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Title: Design and Implementation of Smartphone-based Systems and Networking


1
Design and Implementation of Smartphone-based
Systems and Networking
  • Dong Xuan
  • Department of Computer Science and Engineering
  • The Ohio State University, USA

2
Outline
  • Smartphones Basics
  • Mobile Social Networks
  • E-Commerce
  • E-Health
  • Safety Monitoring
  • Future Research Directions

3
Smartphone Basics
  • A smartphone is a mobile phone offering advanced
    capabilities, often with PC-like functionality
  • Hardware (Apple iPhone 3GS as an example)
  • CPU at 600MHz, 256MB of RAM
  • 16GB or 32GB of flash ROM
  • Wireless 3G/2G, WiFi, Bluetooth
  • Sensors camera, acceleration, proximity, light
  • Functionalities
  • Communication
  • News Information
  • Socializing
  • Gaming
  • Schedule Management etc.

3
4
Smartphone Popularity
  • Smartphones are popular and will become more
    popular

4
5
Smartphone Accessories
6
Smartphone Features
  • Communication/Sensing/Computation
  • Inseparable from our human life

6
7
Our Smartphone Systems
  • E-SmallTalker IEEE ICDCS10
  • senses information published by Bluetooth to
    help potential friends find each other (written
    in Java)
  • E-Shadow IEEE ICDCS11 enables rich local
    social interactions with local profiles and
    mobile phone based local social networking tools
  • P3-Coupon IEEE Percom11 automatically
    distributes electronic coupons based on an
    probabilistic forwarding algorithm

8
Our Smartphone Systems
  • Drunk Driving Detection Per-Health10 uses
    smartphone (Google G1) accelerometer and
    orientation sensor to detect
  • Stealthy Video Capturer ACM WiSec09 secretly
    senses its environment and records video via
    smartphone camera and sends it to a third party
    (Windows Mobile application)

Download Run
Video sent by Email
Captured Video
8
9
Exemplary System IE-SmallTaker
  • Small Talk
  • A Naïve Approach
  • Challenges
  • System Design
  • Implementation and Experiments
  • Remarks

10
Small Talk
  • People come into contact opportunistically
  • Face-to-face interaction
  • Crucial to people's social networking
  • Immediate non-verbal communication
  • Helps people get to know each other
  • Provides the best opportunity to expand social
    network
  • Small talk is an important social lubricant
  • Difficult to identify significant topics
  • Superficial

11
A Naive Approach of Smartphone-based Small Talk
  • Store all users information, including each
    users full contact list
  • User report either his own geo-location or a
    collection of phone IDs in his physical proximity
    to the server using internet connection or SMS
  • Server performs profile matching, finds out small
    talk topics (mutual contact, common interests,
    etc.)
  • Results are pushed to or retrieved by users

12
However
  • Require costly data services (phones internet
    connection, SMS)
  • Require report and store sensitive personal
    information in 3rd party
  • Trusted server may not exist
  • Server is a bottleneck, single point of failure,
    target of attack

13
E-SmallTalker A Fully Distributed Approach
  • No Internet connection required
  • No trusted 3rd party
  • No centralized server
  • Information stored locally on mobile phones
  • Original personal data never leaves a users
    phone
  • Communication only happens in physical proximity

14
Two Challenges
  • How to exchange information without establishing
    a Bluetooth connection
  • Available data communication channels on mobile
    phones
  • Cellular network (internet, SMS, MMS), Bluetooth,
    WiFi, IrDA
  • Bluetooth is a natural choice
  • Bluetooth connection needs users interaction due
    to security reasons
  • How to find out common topics while preserving
    users privacy
  • No pre-shared secret for strangers
  • Bluetooth Service Discovery Protocol can only
    transfer limited service information

15
System Architecture
  • Context exchange
  • Context encoding and matching
  • Context data store
  • User Interface

16
Context Exchange
  • Exploit Bluetooth service discovery protocol
  • No Bluetooth connection needed
  • Publish encoded contact data (non-service
    related) as (virtual) service attributes
  • Limited size and number( e.g. 128 bytes max each
    attribute)

17
Context Encoding
  • Example of Alices Bloom filter
  • Alice has multiple contacts, such as Bob, Tom,
    etc.
  • Encode contact strings, Firstname.lastname_at_phone_n
    umber, such as Bob.Johnson_at_5555555555 and
    Tom.Mattix_at_6141234567

18
Implementation
  • J2ME
  • about 40 java classes, 127Kb jar file
  • On real phones
  • Sony Ericsson (W810i), Nokia (5610xm, 6650, N70,
    N75, N82)

19
Experiments
  • Settings
  • 6 phones, n150, k7, m1024 bits, default
    distance4m, average of 10 runs
  • Performance Metrics
  • Discovery time the period from the time of
    starting a search to the time of finding someone
    with common interest, if there is any
  • Discovery rate percentage of successful
    discoveries among all attempts
  • Power consumption
  • Factors
  • Bluetooth search interval
  • Number of users
  • Distance

20
Experiment Results
  • Minimum, average and maximum discovery time are
    13.39, 20.04 and 59.11 seconds respectively
  • Always success if repeat searching, 90 overall
    if only search once
  • Nokia N82 last 29 hours when discovery interval
    is 60 seconds

21
Related Work
  • Social network applications on mobile phones
  • Social Serendipity
  • Centralized, Bluetooth MAC and profile matching,
    SMS, strangers
  • PeopleTones, Hummingbird, Just-for-Us, MobiLuck,
    P3 Systems, Micro-Blog, and Loopt
  • Centralized, GPS location matching, Internet,
    existing friends
  • Nokia Sensor and PeopleNet
  • Distributed, profile, Bluetooth / Wifi
    connection, existing friends
  • Private matching and set intersection protocols
  • Homomorphic encryption based
  • Too much computation and message overhead for
    mobile phone
  • Limitations
  • Require costly data services (phones internet
    connection, SMS)
  • Require report and store sensitive personal
    information
  • Bottleneck, single point of failure, target of
    attack

22
Remarks
  • Propose, design, implement and evaluate the
    E-SmallTalker system which helps strangers
    initialize a conversation
  • Leveraged Bluetooth SDP to exchange these topics
    without establishing a connection
  • Customized service attributes to publish
    non-service related information.
  • Proposed a new iterative commonality discovery
    protocol based on Bloom filters that encodes
    topics to fit in SDP attributes to achieve a low
    false positive rate

23
Exemplary System IIE-Shadow
  • Concept
  • Application Scenario
  • Goals and Challenges
  • System Design
  • Implementation and Experiments
  • Remarks

23
24
Concept
  • Motivation
  • Importance of Face-to-Face Interaction
  • Prevalence of mobile phones
  • Distributed mobile phone-based local social
    networking system
  • Local profiles
  • Mobile phone based local social interaction tools

25
Application Scenario Conference
26
Goals and Challenges
  • Design Goals
  • Far-reaching and Unobtrusive
  • Privacy and Security
  • Auxiliary Support for Further Interactions
  • Broad Adoption
  • Challenges
  • Lack of Communication Support
  • Power and Computation Limitation
  • Non-pervasive Localization Service

27
Layered Publishing
  • Spatial Layering
  • WiFi SSID
  • at least 40-50 meters, 32 Bytes
  • Bluetooth Device (BTD) Name
  • 20 meters, 2k Bytes
  • Bluetooth Service (BTS) Name
  • 10 meters, 1k Bytes
  • Temporal Layering
  • For people being together long or repeatedly
  • Erasure Code

28
E-Shadow Publishing Procedure
29
Matching E-Shadow with its Owner
  • Intuitive Approach Localization
  • However, imprecision beyond 20-25 meters

30
Human Direction-driven Localization
  • Direction more important than distance
  • Human observation
  • A new range-free localization technique
  • RSSI comparison Less prone to errors
  • Space partitioning Tailored for direction
    decision

31
Walking Route and Localization
  • We allow users to walk a distance
  • Triangular route A-gtB-gtC in (a), for
    illustration purposes
  • Semi-octogonal route A-gtB-gtC-gtD-gtE in (c), more
    natural
  • Take measurements on turning points
  • Calculate the direction through RSSI comparison
    and space partitioning

32
Implementation
  • Information Publishing Module
  • Database
  • Generator
  • Buffers
  • Control Valve
  • Broadcasting Interfaces
  • Retrieval Matching Module
  • Receivers
  • Localization
  • Decoding Storage
  • Sensing Module
  • User Interface

33
Evaluations (1)-Time Energy
  • E-Shadow Collection Time
  • WiFi SSID 2 seconds
  • BTD 12-18 seconds
  • BTS 25-35 seconds
  • E-Shadow Power Consumption
  • 3 hours in full performance operation
  • gt12 hours in typical situation

34
Evaluations (2)-Localization
3 Outdoor Experiments Open field campus
2 Indoor Experiments Large classroom
35
Evaluation (3)-Simulations
Large-Scale Simulations Angle deviation CDFs
12 times of exemplary direction decisions
36
Related Work
  • Centralized mobile phones applications
  • Social Serendipity
  • Centralized, Bluetooth MAC and profile matching,
    SMS, strangers
  • Decentralized mobile phone applications
  • Nokia Sensor
  • Distributed, profile, Bluetooth / Wifi
    connection, existing friends
  • E-Smalltalker
  • Distributed, no Bluetooth / Wifi connection,
    strangers
  • Localization techniques for mobile phones
    applications
  • GPS
  • Virtual Compass
  • peer-based relative positioning system using
    Wi-Fi and Bluetooth radios
  • Limitations
  • Privacy compromise
  • Unable to capture the dynamics of surroundings
  • No mapping between electronic ID and human face
  • Localization techniques either not pervasive or
    not accurate for long range

36
37
Remarks
  • Propose, design, implement and evaluate the
    E-Shadow system which lubricates local social
    interactions
  • E-Shadow concept
  • Layered publishing to capture the dynamics of
    surroundings
  • Human-assisted matching that works for mapping
    E-Shadow with its owner in a fairly large
    distance
  • Implementing and evaluating E-Shadow on real
    world mobile phones

37
38
Exemplary System IIIP3-Coupon
  • Coupon Distribution
  • A Naïve Approach
  • Challenges
  • System Design
  • Implementation and Experiments
  • Remarks

38
39
Electronic Coupon Distribution
  • Electronic coupons
  • Similar to paper coupons
  • Can be stored on mobile phones
  • Two distribution methods
  • Downloading from Internet websites
  • Need to define target group
  • Limited coverage
  • Hard to maintain dynamic preferences lists on
    central databases
  • Peer to Peer Distribution
  • No special destination/target group
  • More coverage
  • More flexible user-maintained preferences list

39
40
A Naive Approach of Peer-to-Peer Coupon
Distribution
  • A store periodically broadcast the coupon
  • Users within broadcast range receive the coupon
  • User can decide whether to use, forward or
    discard the coupon
  • Users forward the coupon to others in physical
    proximity
  • Forwarders IDs are recorded in a dynamically
    expanding list
  • The coupon is used by some user
  • The store reward all users who have forwarded the
    coupon

40
41
However
  • Require manually establishing wireless
    connections
  • Cumbersome
  • Not prompt
  • Not possible for coupon forwarding among
    strangers
  • Require recording the entire forwarding path
  • Potential privacy leakage
  • Discourage users forwarding incentives

41
42
Challenge
  • How to design a prompt coupon distribution
    mechanism that
  • Incentivize coupon forwarder appropriately for
    keeping the coupons circulating
  • Preserve the privacy of coupon forwarders

42
43
P3-Coupon A Probabilistic Coupon Forwarding
Approach
  • Probabilistic sampling on forwarding path
  • Keep only one forwarder for each coupon NO
    privacy leakage
  • Probabilistically flip ownership at each hop
  • Accurate approximation of coupon rewards
  • plenty of chances of interpersonal encounters
  • Accurate bonus distribution with 50 coupons and
    5000 people
  • Adaptive to different promotion strategies
  • Flip-once model
  • Always-flip model
  • No manual connection establishment
  • Connectionless information exchange via Bluetooth
    SDP

43
44
System Architecture
  • Store Side
  • A central server for broadcasting and redeeming
    coupons
  • Client side
  • Coupon forwarding manager, coupon exchange,
    coupon data store, user interface

44
45
Probabilistic Forwarding Algorithm
  • Always-Flip Model
  • The coupon ownership keeps flipping with certain
    probability at each hop.
  • Good at assigning relative bonuses affected by
    the whole path lengths
  • E.g. the parent forwarder receives k times the
    bonus given to children forwarders
  • The flip probability can be calculated in advance
    by the store, once k is fixed, using the
    following formula

45
46
Probabilistic Forwarding Algorithm
  • Extension Flip-Once Model
  • Once flipped, a coupons ownership remain the
    same in a forwarding path.
  • Good at assigning absolute bonuses irrelevant of
    the number of following forwarders
  • E.g. hop 1 user gets 10, hop 2 user gets 5,
    etc.
  • The flip probability can be calculated in advance
    by the store using the following formula

46
47
Coupon Format
  • Coupon description
  • Product description
  • Discounts
  • Coupon issuer
  • Coupon code
  • Start/end date
  • Coupon forwarder information
  • The current owner
  • Digital signature
  • Prevent forging fraud coupons

47
48
Implementation
  • J2ME
  • about 17 java classes, 1390Kb jar file
  • On real phones
  • Samsung (SGH-i550), Nokia (N82, 6650, N71x)

48
49
Experiments
  • Experimental evaluations
  • Coupon forwarding time
  • Power consumption
  • Simulation evaluation
  • Number of Coupon holders vs. Time
  • Distribution saturation time vs. Number of Seeds
  • Coupon ownership distribution for probabilistic
    sampling
  • Deviation between theoretical and actual bonus
    (Always-Flip, Flip-Once)
  • Factors
  • Number of coupons
  • Number of users
  • Number of initial coupon holders

49
50
Experiment Results
  • Average coupon forwarding time is 33.52 seconds
  • Nokia N82 last 25 hours with P3-Coupon running in
    background
  • One coupon could be delivered to 5000 people
    within 32 hours
  • Very small deviation between theoretical and
    actual bonus distribution with 50 coupons
    circulating among 5000 people

50
51
Remarks
  • Propose, design, implement and evaluate the
    P3-Coupon system which helps prompt and privacy
    preserving coupon distribution
  • Probabilistic one-ownership coupon forwarding
    algorithm
  • Implement the system on various types of mobile
    phones
  • Extensive experiments and evaluations show that
    our approach accurately approximate the
    theoretical coupon distribution in which the
    whole forwarding path needs to be recorded
  • Practical for real-world deployment

51
52
Exemplary System IV Drunk Driving Detection
52
  • Motivation
  • Our Contributions
  • Detection Criteria
  • Our System
  • Related Work
  • Implementation and Evaluation
  • Remarks

53
Motivation
53
  • Crashes caused by alcohol-impaired driving pose a
    serious danger to the general public safety and
    health
  • 13,041 and 11,773 driving fatalities happened in
    2007 and 2008
  • 32 of the total fatalities in these two years
  • Drunk driving also imposes a heavy financial
    burden on the whole society
  • Annual cost of alcohol-related crashes totals
    more than 51 billion
  • Data from U.S. NHTSA (National Highway Traffic
    Safety Administration)
  • Data from U.S. CDC (Central of Disease Control)

54
Motivation
54
  • Detection of drunk driving so far still relies on
    visual observation by patrol officers
  • Drunk drivers usually make certain types of
    dangerous maneuvers
  • NHTSA researchers identify cues of typical drunk
    driving behavior
  • Visual observation is insufficient to prevent
    drunk driving
  • The number of patrol officers is far from enough
  • The guidelines are only descriptive and
    qualitative
  • Usually, it is too late when drunk drivers are
    stopped by officers
  • It is essential to develop systems actively
    monitoring drunk driving and to prevent accidents

55
Our Contributions
55
  • Propose utilizing mobile phones as a platform for
    active drunk driving detection system
  • Design a real-time algorithm for drunk driving
    detection system using mobile phones
  • Simple sensors required only
  • i.e., accelerometers and orientation sensors
  • Design and implement a mobile phone-based active
    drunk driving detection system
  • Reliable, Non-intrusive, Lightweight and power
    efficient, and No extra hardware and service cost

56
Cues for Drunk Driving Detection
56
  • Cues related to lane position maintenance
    problems
  • E.g., weaving, drifting, swerving and turning
    with a wide radius
  • Cues related to speed control problems
  • E.g., accelerating or decelerating suddenly, and
    braking erratically
  • Cues related to judgment and vigilance problems
  • E.g., driving with tires on lane marker, slow
    response to traffic signals

57
Drunk Driving Detection Criteria
57
  • Extract fundamental detection criteria from these
    cues
  • Capture the acceleration features
  • E.g., for the lane position maintenance problems

58
Drunk Driving Detection Criteria
58
  • Focus on the first two categories of cues
  • They correspond to higher probabilities of drunk
    driving
  • Map them into patterns of acceleration
  • Probability of drunk driving detection goes
    higher while the number of observed cues increases

59
Our System
59
60
Implementation
60
  • Develop the prototype system on Android G1 phone
    with accelerometer and orientation sensor
  • Implement the prototype in Java, with Eclipse and
    Android 1.6 SDK
  • The whole prototype system can be divided into
    five major components
  • ? User interface ? System configuration ?
    Monitoring daemon
  • ? Data processing ? Alert notification

61
Evaluation - Testing Data Collection
61
  • Test data
  • 72 sets of data with simulated drunk driving
    related behaviors
  • Weaving, swerving, turning with a wide radius
  • Changing speed erratically (accelerating or
    decelerating)
  • 22 sets of data for regular driving
  • Each one for 5 to 10 minutes
  • Mobile phone positions in the vehicle

62
Evaluation - Detection Performance
62
  • Study the accuracy of detecting drunk driving
    related behaviors
  • In terms of false negative and false positive
  • Study performance in the special case, such as
    the phone slides in the vehicle during driving
  • Slides has obvious impacts on detection accuracy
  • May add additional calibration procedure to solve
    it (future work)

63
Evaluation Energy Efficiency
63
  • Curves of battery level states during mobile
    phone running
  • Phone runs without drunk driving detection system
  • Monitoring daemon of system keeps running,
    sensing and doing the pattern matching on the
    monitoring results

64
Related Work
64
  • Driver vigilance monitoring and driver fatigue
    prevention
  • Monitoring the visual cues of drivers to detect
    fatigue in driving
  • Installed cameras just in front of drivers are
    potential safety hazard
  • Monitoring through vehicle-human interface
  • Capture fatigued or drunk driving through
    monitoring interactions
  • Low compatibility, vehicles need to couple with
    auxiliary add-ons
  • Detect abnormal driving through GPS and
    acceleration data
  • Pattern matching with GPS and acceleration data
  • However, GPS data are not always available

65
Remarks
65
  • First to propose utilizing mobile phones as a
    platform for developing active drunk driving
    detection system
  • Design and implement an efficient detection
    system based on mobile phone platforms
  • Experimental results show our system achieves
    good detection performance and power efficiency
  • In the future work, to improve the system with
    additional calibration procedure and by
    integrating all available sensing data on a
    mobile phone such as camera image

66
Exemplary System V Stealthy Video Capturer
  • Background
  • SVC Overview
  • Challenges
  • Our Approaches
  • Experimental Evaluations
  • Remarks

67
Background
  • More and more private information is entrusted to
    our friend, the 3G Smartphone, which is getting
    more and more powerful in performance and
    diversified in functionality.

68
SVC Overview
  • Almost every 3G Smartphone is equipped with a
    camera and the wireless options, such as 3G
    networks, BlueTooth, WiFi or IrDA.
  • These wireless connections are good enough to
    handle certain types of video transmission.
  • We turn 3G Smartphones into an online stealthy
    video-recorder.

69
System Architecture
70
Challenges
  • Stealthily install SVC into 3G Smartphones
  • Windows Hiding
  • Infection Method
  • Collect the video information from 3G Smartphones
  • DirectShow Controls
  • Data Compressing
  • Send the video file to the SVC intender
  • File Sending

71
Infection Method
  • To embed SVC in a 3G Smartphone is called a
    infection process.
  • We employ Trojan horse for downloads as the
    infection approach.
  • Our experimental SVC is hidden in the game of
    tic-tac-toe that we develop in Windows Mobile
    environment.

72
The Scenario of Tic-Tac-Toe
73
Triggering Schemes
  • Triggering Algorithm is designed to determine
    when to turn on the video capture process and
    send the captured video to make SVC stealthier
    and get more useful information.
  • Three scenarios are under consideration.
  • The first scenario is tracking.
  • The second scenario is related with political or
    business espionage.
  • The third scenario is a hybrid one, where SVC is
    used for much diversified everyday purposes.

74
Applications
  • Suspects tracking
  • Kids care

75
Kids tracking
76
Implementation
77
Experimental EvaluationsPower Consumption
  • Power curve

78
Experimental EvaluationsCPU and Memory Usage
  • CPU and Memory

79
Remarks
  • The initial study exploited from SVC will draw
    wide attentions on 3G Smartphones privacy
    protection and open a new horizon on 3G
    Smartphones security research and applications.
  • We are currently investigating the modeling of
    smart spyware from the study of spear and
    shield.

80
A Summary
81
Future Research Directions
  • Smartphone-based Systems and Networking
  • Mobile social networking, e-commerce, e-health,
    safety monitoring etc.
  • Easy to start and exciting but too many
    competitors, lack of scientific depth
  • Smartphone Core Improvement
  • Multitasking, power management, efficient local
    communication protocol, accurate localization,
    security/privacy protection
  • Deep but hard to start

82
Final Remarks
  • Smartphones have brought significant impacts to
    our daily life.
  • We present five exemplary systems on mobile
    social networking, e-commerce, e-health and
    safety.
  • Research and development on smartphones will be
    hot.

82
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