Location-to-URL Mapping Protocol (LUMP) draft-schulzrinne-ecrit-lump-00 - PowerPoint PPT Presentation

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Location-to-URL Mapping Protocol (LUMP) draft-schulzrinne-ecrit-lump-00

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Location-to-URL Mapping Protocol (LUMP) draft-schulzrinne-ecrit-lump-00 Henning Schulzrinne Dept. of Computer Science Columbia University hgs_at_cs.columbia.edu – PowerPoint PPT presentation

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Title: Location-to-URL Mapping Protocol (LUMP) draft-schulzrinne-ecrit-lump-00


1
Location-to-URL Mapping Protocol
(LUMP)draft-schulzrinne-ecrit-lump-00
  • Henning Schulzrinne
  • Dept. of Computer Science
  • Columbia University
  • hgs_at_cs.columbia.edu

2
Overview
  • Support global-scale resolution of service
    identifiers (e.g., service URNs) locations to
    other URLs
  • Attempts to be reliable and scalable
  • borrow concepts, but not protocol limitations,
    from DNS
  • Architecture Forest of trees with a cloud
    above
  • avoid root as only deployment alternative
  • Uses standard web services building blocks

3
Overall architecture
carrier X customers
knows all trees caches results
R
R
R
R
flooding
R
R
nj.us
ny.us
bergen.nj.us
leonia.bergen.nj.us
4
Resolution
  • Client queries local resolver
  • doesnt know which tree to query!
  • If not in cache, find tree root
  • Resolver queries tree root
  • recursively or iteratively

5
Cluster architecture
  • Each resolver or auth. server is actually a
    cluster of 1 nodes
  • Automatically replicates changes (per record) to
    all other nodes
  • tested with mSLP

nj.us
node
node

R
node
node
6
Split jurisdictions
Im responsible for (parts of) Anytown
Anytown
asks both child nodes
query
Elm Street Oak Street Oak Street Anytown
Main Street Broad Street Main Square Anytown
7
Building trees
  • Trees are built from the top down
  • Parents add children
  • query for coverage region
  • Next level down may differ for
  • each service type (sos.fire vs. sos.police vs.
    roadside-assistance)
  • geo vs. civic

8
Top-level distribution
  • Top-levels of trees distribute their coverage
    region to peers
  • either civic pattern (CUS, A1NJ) or polygon
  • Peers distribute data to other peers
  • ? top-level scope data gets flooded to all
    resolvers
  • new resolvers query peer for current data set
  • periodic do you have any new data to avoid sync
    loss
  • volume of data modest since top-level coverage
    changes slowly
  • estimate one map/month (few thousand
    bytes/month)

9
Caching
  • Caching at all levels
  • best effort update if expired and auth. server
    cant be contacted within T, use local value ? no
    good alternative
  • Cache populated by verification queries
  • MSAG validation and/or access testing
  • Query returns hints
  • e.g., ask for specific geo location
  • get back enclosing polygon with service area

10
Operations
  • Query record (recursive, redirection)
  • either from LObj or LRef
  • Query range (poly, civic)
  • return map or list of civic ranges
  • Provide update vector (from peer)
  • identified by time hash
  • also used to seed data
  • Obtain updates via vector
  • get list of objects
  • Push new data object
  • for cluster synchronization

11
Discovery
  • LUMP resolver discovery via
  • DHCP (if offered by ISP)
  • likely close-by and with full cache
  • SIP configuration (MSP)
  • most likely to be operated by MSP?
  • Bonjour
  • subnet

12
Design assumptions
  • Cant predict deployment model
  • May change over lifetime of protocol
  • from peer to root model
  • Want to have diverse implementations in each
    cluster and tree ? need standardized
    synchronization mechanisms

13
Open issues
  • Clean up architecture description and terminology
  • Need to define WSDL
  • Define coverage maps for geo and civic
  • Estimate bandwidth usage for flooding
  • Security how to trust tree scope announcements
  • sign (XMLDSIG) announcements
  • who can sign for what some authority (e.g.,
    regulator, NENA in US?)
  • mediator (trust aggregator) may do job
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