Social SonarControl Your World...Before Your Friends Do!

Presentation Outline

What Is Social Sonar?

Requirement Specifications

Functional Requirements

Non-Functional Requirements

The Application Architecture

The State Diagram

The Challenges of Our Design

The Application Architecture:

Main Object Identification

The UML Diagram

Presentation Review

Marc

The Problem Statement

At a glance:

Provide entertainment to users

Upon further inspection:

How to predict human movement

How will we do it?

Gather traces from users

Game will act as an incentive to provide the trace

Why is it important:

If you can predict human movement, many opportunities unfold

Michael

In ad-hoc routing...Implement efficient routingIn transportation...Reduce congestionSave fuelFor Advertising...Better ad targeting

Better product placement

Social Sonar: What Is It?

Social Gaming Application

Entertains users with interactive game play

Attack peers

Defend yourself

Collect in-game resources

Records location with sampling (discussed later on)

Gathers location traces for research

Michael

Social Sonar: Some Concept Art

Michael

Are There Any Existing Solutions?Cell phone applications

NFC based proximity gaming for the Blackberry

Geo-proximity alarm

Tap Tap War

Google’s Ingress; a mobile reality game [Hanke]

RFID tags to recognize patient/ medicine information.

Some frameworks

JCAF; the Java Context Awareness Framework [Bardram]

Qualcomm's Gimbal

Sathvik

What Services Will We Provide

Location discovery service

People discovery service [An, Wang]

Infrastructure service for research

Context aware services [Bardram]

Sathvik

Geo-fencing Interest sensing An AWARE framework [Bardram]

Requirement Specifications:Functional RequirementsMust find enemies and friends:

Requires Google Maps API to plot users’ locations and set a vision radius

Must seamlessly detect other users around the active user

Must house a database of resources and use them for later purposes such as building fortresses or houses to defend a location

Must publish updates to the user in a non-invasive manner:

Toast messages for notifications

Akshita

Requirement Specifications:Non-Functional RequirementsAvailability:

All times when in range of WiFi

Security concerns

Resolution, screen form factors

Visual aesthetics

Support for multiple channels: WiFi, 3G. The application will prefer WiFi

Efficiency:

Ensure less battery consumption by minimizing GPS usage

Akshita

Use Case Diagrams:Menu Screen

Use Case Diagrams:Game Screen

Akshita

Privacy and Security:User LocationLocation collection Enable/DisableUser/Phone IdentityAndroid_ID (Settings.Secure.ANDROID_ID)Android 2.2 and laterProtects User AnonymityNo setupWeaknessesUser could root phone and change Android_IDUsing virtual box, a single person could make a an army

Some Challenges and Our SolutionsHuman Movement Prediction:

Location prediction algorithm and map matching [Lou]

UTDOA [Yi-Bing Lin, Chien-Chun Huang-Fu]

Sampling rate selection

Aggregation and distribution of location information:

Store location on central server database

Easily query for users and game elements in a local area

Weakness:

Devices cannot directly communicate with each other

Server must provide data to each deviceYi Che & Michael

The Algorithms:Location-Prediction

Our algorithm:

Is not used immediately

Not reliable for consistent use

Allows us to “fill” gaps and “cheat”

Influences from MANET-LPBR [Meghanathan]

The concept of coordinate windows

LastLastKnown Known

LocationLocation

Stability Stability ThresholdThreshold

Current Current TimeTime

Last Last FineFine Update TimeUpdate Time

Sampling ThresholdSampling Threshold

Time

Last Last PredictionPrediction

Stability Stability ThresholdThreshold

LastLastPredictedPredicted LocationLocation

Last Last PredictionPrediction

Last Last FineFine Update TimeUpdate Time

LastLastPredictedPredicted LocationLocation

AnalyzeAnalyze LocationLocation

PredictionsPredictions

Stability Stability ThresholdThreshold

......

Demonstration:Location-Prediction

Algorithm

Marc

Our Design RationaleSampling rate:

Fair balance between accuracy and power consumption

User can always switch to “intense mode”

Location prediction algorithm:

Allows us to “cheat” when obtaining location information

Limit the user’s field of vision:

Fits the theme of our game, and adds an element of balance

Sathvik

Application Architecture:The State Diagram

MAIN_MENU

PLAYING

PAUSED

The State Diagram:The Diagram

The State Diagram:The Main States

MAIN_MENUMAIN_MENU

Presents the user Presents the user with the main with the main

utility options of utility options of the gamethe game

This is the This is the firstfirst state of the gamestate of the game

PLAYINGPLAYING

The user is actively The user is actively playing the gameplaying the game

This is the This is the secondsecond state of the gamestate of the game

PAUSEDPAUSED

The user was The user was playing the game, playing the game, however their play however their play

has been has been interruptedinterrupted

This is the This is the thirdthird state of the gamestate of the game

Yi Che

Application Architecture:Main Object Identification

Marc

MainMenuMainMenu

Monitors user Monitors user input, instantiates input, instantiates correct Activity.correct Activity.

Main entry point Main entry point for the application.for the application.

GameManagerGameManager

Ensures the proper Ensures the proper maintenance of the maintenance of the

game controller.game controller.

SocialSonarSocialSonar

Maintains the Maintains the render thread, and render thread, and

game logic.game logic.

RenderThreadRenderThread

Redraws the Redraws the screen and screen and

updates game updates game asynchronously.asynchronously.

LocationManagerLocationManager

Provides consistent Provides consistent and accurate and accurate

location location information.information.

Application Architecture:The UML Diagram

Marc

GameManager

RenderThread

LocationManager

MainMenu

SocialSonar

Presentation Review

Marc

What Is Social Sonar?

Requirement Specifications

Functional Requirements

Non-Functional Requirements

The Application Architecture

The State Diagram

The Challenges of Our Design

The Application Architecture:

The use-case diagram

Main Object Identification

The UML Diagram

Presentation Review

BibliographyKumar, Udayan. iTrust.  Ahmed Helmy. 2012. Application. 7 Mar 2013. <http://128.227.176.22:8182/iTrust.html>.

Bill Schilit, Norman Adams, Roy Want. “Context Aware Computing Applications”

http://graphics.cs.columbia.edu/courses/mobwear/resources/schilit-mcsa94.pdf

Perez, Sarah. "Intelligent, Context-Aware Personal Assistant App “Friday” Makes Its Public Debut."TechCrunch. 12 Jul 2012: n. page. Web. 7 Mar. 2013.

* Stemm, Mark, Paul Gauthier, Daishi Harada, and Randy Katz. "Reducing Power Consumption of Network Interfaces in Hand-Held Devices." CiteSeerX. Berkeley, n.d. Web. 18 Feb 2013. <http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.39.8384>.

Agarwal, Yuvraj, Steven Hodges, Ranveer Chandra, et al.Augmenting Network Interfaces to Reduce PC Energy Usage. San Diego: 2009.

Sohan, Ripduman, Andrew Moore, et al, and Andrew Rice.Characterizing 10 Gbps Network Interface Energy Consumption. Cambridge: 2010.

Lou, Yin, Chengyang Zhang, Yu Zheng, et al. "Map-Matching for Low-Sampling-Rate GPS Trajectories.". Houston: Microsoft Research, 2010. Web. 4 Apr. 2013. <http://research.microsoft.com/pubs/105051/Map-Matching for Low-Sampling-Rate GPS Trajectories-cameraReady.pdf>.

* Nilson, Martin, and Laura Feeney. Investigating the Energy Consumption of a Wireless Network Interface in an Ad Hoc Networking Environment. 2000.Jacob E. Bardram. The Java Context Awareness Framework (JCAF) – A Service Infrastructure and Programming Framework for Context-Aware Applications. 2005.Xueli An, Jing Wang. OPT – Online Person Tracking System for Context-awareness in Wireless Personal Network (Demo). 2006.Ralph Löwe, Peter Mandl, Michael Weber. Context Directory: A Context-Aware Service for Mobile Context-Aware Computing Applications by the Example of Google Android. 2012.Yi-Bing Lin, Chien-Chun Huang-Fu, Predicting Human Movement based on Telecom's Handoff in Mobile Networks. http://liny.csie.nctu.edu.tw/document/tmc11_PHM.pdfHanke, John . "Google Launches Ingress, a Worldwide Mobile Alternate Reality Game." allthingsd. (2012): n. page. Web. 28 Feb. 2013. <http://allthingsd.com/20121115/google-launches-ingress-a-worldwide-mobile-alternate-reality-game/>.

Meghanathan , N. "Location Prediction Based Routing Protocol for Mobile Ad Hoc Networks.". Jackson: Dept. of Comput. Sci., Jackson State Univ., 2008. Print. <http://ieeexplore.ieee.org.lp.hscl.ufl.edu/stamp/stamp.jsp?tp=&arnumber=4697891>.

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