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Resource Discovery inSelf-Organizing Networks
Hari Balakrishnan MIT Lab for Computer Science
http://wind.lcs.mit.edu/[email protected]
With: William Adjie-Winoto, Elliot Schwartz, Jeremy Lilley, Anit Chakraborty
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Application #1: Location-dependent wireless
services
• Access, control services, communicate with them
• Handle mobility & group communication
• Spontaneous networking
• Locate other useful services (e.g., nearest café)Where
?App should be able to
conveniently specify a resource and access it
• Automatically obtain map of region & discover devices, services and people there
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Application #2: Home networks• Networking consumer devices for
information access and control in and around home– Temperature sensors, security cameras,
baby monitors, appliances, lights, etc.– Many (10s to 100s) of devices in the future
• MUST be rapidly deployable and spontaneous
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Challenges
• Configuration• Routing• Discovery• Adaptation• Security & privacy
Dynamic, mobile environment with no pre-configured support for internetworking or service location
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Today
Routers
DNSHostname
Address
• Mostly static topology & services
• Deploying new services cumbersome
• Applications cannot learn about network
• Failures are common!• High management cost
Servers
Clients
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Ad hoc configuration• Static configuration impossible• DHCP-like configuration undesirable
– Over wireless, pre-configured subnetworks and broadcasts problematic
• Solution: Distributed, randomized address assignment
addr = armask = mr
addr = brmask = mr
[ar:mr]
addr = crmask = n
Coalesce?Route?
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Resource discovery• Why is this hard?
– Dynamic environment (mobility, performance changes, etc.)
– No pre-configured support, no centralized servers
– Must be easy to deploy (“ZERO” manual configuration)
– Heterogeneous services & devices• Approach: a new naming system &
resolution architecture
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Design goals
Responsiveness Name resolvers must track rapid changes
Robustness System must overcome resolver and service failure
Easy configuration Name resolvers must self-configure
Names must be descriptive, signifying application intentExpressiveness
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Intentional Naming System (INS) principles
• Names are intentional, based on attributes– Apps know WHAT they want, not WHERE
• INS integrates resolution and forwarding– Late binding of names to nodes
• INS resolvers replicate and cooperate– Soft-state name exchange protocol with periodic
refreshes• INS resolvers self-configure
– Form an application-level overlay network
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INS architecture overview
[building = ne-43[room = 510]]
[entity = camera]
Intentional name
Intentional Name Resolvers (INR) form a distributed overlay
Integrate resolution and message routing
image
Lookup
camera510.lcs.mit.edu
INR self-configuration
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How does it work?
INRINR
DSRDSR
Application-leveloverlay networkformed based on
performance
Inter-domaininformation viaDSR protocol
Exchange namesas if they were routes
Virtual space partitionsDomain Space Resolvers
Scaling?
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INS service model
INRINR
Self-organizing app-leveloverlay network
formed based on performance
Soft-state namedissemination
applicationapplicationEarly bindingEarly binding
Late bindingLate binding queryqueryset of namesset of names
IntentionalanycastIntentional
multicast
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[vspace = thermometer][building = ne-43
[room = *]][temperature < 620F]
data
[vspace = netgroup][department = arch-lab [state = oregon [city = hillsboro]]][rank = admin]
data
What’s in a name?
• Names are queries– Attribute-value matches– Range queries– Wildcard matches
[vspace = camera][building = ne-43
[room = 504]][resolution=800x600]][access = public][status = ready]
• Names are descriptive– Providers announce names
• Expressive name language (like XML)• Resolver architecture decoupled from language
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Responsiveness: Late binding
• Mapping from name to location(s) can change rapidly
• Integrate resolution and message routing to track change– INR resolves name by lookup-and-forward,
not by returning address– lookup(name) is a route– Forward along route
• A name can map to one location (“anycast”) or to many (“multicast”)
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Late binding services• Intentional anycast
– INR picks one of several possible locations– Choice based on service-controlled metric
[contrast with IP anycast]– Overlay used to exchange name-routes
• Intentional multicast– INR picks all overlay neighbors that “express
interest” in name– Message flows along spanning tree– Overlay used to transfer data too
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Robustness: Names as soft-state
• Resolution via network of replicated resolvers• Names are weakly consistent, like network-
layer routes– Routing protocol to exchange names
• Fate sharing with services, not INRs– Name unresolved only if service absent
• Soft-state with expiration is robust against service/client failure– No need for explicit de-registration
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Self-configuring resolvers• INRs configure using a distributed topology
formation protocol• DSR (DNS++) maintains list of candidate
and active INRs• INR-to-INR “ping” experiments for “link
weights”• Current implementation forms (evolving)
spanning tree• INRs self-terminate if load is low
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Efficient name lookups• Data structure
• Lookup – AND operations among orthogonal attributes– For values pick the value(s) satisfying the lookup
• Polynomial-time in worst case
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Scaling issues
• Two potential problems– Lookup overhead– Routing protocol overhead
• Load-balancing by spawning new INR handles lookup problem
• Virtual space partitioning handles routing protocol problem– Just spawning new INR is insufficient
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Virtual space partitioning
vspace=camera vspace=5th-floor
Delegate this to another INR
Routing updates for each vspace
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Applications• Wireless Networks of Devices
(WIND)– Location-dependent mobile applications– Floorplan: A navigation tool– Camera: An image/video service– Printer: A smart print spooler– TV & jukebox
• Server replication• Caching service
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WIND
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Status & performance• Java implementation of INS & applications• PC-based resolver performance
– 1 resolver: several thousand names @100-1000 lookups/s– Discovery time linear in hops
• Scalability– Virtual space partitions for load-shedding– Wide-area design in progress
• Deployment– Hook in wide-area architecture to DNS– Standardize virtual space names (like MIME)
• Paper at SOSP 17 (http://wind.lcs.mit.edu/)
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Related work• Domain Name System
– Differences in expressiveness and architecture• Service Location Protocol
– More centralized, less spontaneous• Jini:
– INS can be used for self-organization & fault-tolerant discovery
• Universal Plug-and-Play & SSDP– XML-based descriptions; INS fits well
• Intentional names in other contexts– Semantic file systems, adaptive web caching,
DistributedDirector
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Application-Level Networks
Increasing number of services that set up application-level overlay networks
• Distributed Web caches• Replica management systems• Transcoders• Multi-party communication• Naming systems• Net news
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What Do They Have in Common?
• Form an overlay over IP• Nodes exchange meta-data
information• Nodes forward messages based on
meta-data• Incorporate configuration machinery• Fault/crash recovery• Load balancing
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Supporting Application-Level Networks
• General protocols for meta-data dissemination
• Fault-tolerance primitives• Self-configuring overlays
– Bootstrap and placement– Neighbor formation– Load balancing
• Security and privacy primitives
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Future Internet Architecture
Resourcemanagement
Flexible IP routers
Traffic engineering
Congestion Manager
Scheduling,buffer mgmt
Middleware
...Cache & replica
management Self-configuringoverlays
INS
Media transcoders
Performance discoveryService
location Jini UPnPE-speak T-spaces
Decentralizedsecurity
Use each other to add value
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Conclusion• Achieving self-organizing networks requires a
flexible naming system for resource discovery– INS works in dynamic, heterogeneous networks– Expressiveness: names convey intent– Responsiveness: late binding– Robustness: soft-state names– Configuration: Resolvers self-configure
• Application-level overlay networks are a good way to build flexible, self-organizing network applications