cis788.11j: introduction to wireless sensor networks (testbeds)
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TRANSCRIPT
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Lecture 8: Testbeds
Anish Arora
CIS788.11J
Introduction to Wireless Sensor Networks
Material uses slides from Larry Peterson, Jay Lapreau, and GENI.net
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References
• EmuLab : artifact-free, auto-configured, fully controlled A configurable Internet emulator 2001: 200 nodes, 500 wires, 2x BFS (switch) 2006: 350 PCs, 7 IXPs, 40 WANodes, 27+ 802.11nodes
• PlanetLab : real environment
• GENI
• 670 machines spanning 325 sites and 35 countries
nodes within a LAN-hop of > 3M users
• Supports distributed virtualization
each of 600+ network services running in their own slice
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Emulab philosophy
• Live-network experimentation Achieves realism
Surrenders repeatability
e.g., MIT “RON” testbed, PlanetLab
• Pure emulation Introduces controlled packet loss and delay
Requires tedious manual configuration
• Emulab approach Brings simulation’s efficiency and automation to emulation
Artifact free environment
Arbitrary workload: any OS, any ”router” code, any program, for any user
So default resource allocation policy is conservative:
allocate full real node & link: no multiplexing; assume max. possible traffic
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Emulab
• Allow experimenter complete control, i.e., bare hardware with lots of tools for common cases OS’s, disk loading, state mgmt tools, IP, traffic generation,
batch, ...
• Virtualization of all experimenter-visible resources
topology, links, software, node names, network interface names, network addresses
Allows swapin/swapout • Remotely accessible• Persistent state maintenance (in database)• Separate control network• Configuration language: ns
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Experiment Life Cycle
$ns duplex-link $A $B 1.5Mbps 20ms
BA DB
A BBA
SpecificationGlobal Resource AllocationNode Self-ConfigurationExperiment ControlSwap OutParsingSwap In
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assign:Mapping Local Cluster Resources
• Maps virtual resources to local nodes and VLANs
• General combinatorial optimization approach to NP-complete problem
• Based on simulated annealing
• Minimizes inter-switch links, # switches & other constraints …
• All experiments mapped in less than 3 secs [100 nodes]
• WANassign for Mapping Global Resources (uses genetic algorithm)
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Frisbee:Disk Loading
• Loads full disk images (bulk download)• Performance techniques:
Overlaps block decompression and device I/O Uses a domain-specific algorithm to skip unused blocks Delivers images via a custom reliable multicast protocol
• 13 GB generic IDE 7200 rpm drives• Was 20 minutes for 6 GB image• Now 88 seconds
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IDE planned for Emulab
• Evolve Emulab to be the network-device-independent control and integration center for experimentation, research, development, debugging, measurement, data management, and archiving
Collaboratory: Emulab’s project abstraction
Workbench: Emulab’s experiment abstraction
Device-independent: Emulab’s builtin abstractions for
all things network-related
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Collaboratory Subsystems
• Source repository:Sourceforge, CVS, Subversion• Datapository• “My Wikis”• Mailing list(s)• Bug database• Chat/IM, chatroom management• Moodle?• Approach
Transparently do authentication, authorization and membership mgmt: “single signon”
Use separate server for information and resource security and management
Support flexible access policies: default is project-private, but project leader can change, per-subsytem Private, public read-only, public read/write
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Experimentation Workbench
• Four types: Workflow management (processes), including
Measurement and feedback steps
mandatory pipelines
Experiment management
Data management
Analyses
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Workbench: “Time Travel” and Stateful Swapout
• Time-travel of distributed systems for debugging Generalize disk image format and handling Periodic disk checkpointing Full state-save on swapout Xen-based virtual machines Challenge: network state (packets in flight)
Pragmatic approach: quiesce senders, flush buffers
• Stateful swapout/swapin [easier] Allows transparent pre-emption experiment
• Related to workbench: history, tree traversal Can share some mechanisms, some UI
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Planetlab: Requirements
1) It must provide a global platform that supports both short-term experiments and long-running services. services must be isolated from each other multiple services must run concurrently must support real client workloads
• Key Ideas Slices Virtualization
multiple architectures on a shared infrastructure Programmable
virtually no limit on new designs Opt-in on a per-user / per-application basis
attract real users demand drives deployment / adoption
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PlanetLab: Slices
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Slices
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Slices
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User Opt-in
ServerNAT
Client
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Virtualization: Per Node View
Virtual Machine Monitor (VMM)
NodeMgr
OwnerVM
VM1 VM2 VMn…
Linux kernel (Fedora Core)+ Vservers (namespace isolation)+ Schedulers (performance isolation)+ VNET (network virtualization)
Auditing serviceMonitoring servicesBrokerage servicesProvisioning services
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Global View
…
…
…
PLC
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Requirements
2) It must be available now, even though no one knows for sure what “it” is deploy what we have today, and evolve over time make the system as familiar as possible (e.g., Linux) accommodate third-party management services
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Brokerage Service
PLC(SA)
VMM
NM VM VM VM…
.
.
.
.
.
.
(broker contacts relevant nodes)
Bind(slice, pool)
VM
User BuyResources( ) Broker
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Requirements
3) Convince sites to host nodes running code written by unknown researchers from other organizations. protect the Internet from PlanetLab traffic must get the trust relationships right trusted intermediary: PLC
NodeOwner
PLCService
Developer(User)1
2
3
4
1) PLC expresses trust in a user by issuing it credentials to access a slice
2) Users trust PLC to create slices on their behalf and inspect credentials
3) Owner trusts PLC to vet users and map network activity to right user
4) PLC trusts owner to keep nodes physically secure
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Requirements
4) Sustaining growth depends on support for site autonomy and decentralized control sites have final say over the nodes they host must minimize (eliminate) centralized control
• Owner autonomy owners allocate resources to favored slices owners selectively disallow unfavored slices
• Delegation PLC grants tickets that are redeemed at nodes enables third-party management services
• Federation create “private” PlanetLabs using MyPLC establish peering agreements
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Requirements
5) It must scale to support many users with minimal resources available expect under-provisioned state to be the norm shortage of logical resources too (e.g., IP addresses)
• Decouple slice creation and resource allocation given a “fair share” by default when created acquire additional resources, including guarantees
• Fair share with protection against thrashing 1/Nth of CPU 1/Nth of link bandwidth
owner limits peak rate upper bound on average rate (protect campus bandwidth)
disk quota
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GENI Design
• Key Idea Slices embedded in a substrate of networking resources
• Two central pieces Physical network substrate
expandable collection of building block components nodes / links / subnets
Software management framework knits building blocks together into a coherent facility embeds slices in the physical substrate
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National Fiber Facility
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+ Programmable Routers
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+ Clusters at Edge Sites
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+ Wireless Subnets
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+ ISP Peers
MAE-West
MAE-East
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Closer Look
Internet
backbone wavelength
backbone switch
Sensor Network
Edge SiteWireless Subnet
Customizable Router
DynamicConfigurable
Switch
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Summary of Substrate
• Node Components edge devices customizable routers optical switches
• Bandwidth national fiber facility tail circuits (including tunnels)
• Wireless Subnets urban 802.11 wide-area 3G/WiMax cognitive radio sensor net emulation
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Management Framework
GMC
Management Services
Substrate Components
- name space for users, slices, & components
- set of interfaces (“plug in” new components)
- support for federation (“plug in” new partners)
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GENI Management Core (GMC)
Resource Controller Auditing Archive
Slice ManagerGMC
nodecontrol
sensordata
CM
Virtualization SW
Substrate HW
CM
Virtualization SW
Substrate HW
CM
Virtualization SW
Substrate HW