Title: Is Your Car Talking with My Smart Phone? or Distributed Sensing and Computing in Mobile Networks
1Is Your Car Talking with My Smart
Phone?orDistributed Sensing and Computing in
Mobile Networks
- Cristian Borcea
- Department of Computer Science, NJIT
2Wireless Computing/Sensing Systems
- gt3.3B cell phones vs. 600M Internet-connected
PCs in 2007 - gt600M cell phones with Internet capability,
rising rapidly - New cars come equipped with GPS, navigation
systems, and lots of sensors - Sensor deployment just starting, but some
estimates 5-10B units by 2015
3Ubiquitous Computing Vision
- Computing, communication, and sensing anytime,
anywhere - Wireless systems cooperate to achieve global tasks
- How close are we from this vision?
4So Far Not Very Close
- Nomadic computing
- Devices laptops
- Internet intermittent connectivity
- Work typical desktop applications
- Mobile communication
- Devices PDAs, mobile phones, Blackberries
- Internet continuous connectivity
- Work email and web
- Experimental sensor networks
- Devices Berkeley/Crossbow motes
- Internet possible through base station
- Work monitor environment, wildlife
5Why?
- Hard to program distributed applications over
collections of wireless systems - Systems
- Distributed across physical space
- Mobile
- Heterogeneous both hardware and software
- Resource-constrained battery, bandwidth, memory
- Networks
- Large scale
- Volatile ad hoc topologies, dynamic resources
- Less secure than wired networks
6Our Research
- What programming models, system architectures,
and protocols do we need when everything connects?
7Outline
- Motivation
- MobiSoC A middleware for mobile social computing
- Migratory Services A context-aware service model
for mobile ad hoc networks - RBVT Road-based routing using real-time traffic
information in vehicular networks - Conclusions
- New projects
- Mobius A socially-aware peer-to-peer network
infrastructure - Traffic safety using vehicular networks and
sensor networks
8Social Computing in the Internet
Myspace
Facebook
LinkedIn
- Social networking applications improve social
connectivity on-line - Stay in touch with friends
- Make new friends
- Find out information about events and places
9Mobile Social Computing
- More than just social computing anytime, anywhere
- New applications will benefit from real-time
location and place information - Smart phones are the ideal devices
- Always with us
- Internet-enabled
- Locatable (GPS or other systems)
- 200-400 MHz processors
- 64-128 MB RAM
- GSM, WiFi, Bluetooth
- Camera, keyboard
- Symbian, Windows Mobile, Linux
- Java, C, C
10Mobile Social Computing Applications (MSCA)
- People-centric
- Are any of my friends in the cafeteria now?
- Is there anybody nearby with a common background
who would like to play tennis? - Place-centric
- How crowded is the cafeteria now?
- Which are the places where CS students hang out?
- How to program MSCA?
- Challenges capturing the dynamic relations
between people and places, location systems,
privacy, battery power
11MobiSoC Middleware
- Common platform for capturing, managing, and
sharing the social state of a physical community - Discovers emergent geo-social patterns and uses
them to augment the social state
12MobiSoC Architecture
13Learning Emergent Geo-Social Patterns Example
GPI Algorithm
- GPI identifies previously unknown social groups
and their associated places - Fits into the people-place affinity learning
module - Clusters user mobility traces across time and
space - Its results can
- Enhance user profiles and social networks using
newly discovered group memberships - Enhance place semantics using group meeting times
and profiles of group members
14Location System
- Hardware-based location systems not feasible
- GPS doesnt work indoors
- Deploying RF-receivers to measure the signals of
mobiles is expensive and not practical for large
places - The user has no control over her location data!
- Software-based location systems that run on
mobile devices preferable - Use signal strength and known location of WiFi
access points or cellular towers - Allow users to decide when to share their location
15Mobile Distributed System Architecture
- MSCA split between thin clients running on
mobiles and services running on servers - MSCA clients communicate synchronously with the
services and receive asynchronous events from
MobiSoC
- Advantages
- Faster execution
- Energy efficiency
- Improved trust
16Clarissa Location-enhanced Mobile Social Matching
MatchTypeHangout Time 1-3PM Co-Location
required
Match Alert
Match Alert
MatchTypeHangout Time 2-4PM Co-Location
required
17Tranzact Place-based Ad Hoc Social Collaboration
Cafeteria
18MobiSoC Implementation
- Runs on trusted servers
- Beta release https//sourceforge.net/projects/mob
isoc/ - Service oriented architecture over Apache Tomcat
- Core services written in JAVA
- API is exposed to MSCA services using KSOAP
- KSOAP is J2ME compatible and can be used to
communicate with clients - Client applications developed using J2ME on
WiFi-enabled Windows-based smart phones - Clarissa http//apps.facebook.com/matching/
- Location engine modified version of Intels
Placelab - Accuracy 10-15 meters
19Outline
- Motivation
- MobiSoC A middleware for mobile social computing
- Migratory Services A context-aware service model
for mobile ad hoc networks - RBVT Road-based routing using real-time traffic
information in vehicular networks - Conclusions
- New projects
- Mobius A socially-aware peer-to-peer network
infrastructure - Traffic safety using vehicular networks and
sensor networks
20Ad Hoc Networks as Data Carriers
- Traditionally, ad hoc networks used to
- Connect mobile systems (e.g., laptop, PDA) to the
Internet - Transfer files between mobile systems
Internet
Read email, browse the web
File transfers
21Ad Hoc Networks as People-Centric Mobile Sensor
Networks
- Typical devices smart phones and vehicular
systems - Run distributed services
- Acquire, process, disseminate real-time
information from proximity of regions, entities,
or activities of interest - Have context-aware execution
- Often interact for longer periods of time with
clients
Traffic jam predictor
Entity tracking
Parking spot finder
22Problems with Traditional Client-Server Model in
Ad Hoc Networks
- When service stops satisfying context
requirements, client must discover new service - Overhead due to service discovery
- State of the old service is lost
- Not always possible to find new service
23Migratory Services Model
Context Change! (e.g., n2 moves out of the region
of interest) MS cannot accomplish its task on n2
any longer
24One-to-One Mapping between Clients and Migratory
Services
M
Meta-service
25Migratory Services Framework
26 TJam Migratory Service Example
- Predicts traffic jams in real-time
- The request specifies region of interest
- Service migrates to ensure it stays in this
region - Uses history (service execution state) to improve
prediction - TJam utilizes information that every car has
- Number of one-hop neighboring cars
- Speed of one-hop neighboring cars
Inform me when there is high probability of
traffic jam 10 miles ahead
27Implementation
- Implemented in Java
- Java 2 Micro-Edition (J2ME) with CLDC 1.1 and
MIDP 2.0 - J2ME with CDC
- Development using HP iPAQs (running Linux), Nokia
phones (running Symbian) - SM platforms
- Original SM on modified KVM (HP iPAQs)
migration state captured in the VM - Portable SM on Java VM, J2ME CDC (Nokia 9500)
migration state captured using bytecode
instrumentation
28Outline
- Motivation
- MobiSoC A middleware for mobile social computing
- Migratory Services A context-aware service model
for mobile ad hoc networks - RBVT Road-based routing using real-time traffic
information in vehicular networks - Conclusions
- New projects
- Mobius A socially-aware peer-to-peer network
infrastructure - Traffic safety using vehicular networks and
sensor networks
29Vehicular Ad Hoc Networks (VANET)
Vehicle-to-vehicle short-range wireless
communication
- Safer driving
- Quick dissemination of traffic alerts
- More fluid traffic
- Real-time dissemination of traffic conditions,
traffic queries, dynamic route planning - In-vehicle computing entertainment
- P2P file sharing, gaming, location-aware
advertisements
30EZCab Automatic Cab Booking Application
Need a cab
- Use mobile ad hoc networks of cabs to book a free
cab - Used HP iPaqs, GPS, WiFi
31TrafficView Traffic Monitoring Application
- Provides dynamic, real-time view of the traffic
ahead of you - Initial prototype
- Laptop/PDA running Linux
- WiFi Omni-directional antennas
- GPS Tiger/Line-based digital maps
- Road identification software
- Second generation prototype (developed
- by Rutgers Univ) adds
- Touch screen display
- 3G cards
- Possibility to connect to the OBD system
32Routing still a Big Problem for VANET
- Topological routing (e.g., AODV, DSR) suffers
from frequent broken paths
- Geographical routing (e.g., GPSR) frequently
routes packets to dead-ends
33RBVT Routing
- Make decisions based on
- Road topology
- Real-time data about vehicular connectivity on
the roads - More stable paths
- Consist of wirelessly-connected road
intersections - Geographical forwarding used within road segments
34Reactive and Proactive RBVT
- RBVT-R (reactive)
- Creates paths on-demand
- Route discovery floods the network to find
destination and records path - Route reply returns path to source
- RBVT-P (proactive)
- Connectivity packet unicasted periodically to
discover the graph of wirelessly-connected road
segments - When complete, connectivity packet flooded in the
network to update the nodes with the new graph - Nodes compute shortest paths using this graph
35Improved Geographical Forwarding
- Remove overhead-prone periodic hello messages
- Used to learn the neighbors
- Replace them with distributed receiver-based next
hop election - Self-election based on distance to destination,
received power, and distance to sender - Messages piggybacked on 802.11 RTS/CTS
36Evaluation
- NS-2 simulator with 250 cars moving at 20-60mph
- 15 concurrent CBR flows
- Implemented a realistic vehicular traffic
generator - Average delivery rate RBVT-R is 71 better than
AODV and 41 better than GSR - Average end-to-end delay RBVT-P is one order of
magnitude better than AODV and GSR
37Conclusions and Lessons Learned
- Smart phones and vehicular systems create large
scale real-life mobile networks - Significant amount of system/networking research
necessary to build applications over these
networks - Testing in real-life conditions is a must
- Ideally, at a decent scale as well
- Power is the most important resource of a mobile
system - Communication failures are the norm rather than
the exception - Applications must be able to adapt to context and
be robust to sensing errors
38Outline
- Motivation
- MobiSoC A middleware for mobile social computing
- Migratory Services A context-aware service model
for mobile ad hoc networks - RBVT Road-based routing using real-time traffic
information in vehicular networks - Conclusions
- New projects
- Mobius A socially-aware peer-to-peer network
infrastructure - Traffic safety using vehicular networks and
sensor networks
39Mobius Network Infrastructure
- Decentralized two-tier infrastructure for mobile
social computing - P2P tier
- Manages social state
- Runs user-deployed services in support of mobile
applications - Dynamically adapts to the geo-social context to
enable energy-efficient, scalable, and reliable
applications - Mobile tier
- Runs mobile applications and collects geo-social
information using ad hoc communication
Application scenario Community Multimedia
Sharing System
40Traffic Safety using VANET/Sensor Networks
Symbiosis
- Add road-side sensors that communicate among
themselves as well as with vehicles passing by - Improvement over VANET-only solutions
- Better detection of dangerous events
- Better network connectivity
- Persistent location-based storage
- Research
- Communication protocols between vehicles and
sensors - Programming API over this heterogeneous
environment
41Acknowledgments
- Work sponsored by NSF grants
- CNS-0831753, CNS-0454081, IIS-0534520, IIS-
0714158 (mobile social computing) - CNS-0520033, CNS-0834585 (vehicular networks)
- Students
- Daniel Boston, Ankur Gupta, Achir Kalra, Josiane
Nzouonta, Neeraj Rajgure - Collaborators
- Grace Wang (CS), Quentin Jones (IS), Adriana
Iamnitchi (Univ. of South Florida), Liviu Iftode
(Rutgers), Oriana Riva (ETH Zurich)
42Thank you! http//www.cs.njit.edu/borcea/