Tacconi PhD final exam

Dottorato di ricerca in Ingegneria informatica, Multimedialita’ e Telecomunicazioni, XXI cicloDottorato di ricerca in Ingegneria informatica, Multimedialita’ e Telecomunicazioni, XXI ciclo David Tacconi David Tacconi

Systems and Solutions for Mobile Pervasive Computing EnvironmentsSystems and Solutions for Mobile Pervasive Computing Environments

Firenze, 8th April 2009David Tacconi

System and Solutionsfor Mobile Pervasive Computing Environments

Tutors: Prof. Romano Fantacci, Ing. Laura Pierucci, Prof. Imrich Chlamtac

PhD final examFirenze, 8th April, 2009

David Tacconi




Outline Introduction System Architecture Applications and challenges Intelligent Transportation System (ITS) Application

scenarios: Routing issues Data management issues

Mobile Social Network (MSN) application scenario: Real implementation Social analysis Routing framework Service evolution

Conclusions




Introduction Mobile Computing:

the possibility of being able to use a computing device even when being mobile and therefore changing

location Pervasive Computing:

a halo of embedded devices immersed into reality able to provide information to a human or to another device about the environments he is immersed in

Mobile Pervasive Computing: Devices moving around Looking for information from sensing devices Not necessarily connected to a central server Opportunistically exchanging information on the fly




System Architecture




Application ScenariosITS - scenario 1:

Mobile Nodes querying a large WSN (cars looking for a free parking)

With the absence of a central serverNeed for new routing framework to handle a

WSN with a mobile sinkITS - scenario 2:

Mobile nodes querying gateway nodesExchanging information on the flyNeed for new data management techniques for

handling large amount of volatile data




Application ScenariosMobile Social Networking

Nodes interact among them on the basis of users’ profiles and interests

Groups of friends get created in a localized wayIn particular we deal with:

A real implementation for smartphoneSocial analysis deriving from the use of this

mobile service in a real environmentRouting algorithm based on degree of

friendshipService evolution driven by mobility




ITS: mobile sinks querying a large WSN Mobile Sink querying a WSN

Representing cars looking for a parking place System architecture specifically tailored for ITS

scenarios:MS e.g. a carSensing nodes e.g. presence sensorsGateway nodes e.g interface nodes for the MS NOT

providing continuous connection to the MS




ITS: the routing framework Geographic forwarding MS experiences

frequent disconnections Deadlock management Mobility prediction Load balancing

strategies Delay aware routing Energy aware routing




ITS: simulation results Simulations performed in Omnet++ Network dimensioning Comparative study to evaluate load balancing techniques Time to first node failure evaluated varying mobility and # of nodes




ITS: Data management issues Data management and

compression scheme : Are needed in context aware

applications for mobile nodes or in ITS applications

Largely deployed WSN WSN can be considered as a

Sensor Map (Image) Local information has to be

more precise while only coarse approximation can be kept for further information

Wavelet compression and data management scheme can help

Application scenario is described in figure




Data management for large WSN:Simulation results

Simulation conducted in Omnet++ Large number of sensors (128x128 sensor grid) Variable number of nodes (100 – 600) Variable mobility pattern Distortion between real sensor image and stored sensor image is measured




Mobile Social Network Scenario: DTN

MN5 MN5

MN3MN 7

MN1

MN2

MN4

MN 6

Node Movement

Opportunistic Information Exchange

BlueTooth Module

WiFi Module

Mobile NodeMN

Back Haul Connection




State of the ArtOpportunistic networking has been deeply

investigated from a theoretical point of view:Bionets EU projectHaggle EU projectSeveral conferences and research intiatives

Only few real developments have been proposed:To understand networking performance of the

implemented protocols To investigate social aspects related to

proximity communications




Motivation for a real implementation Mobile Phones are used:

For Voice/video calls As Messaging device As MP3 player As Cameras To surf the web

What if users could share data: Using their mobile phones Leveraging on proximity communications rather than relying on a

backhaul connection Simply editing their preference and search options every once in a

while Putting the mobile phone in the pocket and then

TRANSPARENTLY exchanging information when meeting other users, according to personal interests




A middleware for pervasive environment U-Hopper:

User centric Heterogeneous Opportunistic Middleware

provides users with ‘missing’ functionalities Is Java + Bluetooth based Can be used on every phone with J2ME support or

Linux J2SE laptop Supported applications (december 2008):

Profile editing (limited)Advertisement and Business card exchangeSensor data reading (images) and exchangeContact exchange to trace contact evolutionRing-tones exchange




U-Hopper System ArchitectureProfile Manager (PM): handles the creation/update/deletion of the user profile. Such profile can be explicitly created by the user, and dynamically updated on the basis of users daily activities.

Service Container (SC):is the environment where context-aware services are executed. Such Container provides seamless access to resources such as content storage, opportunistic data retrieval, etc.

oContent Manager (CM): ostores permanently any data item considered as relevant to the Interest Manager. It is accessed by the CA for storing any incoming data, and by the SC for augmenting context-aware services.




U-Hopper System Architecture

oInterest Manager (IM): omerges the user profile and the requirements originating from the hosted services, into interests, which are a description of the data requested by the user.

oContent Acquisition (CA): ostores/update/removes data according to user preferences and service requirements.

Opportunistic Communication (OC) Unit this engine transparently exchanges data among mobile nodes encountering on the move. Also it is in charge of reading nearby sensors. Such unit periodically searches available data sources, and takes care of all the necessary steps for gathering such information.




Information exchange

SERVERCLIENTOpen Connection

Send INTERESTS

Send DATARetreive DATA

Send INTERESTS

Retreive DATASend DATA

Close Connection

Store DATA

Store DATA




U-Hopper in pills… The middleware:

J2ME version + J2SE versionLeverage on Bluetooth for communicationPersistency: RMS on J2ME and MySQL Db on J2SE

devicesUsed as a pure middleware

Multiple applications with U-HopperP2P data exchange (ring-tones + advertisement)Business cards exchangeSensor data reading and exchangeOthers (not yet implemented…)




U-Hopper application: mobile P2P

MN2


BlueTooth Module

Mobile NodeMN

Interests: U2 / Walk-On

MN1

Interests: U2 / Walk-On




MSN: an analysis Office environment test bed:

Interests collected through questionnairesContact pattern registered using U-hopper21 participants for a 3 weeks period




MSN: The contacts patternGraph-based representation of the network

of contacts An edge exists between any 2 vertexes if

contact time is at least 30 minutes per day.




MSN: emulation results Nodes infection ratio has been evaluated:

Injecting packets in the networkAccording to users’ interestsOn three different formats: text, music videoPackets have a varying TTL




MSN: introducing the social dimensionQuestionnaires have been distributed:

To understand the real interests of usersTo map networking interaction with real

interestsInterests have been added to users profilesA java simulator has been developed:

With real contact tracesMapping them with real interests

We have defined a metric to understand impact of sociality into opportunistic networking




MSN: users affinityAffinity :

Preferences are:

The resulting graphs

with affinity>0.75 =>




MSN: friendship based routing Users exchange data

if their interests match enough

Interests are weighted according to a predefined # of friends K that have those interests

K-nearest friends are selected for info diffusion




MSN: friendship routing resultsWe evaluated:

Network Infection Rate i.e. how much messages are propagated in the network?

Utility: upon receiving a message, how much does it much user’s interests?




MSN: the T9 service evolutionOpportunistic networking is used to have a

service evolving in a distributed wayUsers exchange services parameters The service evolve in such a way that user

perception of the service increasesWe defined a mathematical framework to

do thatThe example used is T9 service where we

showed dictionary evolution to better fit users’ request




MSN: the T9 service evolution Fitness:

is defined as the satisfaction a user experiences when using a service

The higher the fitness the higher the degree of satisfaction In the T9 example:

User fitness is low if he has to search to many time for a word Fitness is high if all words come at first

Mobile opportunistic networking could help If I meet a user with high fitness he sends me his dictionary My dictionary enlarges and my fitness increases

We have defined an analytical framework and a simulation framework: to understand how the T9 service could evolve with mobile

interactions The impact of mobility for increasing users’ fitness




Missing word: Bondone, falaise

MSN: T9 distributed evolution

TARGET TEXT: “Shall we meet tonight on the Bondone at 8.00 pm on the falaise?”


BlueTooth Module

Mobile NodeMN

MN5

Missing word: Bondone,falaise

Fitness really low

Bondone, falaise

MN3

Has the words: Bondone,falaise

Fitness is high




Conclusion In this work, a system architecture:

has been defined, designed and implemented to work in mobile pervasive environments assuming no centralized connections

The designed system architecture:solve the ITS scenario issues (routing and data

management)deals with the MSN challenges

Challenges of such scenarios have been faced and overcome from:an analytical point of view through an extensive simulation analysis implementing a prototype and applying it to real world




Thank You!!!

David Tacconi

Email: [email protected]: www.davidtacconi.com

Technology

Tacconi PhD final exam