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An integrated Experimental Environment for Distributed Systems and Networks

This paper presents Netbed, an integrated experimental environment for distributed systems and networks. It combines simulation, emulation, and live network experimentation in a single framework, providing researchers with a platform to develop, debug, and evaluate their systems. Netbed offers accuracy, artifact-free environment, and universality for resource allocation. It utilizes local-area, distributed, simulated, and emulated resources to create a controlled and repeatable environment for experiments.

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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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