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Location Based Services Lenin Ravindranath, Microsoft Research India.

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Presentation on theme: "Location Based Services Lenin Ravindranath, Microsoft Research India."— Presentation transcript:

1 Location Based Services Lenin Ravindranath, Microsoft Research India

2 Motivation  Location is a key element of user context  Mobile devices a natural conduit for location based services  They are ubiquitous  Have many sensors sensors  Location -> GPS  GPS based devices are not common  GPS is power hungry  Many apps care about relative location  relative to landmarks  relative to people

3 Scenario Demo!

4 Aspects  Location Determination  need relative location  Neighborhood Discovery  spatial and temporal  Communication  push vs. pull  with or without Internet access  Service model  stateful vs. stateless

5 Overview  Beacon-Stuffing  WiFiAds  Neighborcast  People Near Me  Neighborhood GPS  Landmark based Services  Post-its in the air  Ads, comments and reviews  Location and Neighborhood based reminders, profiles  Social networking

6 Beacon-Stuffing Access Point Beacon Packets Network Name SSID: NYCWireless Network Name SSID: T-Mobile Networks Found Connected WiFi Beaconing Protocol

7 Beacon-Stuffing  Stuff beacon packets with information  Unused fields in beacons (Beacon Information Element)  Stripe across multiple beacons, if needed  Clients receive beacons even when they are not connected to any network  Clients receive beacons from other networks even when they are connected to a particular network  Send dynamic information

8 WiFiAds – Location sensitive Ads AdCenter AP at CoffeeDay WiFi Beacon Within 250 m of CoffeeDay CoffeeDay close to me.. Hmm! I love Hot Choc! Go to CoffeeDay Coffee DayDrink of the day is Hot Chocolate Client running our software

9 Beacon-Stuffing Summary  No absolute location required  Clients near the broadcasting AP gets the information  Push model of information delivery  No connectivity required  Stateless  Published in HotMobile 2007  Joint work with Ranveer Chandra, Jitu Padhye, Alec Wolman  Techfest 2007 Demo

10 Overview  Beacon-Stuffing  WiFiAds  Neighborcast  Buddies Near Me  Neighborhood GPS  Landmark based Services  Post-its in the air  Ads, comments and reviews  Location and Neighborhood based reminders, profiles  Social networking

11 Neighborcast  Goal: communication among nearby nodes  2 nodes are nearby if they hear a common AP  Nearby nodes can be on different frequency channels LAN/Internet

12 Neighborcast  Solution: Leverage multicast techniques  Mapping from AP BSSID to multicast group address  BSSIDs correspond to AP’s MAC ID, and is globally unique  Client joins group of every AP around it  APs it hears as part of its scanning process  Clients frequently publish info on group of associated AP  Infrequently publishes info on other groups it is subscribed to

13 Neighborcast LAN/Internet 00:0B:80:12:34:56 00:0A:80:12:34:55 00:0C:80:12:34:57 Multicast group for BSSID 00:0B:80:12:24:56

14 Implementing Neighborcast  3 approaches:  IP Multicast  Application Level Multicast (ALM)  Pub-sub using RSS feeds  Tradeoffs: overhead, scalability, ease of deployment

15 Neighborcast using IP Multicast  Map AP’s BSSID to IP multicast group address  BSSID (6 bytes): :XX:XX:XX:XX  IP multicast address (4 bytes): :XX:XX:XX  Our mapping approach:  228.XX.XX.XX, where XX:XX:XX is last 3 bytes of BSSID  Example: 00:17:95:81:CA:30 will be  Since 0x81 = 129, 0xCA = 202, 0x30 = 48  Might have collisions! Probably not in same subnet…

16  Neighborcast using IP multicast:  Every client maps AP’s BSSID to IP multicast address  Joins multicast group of all BSSIDs it hears  Publishes info of multicast group of AP it is associated with  Pros:  No need for special infrastructure/server  Approach is scalable since all traffic is local  Cons:  Limited deployment of IP multicast, only in edge networks Neighborcast using IP Multicast

17 Buddies Near Me  Each client joins Neighborcast group of all APs around it  It announces its presence (along with signal strengths) to its Neighborcast group  Learns of nearby buddies  Can also estimate “nearness”  Signal strength

18 Neighborhood GPS  Dynamically help neighbors leverage GPS data from other phones GPS computed-location Cloud/Server

19 Neighborcast Summary  No absolute location required  Two clients are nearby if they hear a same AP  Neighborcast forms IP overlay among nearby nodes  Client needs to be connected  Stateless  Published in HotMobile 2008  Joint work with Ranveer Chandra, Jitu Padhye  Techfest 2008 Demo

20 Overview  Beacon-Stuffing  WiFiAds  Neighborcast  People Near Me  Neighborhood GPS  Landmark based Services  Post-its in the air  Ads, comments and reviews  Location and Neighborhood based reminders, profiles  Social networking

21 Location as Landmarks  For many apps absolute location (GPS) is not required  Location as perceived by a user  Landmarks  Access Points BSSID  GSM Tower ID GSM Tower Access Point

22 Information tagged with Landmarks  Users publish information  Landmark Tagged Information  Automatically tag information published with landmarks  Pictures, Videos, Blogs, Ads  Users search for information  Landmark based Search  Query information based on landmarks

23 Landmark based services Publish (info, AP BSSID, GSM ID) Search (query, AP BSSID, GSM ID) Access Point AP1 BSSID: 00:11:22:33:44:55 GSM Tower GSM1 Tower ID: XX1 Server

24 Post-its in the air

25  Scan for landmarks  Post (tagged with landmarks)  Search (giving landmarks)  Retrieve post-its in the air  Challenges  What if a landmark moves?  Move posts to Neighborhood  How to find the neighborhood?  Radio map

26 Radio Map  Periodically clients report Access Points and GSM towers seen  Build a graph  Nodes are APs/GSM Towers  Edge between two nodes if they are reported together  Node weights and Edge Weights  Delete nodes and edges based on their weights GSM Wi Fi GSM Wi Fi

27 Buddies Near Me GSM WiFi GSM WiFi

28 Buddies who were here  You are visiting a new place  Need to know information and past experience of people  Find friends who visited this place in the past  Find them online  Ask queries

29 Location Sensitive Search  Search for Coffee  Gives nearby Coffee shops info  Search results ranked based on nearness

30 Comments and Reviews  Read others reviews  Post comments

31 Reminders in the air  Location based reminders  Post reminders in the air  Remind me when I cross this place next time  Remind me to buy milk when I am near the market  Remind me office work only when I am in the office  Neighborhood based reminders  Remind me when one or more friends are nearby at a location  Remind me to give Prashanth Rs 100 when he comes nearby

32 Other Applications  Location based profiles  Location based games, Game pairing  Dating service  Enhanced presence

33 Landmark based services Summary  No absolute location required  Leverage Landmarks and Neighborhoods  Client needs to be connected  Stateful  Number of applications  Submitted to Ubicomp 2008  Joint work with Mohit Gupta, Prashanth Mohan  Thinkweek paper (Brooks was here.. So was Red)

34 Benefits Does not depend on GPS Lesser power Works inside buildings, malls No regular war driving necessary (as is in the case of WiFi, GSM triangulation) Readily deployable No operator support required

35 Questions

36 Code in the air  Post code in the air  Devices crossing that location will execute them  Harnessing other devices  Example  Monitor temperature at a place continuously  Post the following code in the air use sensor(themometer) temp = themometer.getTemperature() send(temp, “http://leninr/tempService”)


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