System and Solutions for Mobile Pervasive Computing Environments Tutors: Prof. Romano Fantacci, Ing. Laura Pierucci, Prof. Imrich Chlamtac PhD final exam Firenze, 8 th 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

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

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 Scenarios ITS - scenario 1: Mobile Nodes querying a large WSN (cars looking for a free parking) With the absence of a central server Need for new routing framework to handle a WSN with a mobile sink ITS - scenario 2: Mobile nodes querying gateway nodes Exchanging information on the fly Need for new data management techniques for handling large amount of volatile data

ITS - scenario 1:

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

With the absence of a central server

Need for new routing framework to handle a WSN with a mobile sink

ITS - scenario 2:

Mobile nodes querying gateway nodes

Exchanging information on the fly

Need for new data management techniques for handling large amount of volatile data

Application Scenarios Mobile Social Networking Nodes interact among them on the basis of users’ profiles and interests Groups of friends get created in a localized way In particular we deal with: A real implementation for smartphone Social analysis deriving from the use of this mobile service in a real environment Routing algorithm based on degree of friendship Service evolution driven by mobility

Mobile Social Networking

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

Groups of friends get created in a localized way

In particular we deal with:

A real implementation for smartphone

Social analysis deriving from the use of this mobile service in a real environment

Routing algorithm based on degree of friendship

Service 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 car Sensing nodes e.g. presence sensors Gateway nodes e.g interface nodes for the MS NOT providing continuous connection to the MS

Mobile Sink querying a WSN

Representing cars looking for a parking place

System architecture specifically tailored for ITS scenarios:

MS e.g. a car

Sensing nodes e.g. presence sensors

Gateway 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

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

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 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

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 MN1 MN2 MN4 Back Haul Connection MN5 MN3 MN 7 MN 6 Node Movement Opportunistic Information Exchange BlueTooth Module WiFi Module Mobile Node MN

State of the Art Opportunistic networking has been deeply investigated from a theoretical point of view: Bionets EU project Haggle EU project Several 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

Opportunistic networking has been deeply investigated from a theoretical point of view:

Bionets EU project

Haggle EU project

Several 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

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 exchange Sensor data reading (images) and exchange Contact exchange to trace contact evolution Ring-tones exchange

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 exchange

Sensor data reading (images) and exchange

Contact exchange to trace contact evolution

Ring-tones exchange

U-Hopper System Architecture Profile 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. Content Manager (CM): stores 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.

Profile 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.

Content Manager (CM):

stores 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 Interest Manager (IM): merges the user profile and the requirements originating from the hosted services, into interests , which are a description of the data requested by the user. Content Acquisition (CA): stores/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.

Interest Manager (IM):

merges the user profile and the requirements originating from the hosted services, into interests , which are a description of the data requested by the user.

Content Acquisition (CA):

stores/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 SERVER CLIENT Retreive DATA Retreive DATA Store DATA Store DATA Open Connection Send INTERESTS Send DATA Send INTERESTS Send DATA Close Connection

U-Hopper in pills… The middleware: J2ME version + J2SE version Leverage on Bluetooth for communication Persistency: RMS on J2ME and MySQL Db on J2SE devices Used as a pure middleware Multiple applications with U-Hopper P2P data exchange (ring-tones + advertisement) Business cards exchange Sensor data reading and exchange Others (not yet implemented…)

The middleware:

J2ME version + J2SE version

Leverage on Bluetooth for communication

Persistency: RMS on J2ME and MySQL Db on J2SE devices

Used as a pure middleware

Multiple applications with U-Hopper

P2P data exchange (ring-tones + advertisement)

Business cards exchange

Sensor data reading and exchange

Others (not yet implemented…)

U-Hopper application: mobile P2P Opportunistic Information Exchange BlueTooth Module Mobile Node MN Interests: U2 / Walk-On MN2 MN1 Interests: U2 / Walk-On

MSN: an analysis Office environment test bed: Interests collected through questionnaires Contact pattern registered using U-hopper 21 participants for a 3 weeks period

Office environment test bed:

Interests collected through questionnaires

Contact pattern registered using U-hopper

21 participants for a 3 weeks period

MSN: The contacts pattern Graph-based representation of the network of contacts An edge exists between any 2 vertexes if contact time is at least 30 minutes per day.

Graph-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 network According to users’ interests On three different formats: text, music video Packets have a varying TTL

Nodes infection ratio has been evaluated:

Injecting packets in the network

According to users’ interests

On three different formats: text, music video

Packets have a varying TTL

MSN: introducing the social dimension Questionnaires have been distributed: To understand the real interests of users To map networking interaction with real interests Interests have been added to users profiles A java simulator has been developed: With real contact traces Mapping them with real interests We have defined a metric to understand impact of sociality into opportunistic networking

Questionnaires have been distributed:

To understand the real interests of users

To map networking interaction with real interests

Interests have been added to users profiles

A java simulator has been developed:

With real contact traces

Mapping them with real interests

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

MSN: users affinity Affinity : Preferences are: The resulting graphs with affinity>0.75 =>

Affinity :

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

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 results We 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?

We 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 evolution Opportunistic networking is used to have a service evolving in a distributed way Users exchange services parameters The service evolve in such a way that user perception of the service increases We defined a mathematical framework to do that The example used is T9 service where we showed dictionary evolution to better fit users’ request

Opportunistic networking is used to have a service evolving in a distributed way

Users exchange services parameters

The service evolve in such a way that user perception of the service increases

We defined a mathematical framework to do that

The 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

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 ?” Opportunistic Information Exchange BlueTooth Module Mobile Node MN Bondone, falaise Has the words: Bondone,falaise Fitness is high MN5 Missing word: Bondone,falaise Fitness really low MN3

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

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: david.tacconi@gmail.com Web: www.davidtacconi.com

Thank You!!!

David Tacconi

Email: david.tacconi@gmail.com

Web: www.davidtacconi.com