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Resource Discovery in Self-Organizing Networks

Resource Discovery in Self-Organizing Networks

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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://inat.lcs.mit.edu/hari@lcs.mit.edu

  2. Servers Services in our environment Application #1: Collab Regions

  3. Application #2: Networks of Devices • Access and control services provided by (wireless) networked devices • Integrate the physical world • Sensor computing • Location-dependent applications • Active maps, mobile camera network, object tracking system, climate sensing • Rapidly deployable & configurable systems

  4. Challenges • Configuration • Routing • Discovery • Adaptation • Security

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

  6. Configuration • Manual configuration • Contact network administrator and get an address (+ DNS mapping) • This is the predominant mode today! • Dynamic Host Configuration Protocol (DHCP) • Decentralized ad hoc configuration (work-in-progress)

  7. Packet Routing • IP routing & forwarding • Unicast (RIP, OSPF, BGP) • Multicast (DVMRP, PIM, CBT, BGMP) • Mobile IP (RFC 2002) • Movement (as opposed to relocation) • Continuous connections to mobile hosts • Mobile data sources • Ad hoc routing (IETF MANET WG)

  8. Discovery • Perhaps the hardest challenge in this area • Heterogeneity • Devices • Services • User interfaces • Change • Mobility • Data • Performance • Robust architecture • Spontaneous deployment: ZERO config!

  9. Intentional Naming System Apps know WHAT they want, not WHERE • Descriptive names • Describe intent based on attribute-value tuples • Self-configuring resolvers • Integrate resolution and forwarding • “Late binding” of names to nodes • Soft-state dissemination protocols • Periodic announcements and refreshes

  10. Intentional name • [building = ne-43 • [room = 510]] • [entity = camera] INR INR INR INS Architecture camera510.lcs.mit.edu Intentional Name Resolvers form a distributed overlay Lookup image Integrate resolution and message forwarding

  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. Names are descriptive • Providers announce names • [vspace = camera] • [building = ne-43 • [room = 504]] • [resolution=800x600]] • [access = public] • [status = ready] [vspace = café] [state = ca [city = berkeley] [region = northside]]] [distance < 0.25 miles] • [vspace = thermometer] • [building = ne-43 • [room = *]] • [temperature < 620F] data data Name-Specifiers • Problem: Expressive name language (like XML) • Names are query expressions • Attribute-value matches • Range queries • Wildcard matches Administratively scoped names (e.g., lcs.mit.edu)

  13. Self-Configuring Resolvers • Problem: Manual configuration • Solution: self-configuration protocol • Bootstrap • DNS maintains list of per-domain INRs • Neighbor formation • Based on metrics like round-trip latency • Load balancing • Spawn/kill resolvers on INR nodes

  14. Late Binding • Problem: Track rapid changes • Solution: Integrate resolution and forwarding message • Periodic advertisements from provider nodes refresh state in INR • INRs forward message to destinations • Handles mobile, grouped, and replicated services (& people)

  15. Soft-state Dissemination • Problem: Robustness and availability • Solution: Treat names as soft-state; use “routing” protocols to exchange • Application-level routing & forwarding between INR overlay nodes • To scale well, use bandwidth management heuristics • Namespaces become huge quickly • Treat “hot” and “cold” names differently

  16. 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

  17. Applications • Wireless Networks of Devices (WIND) • Location-dependent & mobile applications over RF and IR • Floorplan: A navigation tool • Camera: An image/video service • Printer: A smart print spooler • TV & jukebox • Server replication • Caching service

  18. TCP UDP Internet UDP WIND Demo • Problem: Firewalls • E.g., UDP for names, advertisements, video • Solution: split protocol across firewall • Completely unchanged applications! • Transparently replace DatagramSocketImpl in java.net udp_recv() IBM Intranet Firewall MIT

  19. Status & Performance • Java implementation of system • Ported to Palm III too! • PC-based resolver performance • 1 resolver --> 75,000 names at > 100 lookups/s (untuned) • Discovery time linear in hops • Algorithms for robust self-configuration • Scalability • Wide-area architecture design in progress • Problem: Decouple service & network hierarchy • Deployment • Hook in wide-area architecture to DNS • Standardize “virtual spaces” (like MIME data types)

  20. 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 • Universal Plug-and-Play • XML-based descriptions; INS fits well • IBM T-spaces • Intentional names in other contexts • Semantic file systems, adaptive web caching, DistributedDirector

  21. INS Summary • Expressive naming language • Self-configuring resolvers form an application-level overlay • Integrate resolution and routing • Soft-state dissemination protocols • Runs on impoverished devices too • Wide-area architecture in progress Enables self-organizing networks & applications

  22. 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 • Resource discovery

  23. 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

  24. What’s the “Right” Network Support? • Put a lot (and more) in the routers • IP Multicast • Reliable multicast primitives • Name redirection (“resolution”) • Web caches • Programmable active routers... • Or, provide more support at the application-level

  25. Supporting Application-Level Networks • General protocols for meta-data dissemination • Using all the good stuff we’ve learned about soft-state protocols • Fault-tolerance primitives • Self-configuring overlays: key component • Bootstrap and placement • Neighbor formation • Load balancing • Security and privacy primitives • E.g., self-certifying names

  26. 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

  27. Conclusions • Achieving self-organization isn’t easy! • Configuration • Message routing • Discovery: INS has many desirable features! • Adaptation • Security & privacy • Application-level networking is key to achieving self-organization and flexibility • But it is being done in rather ad hoc ways • It behooves us to ensure that the future application-level network architecture is at least as sound as the underlying IP substrate