IP address • Each local node support separated network isolatedfrom the experimental one • Enable to control a node via a tunnel as wewhere on itwithoutinterfering

  31. Preemptionand Scheduling • Netbedtry to preventidling • 3 metrics: traffic, use of pseudo-terminal devices & CPU loadaverage • To be sure, a message is sent to the user whocandisapprovemanually • A challenge for distributednodeswithseveralJails • Netbed proposes automated batch experiments • When no interaction isrequired • Enables to wait for available resources

  32. Outline Motivation Netbed structure Validation and testing Netbed contribution Conclusion

  33. Validation • 1st row : emulation overhead • Dummynet gives better results than nse

  34. Validation • They expect to have better results with future improvements of nse

  35. Validation • 5 nodes are communicating with 10 links • Evaluation of a derivative of DOOM • Their goal is to sent 30 tics/sec

  36. Testing • Challenges • Depends on physical artifacts (cannot be cloned) • Should evaluate arbitrary programs • Must run continuoustly • Minibed: 8 separated Netbed nodes • Test mode: prevent hardware modifications • Full-test mode: provides isolated hardware

  37. Outline Motivation Netbed structure Validation and testing Netbed contribution Conclusion

  38. Practical benefits • All-in-one set of tools • Automated and efficient realization of virtual topologies • Efficient use of resources through time-sharing and space-sharing • Increase of fault-tolerance (resource virtualization)

  39. Practical benefits • Examples • The “dumbbell” network • 3h15 --> 3 min • Improvement in the utilization of a scarce and expensive infrastructure: 12 months & 168 PC in Utah • Time-sharing (swapping): 1064 nodes • Space-sharing (isolation): 19,1 years • Virtualization of name and IP addresses • No problem with the swappings

  40. Key services • Experiment creation and swapping • Mapping • Reservation • Reboot issuing • Reboot • Miscellaneous • Double time to boot on a custom disk image

  41. Key services • Mapping local resources: assign • Match the user’s requirements • Based on simulated annealing • Try to minimizes the number of switch and inter-switch bandwidth • Less than 13 seconds

  42. Key services • Mapping local resources: assign

  43. Key services • Mapping distributed resources: wanassign • Different constraints • Fully connected via the internet • “Last mile”: type instead of topology • Specific topologies may be guaranteed by requesting particular network characteristics (bandwidth, latency & loss) • Based on a genetic algorithm

  44. Key services • Mapping distributed resources: wanassign • 16 nodes 100 edges : ~1sec • 256 nodes & 40 edges/nodes : 10min~2h

  45. Key services • Disk reloading • 2 possibilities • complete disk image loading • incremental synchronization (hash tables on files or blocks) • Good • Faster (in their specific case) • No corruption • Bad • Waste of time when similar images are needed repeatly • Pace reloading of freed node (reserved for 1 user)

  46. Key services • Disk reloading • Frisbee • Performance techniques: • Uses a domain-specific algorithm to skip unused blocks • Delivers images via a custom reliable multicast protocol • 117 sec for 80 nodes, write 550MB instead of 3GB

  47. Key services • Scaling of simulated resources • Simulated nodes are multiplexed on 1 physical node • Must deal with real time taking into account the user’s specification : rate of events • Test of a live TCP at 2Mb CBR • 850MHz PC with UDP background 2Mb CBR / 50ms • Able to have 150 links for 300 nodes • Problem of routing in very complex topologies

  48. Example of a new possibility • Possibility to program different batch experiment, with the modification of only 1 parameter by 1 • The Armada file system from Oldfield & Kotz • 7 bandwidths x 5 latencies x 3 application settings x 4 configs of 20 nodes • 420 tests in 30 hrs (4.3 min ~ per experiment)

  49. Outline Motivation Netbed structure Validation and testing Netbed contribution Conclusion

  50. Summary • Netbed deals with 3 test environments • Reuse of ns script • Quick setup of the test environment • Virtualization techniques provide the artifact-free environment • Enables qualitatively new experimental techniques

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