The MobiSoC Middleware The MobiSoC Middleware for Mobile Social for Mobile Social

ComputingComputing

Cristian BorceaCristian Borcea, Ankur Gupta, , Ankur Gupta, Achir Kalra, Quentin Jones, Liviu Achir Kalra, Quentin Jones, Liviu

Iftode*Iftode*Department of Computer ScienceDepartment of Computer Science

New Jersey Institute of TechnologyNew Jersey Institute of Technology

*Rutgers University*Rutgers University

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Social Computing in the InternetSocial Computing in the Internet

Social networking applications that improve Social networking applications that improve social connectivity on-linesocial connectivity on-line– Stay in touch with friendsStay in touch with friends– Make new friendsMake new friends– Find out information about events and placesFind out information about events and places

LinkedInLinkedInMyspaceMyspace FacebookFacebook

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Shift from Physical Communities Shift from Physical Communities to Virtual Communitiesto Virtual Communities

Leads to missed social opportunitiesLeads to missed social opportunities– People not aware of their neighborhoodsPeople not aware of their neighborhoods– Example: don’t know neighbors with common interests Example: don’t know neighbors with common interests

or nearby eventsor nearby events Inter-personal affinities can be leveraged in Inter-personal affinities can be leveraged in

stronger social ties in physical communitiesstronger social ties in physical communities– People who share common places can easily meet and People who share common places can easily meet and

talktalk Is there any way to get the best of both worlds?Is there any way to get the best of both worlds?

Merge the benefits of social computing and physical Merge the benefits of social computing and physical communities?communities?

• 200-400 MHz processors200-400 MHz processors• 64-128 MB RAM64-128 MB RAM• GSM, WiFi, BluetoothGSM, WiFi, Bluetooth• Camera, keyboardCamera, keyboard• Symbian, Windows Mobile, LinuxSymbian, Windows Mobile, Linux• Java, C++, C#Java, C++, C#

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Mobile Social ComputingMobile Social Computing

Social computing Social computing anytime, anywhereanytime, anywhere New applications will benefit from New applications will benefit from real-time real-time

location and place informationlocation and place information Smart phones are the ideal devicesSmart phones are the ideal devices

– Always with usAlways with us– Internet-enabledInternet-enabled– Locatable (GPS or other systems)Locatable (GPS or other systems)

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Are People Willing to Share their Are People Willing to Share their Location?Location?

Yes, if they benefit from thatYes, if they benefit from that Study with 500+ people in Manhattan over 3 weeksStudy with 500+ people in Manhattan over 3 weeks

– 84% willing to share location to compute place crowding84% willing to share location to compute place crowding– 77% willing to share their location data with others in public or 77% willing to share their location data with others in public or

semi-public placessemi-public places– 57% would like to know information about other people57% would like to know information about other people

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Mobile Social Computing Mobile Social Computing Applications (MSCA)Applications (MSCA)

People-centricPeople-centric– Are any of my friends in the cafeteria now?Are any of my friends in the cafeteria now?

– Is there anybody nearby with a common Is there anybody nearby with a common background who would like to play tennis?background who would like to play tennis?

Place-centricPlace-centric– How crowded is the cafeteria now?How crowded is the cafeteria now?

– Which are the places where CS students hang out?Which are the places where CS students hang out?

How to program MSCA?How to program MSCA? Challenges: capturing the dynamic relations Challenges: capturing the dynamic relations

between people and places, location systems, between people and places, location systems, privacy, power privacy, power

OutlineOutline MotivationMotivation MobiSoC MiddlewareMobiSoC Middleware ApplicationsApplications

– Clarissa: people-centric MSCAClarissa: people-centric MSCA

– Tranzact: place-centric MSCATranzact: place-centric MSCA

Implementation & experimental resultsImplementation & experimental results ConclusionsConclusions

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MobiSoC MiddlewareMobiSoC Middleware Common platform for capturing, managing, and Common platform for capturing, managing, and

sharing the sharing the social state of a physical communitysocial state of a physical community Discovers emergent geo-social patterns and Discovers emergent geo-social patterns and

uses them to augment the social stateuses them to augment the social state

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MobiSoC ArchitectureMobiSoC Architecture

Learning Emergent Geo-Social Learning Emergent Geo-Social Patterns Example: GPIPatterns Example: GPI

GPI – algorithm that identifies previously GPI – algorithm that identifies previously unknown social groups and their associated unknown social groups and their associated placesplaces– Fits into the people-place affinity learning moduleFits into the people-place affinity learning module

Clusters user mobility traces across time and Clusters user mobility traces across time and spacespace

Its results canIts results can– Enhance user profiles and social networks using Enhance user profiles and social networks using

newly discovered group membershipsnewly discovered group memberships

– Enhance place semantics using group meeting times Enhance place semantics using group meeting times and profiles of group membersand profiles of group members 1010

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Location SystemLocation System

Hardware-based location systems not feasible Hardware-based location systems not feasible – GPS doesn’t work indoorsGPS doesn’t work indoors

– Deploying RF-receivers to measure the signals of Deploying RF-receivers to measure the signals of mobiles is expensive and not practical for large mobiles is expensive and not practical for large placesplaces

The user has no control over her location data!The user has no control over her location data!

Software-based Software-based location systems that run on location systems that run on mobile devices preferablemobile devices preferable– Use signal strength and known location of WiFi Use signal strength and known location of WiFi

access points or cellular towersaccess points or cellular towers

– Allow users to decide when to share their locationAllow users to decide when to share their location

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Mobile Distributed System Mobile Distributed System ArchitectureArchitecture

MSCA split between thin clients running on mobiles MSCA split between thin clients running on mobiles and services running on serversand services running on servers

MSCA clients communicate synchronously with the MSCA clients communicate synchronously with the services and receive asynchronous events from services and receive asynchronous events from MobiSoCMobiSoC

AdvantagesAdvantages Faster executionFaster execution Energy efficiencyEnergy efficiency Improved trustImproved trust

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Clarissa: Location-enhanced Clarissa: Location-enhanced mobile social matchingmobile social matching

Match Alert

MatchType=Hangout

Time: 1-3PMCo-Location:

required

MatchType=Hangout

Time: 2-4PMCo-Location:

required

Match Alert

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Tranzact: Place-based ad hoc Tranzact: Place-based ad hoc social collaborationsocial collaboration

What’s on th

e

menu?

Cafeteria

Chicken

teriyaki

Hungry

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MobiSoC ImplementationMobiSoC Implementation

Runs on trusted serversRuns on trusted servers Service oriented architecture over Apache TomcatService oriented architecture over Apache Tomcat

– Core services written in JAVACore services written in JAVA

– API is exposed to MSCA services using KSOAPAPI is exposed to MSCA services using KSOAP KSOAP is J2ME compatible, hence can be used to communicate KSOAP is J2ME compatible, hence can be used to communicate

with clientswith clients

Client applications developed using J2ME on WiFi-Client applications developed using J2ME on WiFi-

enabled Windows-based smart phonesenabled Windows-based smart phones– Clarissa: http://apps.facebook.com/matching/ Clarissa: http://apps.facebook.com/matching/

Location engine: modified version of Intel’s Location engine: modified version of Intel’s

Placelab Placelab – At least 3 WiFi access points visible in most NJIT placesAt least 3 WiFi access points visible in most NJIT places– Accuracy 10-15 metersAccuracy 10-15 meters

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Location Engine Power Location Engine Power ConsumptionConsumption

Trade-off between frequent location updates Trade-off between frequent location updates for synchronous awareness and rare updates for synchronous awareness and rare updates to save powerto save power

GPI ResultsGPI Results

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Experimental resultsExperimental results– Mobility traces from 20 users carrying smart phones over one Mobility traces from 20 users carrying smart phones over one

month periodmonth period– Identified all groups and places (place accuracy < 10 meters)Identified all groups and places (place accuracy < 10 meters)

Simulations for larger scaleSimulations for larger scale– Identified over 96% of members, when meeting attendance Identified over 96% of members, when meeting attendance

frequency at least 50% frequency at least 50% – Less than 1% false positivesLess than 1% false positives

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ConclusionsConclusions Mobile social computing applications can be Mobile social computing applications can be

deployed in real-life todaydeployed in real-life today MobiSoC manages community social state MobiSoC manages community social state

– Discovers emergent patterns from social interactionsDiscovers emergent patterns from social interactions Improves people and place profiles using these patternsImproves people and place profiles using these patterns

– Provides support for rapid application developmentProvides support for rapid application development

Distributed system architecture based on MobiSoC Distributed system architecture based on MobiSoC addresses efficiency, power, and trust issuesaddresses efficiency, power, and trust issues

SmartCampus: large scale mobile social computing SmartCampus: large scale mobile social computing test-bed at NJITtest-bed at NJIT– Test mobile social computing applications with 200+ Test mobile social computing applications with 200+

users carrying smart phones across the campus this users carrying smart phones across the campus this spring spring

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Thank you!Thank you!

Work sponsored by the NSF grants CNS-Work sponsored by the NSF grants CNS-0454081, IIS-0534520, CNS-0520033, and 0454081, IIS-0534520, CNS-0520033, and

CNS-0520123CNS-0520123

http://www.cs.njit.edu/~borcea/http://www.cs.njit.edu/~borcea/