Location-based services

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					   ORBIT: Multimedia
Messaging & location-
      based services
       Henning Schulzrinne
       Columbia University
   Disconnected ad-hoc networks
       multi-modal networking
       7DS prototype
   Location-based services
       location determination
       service creation
       privacy policies
Wireless Network: filling the
infrastructure-ad hoc gap
   Wireless networks:
      Ubiquitous, fast, cheap: pick any two…
   Currently, varies from 0.1c to $4/MB
   Research has primarily explored:
      one-hop infrastructure extension (2G, 3G, 802.11)
      multi-hop connected ad-hoc networks (mesh networks)
   But:
      2G/3G bandwidth will remain low and precious
      hot spots not ubiquitous
      ad hoc networks don’t scale
      brittle if spanning large areas
   Our proposal: use mobile nodes to carry data
      to and from infrastructure networks
   Tourism:
      get information about sights, travel, public transport schedules, ..
      upload picture postcards and video recordings
   Transportation:
      users in buses and trains leverage data capability
   Emergencies:
      propagate “I’m alive” and rescue information
   Mobile sensors:
      sensors spread too far to communicate directly with each other
      large sensor data objects
7DS – a framework for
intermittently connected networks
   Two directions for data:                                 delay
       Internet  mobile nodes
                                                     high        low
       mobile nodes  Internet

                                              high   7DS         802.11
   Each in multiple hops

   but not routed                            low    satellite   voice (2G,
                                                     SMS?        2.5G)
Average Delay (s) vs Dataholders (%)
Peer-to-Peer schemes

       Average Delay (s)

                           1000       high transmission power
                                                            medium transmission power
                                  0    10    20   30   40   50   60   70      80    90     100
                                                                           Dataholders (%)

     P2P (high transmission power) one initial dataholder & 20 cooperative hosts in 2x2
     P2P(medium transmission power) one initial dataholder & 20 coperative hosts in 1x1
Current status: prototype
   Initial Java implementation
       search not just by URL, but by content
        greater likelihood of finding appropriate material
   Working on PDA implementations
   Also, considering Linux embedded systems
       low-power, self-contained
Combining cellular and 7DS
   Proposed research                         Content location
        use ubiquitous, low-speed
         networks for control                   find nearest hotspot
             some only one-way               Cache cleaning
              (satellite, XM, Spot)
        short-range, multi-hop for bulk        indicate popular
         data transmission                       content for proactive
   Cellular reselling                           querying
        pay once for bandwidth, use            remove stale content in
         many times
   Inverse multiplexing                         mobile  Internet case
        for high-priority content            Incentive management
                                                  reputation management
                                                  credit for delivering data
Location-based services
   Finding services based on location
     physical services (stores, restaurants, ATMs, …)
     electronic services (media I/O, printer, display, …)
     not covered here
   Using location to improve (network) services
     communication
           incoming communications changes based on where I am
       configuration
           devices in room adapt to their current users
       awareness
           others are (selectively) made aware of my location
       security
           proximity grants temporary access
   Privacy rules for access to context data
Location-based services & SIP
   We’re using SIP (and SIMPLE) as generic protocols
       effecting change (“actuators”)
         send MESSAGE to devices
       distributing event information (“sensors”)
   Advantages:
       people and rooms identified by URIs
       cross-domain, with extensive security mechanisms
         domains don’t need to trust each other
       scalable to global system
         many other systems are mostly local
Location-based services
   Presence-based approach:
       UA publishes location to presence agent (PA)
       becomes part of general user context
       other users (human and machines) subscribe to context
         call handling and direction
         location-based anycast (“anybody in the room”)
         location-based service directory

   Languages for location-based services
       building on experience with our XML-based service
        creation languages
       CPL for user-location services
       LESS for end system services
Location information
   geospatial
       longitude, latitude, altitude
   civil
       time zone, country, city, street, room, …
   categorical
       type of location
       properties of location
           privacy (“no audio privacy”)
           suitability for different communication media
Determining location
   GPS may not be practical (cost, power,
   Add location beacons
       extrapolate based on distance moved
           odometer, pedometer, time-since-sighting
       idea: meet other mobile location beacons
           estimate location based on third-party information
Example: user-adaptive device
configuration                                     “all devices that are in the building”
                                                  RFC 3082?
                802.11 signal      SLP
             strength  location
  To: 815cepsr
  Contact: alice@cs

                       PA          SUBSCRIBE
                                   to each room

1. discover room URI                                                            SIP
2. REGISTER as contact for room URI

                                                    SUBSCRIBE to configuration
                                                    for users currently in rooms

                                                                                      room 815
Architectures for (geo)
information access
   Claim: all using protocols fall into one of these categories
   Presence or event notification
     “circuit-switched” model
     subscription: binary decision
   Messaging
     email, SMS
     basically, event notification without (explicit) subscription
     but often out-of-band subscription (mailing list)
   Request-response
     RPC, HTTP; also DNS, LDAP
     typically, already has session-level access control (if any at all)
   Presence is superset of other two
Presence/Event notification
   Three places for policy enforcement
       subscription  binary
         only policy, no geo information
         subscriber may provide filter  could reject based on filter
           (“sorry, you only get county-level information”)  greatly
           improves scaling since no event-level checks needed
       notification  content filtering, suppression
         only policy, no geo information
       third-party notification
         e.g., event aggregator
         can convert models: gateway subscribes to event source,
           distributes by email
         both policy and geo data
Presence model


subscriber (watcher)

       for each
               event generator                                   change to previous
                   policy                                           notification?
                                                  rate limiter

Policy rules
   There is no sharp geospatial boundary
   Presence contains other sensitive data
    (activity, icons, …) and others may be added
   Example: future extensions to personal
    medical data
       “only my cardiologist may see heart rate, but
        notify everybody in building if heart rate = 0”
   Thus, generic policies are necessary
Processing models
   Sequential model:
       for each subscriber, apply rules to new data
       doesn’t scale well to large groups
   Relational database model:
       re-use indexing and other query optimizations
       well-defined query and matching semantics
       e.g., mySQL and PostGres have geo extensions
       At time of subscription:
         SELECT address FROM policies WHERE
           person=$subscriber (AND now()
           between(starttime,endtime) OR starttime is null) AND
           (a3=$a3 or a3 is null) …
   7DS as extension of infrastructure and ad-
    hoc networks
   Combine benefits of low bit-rate, but
    ubiquitous and high bit-rate, but sparse
   Location-based services as core wireless
       from location determination to location
        management and privacy

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