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Resource Discovery in Self-Organizing Networks

Resource Discovery in Self-Organizing Networks. Hari Balakrishnan MIT Lab for Computer Science http://wind.lcs.mit.edu/ hari@lcs.mit.edu. With: William Adjie-Winoto, Elliot Schwartz, Jeremy Lilley, Anit Chakraborty. Spontaneous networking.

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Resource Discovery in Self-Organizing Networks

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  1. Resource Discovery inSelf-Organizing Networks Hari Balakrishnan MIT Lab for Computer Sciencehttp://wind.lcs.mit.edu/hari@lcs.mit.edu With: William Adjie-Winoto, Elliot Schwartz, Jeremy Lilley, Anit Chakraborty

  2. Spontaneous networking • Automatically obtain map of region & discover devices, services and people there • Locate other useful services (e.g., nearest café) Where? Application #1: Location-dependent wireless services • Access, control services, communicate with them • Handle mobility & group communication App should be able to conveniently specify a resource and access it

  3. 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

  4. Challenges • Configuration • Routing • Discovery • Adaptation • Security & privacy Dynamic, mobile environment with no pre-configured support for internetworking or service location

  5. DNS Hostname Address Today Clients • Mostly static topology & services • Deploying new services cumbersome • Applications cannot learn about network • Failures are common! • High management cost Routers Servers

  6. [ar:mr] Ad hoc configuration • Static configuration impossible • DHCP-like configuration undesirable • Over wireless, pre-configured subnetworks and broadcasts problematic • Solution: Distributed, randomized address assignment Coalesce? Route? addr = ar mask = mr addr = br mask = mr addr = cr mask = n

  7. 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

  8. Design goals Expressiveness Names must be descriptive, signifying application intent Name resolvers must track rapid changes Responsiveness System must overcome resolver and service failure Robustness Name resolvers must self-configure Easy configuration

  9. 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

  10. Intentional name • [building = ne-43 • [room = 510]] • [entity = camera] INS architecture overview camera510.lcs.mit.edu Intentional Name Resolvers (INR) form a distributed overlay Lookup image INR self-configuration Integrate resolution and message routing

  11. Inter-domain information via DSR protocol Application-level overlay network formed based on performance Exchange names as if they were routes How does it work? Scaling? Virtual space partitions Domain Space Resolvers INR DSR

  12. set of names Self-organizing app-level overlay network formed based on performance Soft-state name dissemination INS service model application Early binding INR Late binding query Intentional anycast Intentional multicast

  13. Names are descriptive • Providers announce names • [vspace = camera] • [building = ne-43 • [room = 504]] • [resolution=800x600]] • [access = public] • [status = ready] [vspace = netgroup] [department = arch-lab [state = oregon [city = hillsboro]]] [rank = admin] • [vspace = thermometer] • [building = ne-43 • [room = *]] • [temperature < 620F] data data What’s in a name? • Expressive name language (like XML) • Resolver architecture decoupled from language • Names are queries • Attribute-value matches • Range queries • Wildcard matches

  14. 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”)

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. Delegate this to another INR Virtual space partitioning vspace=camera vspace=5th-floor Routing updates for each vspace

  21. 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

  22. WIND

  23. 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/)

  24. 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

  25. 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

  26. 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

  27. 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

  28. Middleware Media transcoders Cache & replica management Self-configuring overlays ... Performance discovery INS Service location Decentralized security Jini UPnP E-speak T-spaces Resource management Traffic engineering Congestion Manager Future Internet Architecture Use each other to add value Flexible IP routers Scheduling, buffer mgmt

  29. 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

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