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Tacconi PhD final exam


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Final presentation of the thesis work entitled Systems and solutions for mobile pervasive computing environments

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Tacconi PhD final exam

  1. 1. 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
  2. 2. Outline <ul><li>Introduction </li></ul><ul><li>System Architecture </li></ul><ul><li>Applications and challenges </li></ul><ul><li>Intelligent Transportation System (ITS) Application scenarios: </li></ul><ul><ul><li>Routing issues </li></ul></ul><ul><ul><li>Data management issues </li></ul></ul><ul><li>Mobile Social Network (MSN) application scenario: </li></ul><ul><ul><li>Real implementation </li></ul></ul><ul><ul><li>Social analysis </li></ul></ul><ul><ul><li>Routing framework </li></ul></ul><ul><ul><li>Service evolution </li></ul></ul><ul><li>Conclusions </li></ul>
  3. 3. Introduction <ul><li>Mobile Computing: </li></ul><ul><ul><li>the possibility of being able to use a computing device </li></ul></ul><ul><ul><li>even when being mobile and therefore changing location </li></ul></ul><ul><li>Pervasive Computing: </li></ul><ul><ul><li>a halo of embedded devices immersed into reality </li></ul></ul><ul><ul><li>able to provide information to a human or to another device </li></ul></ul><ul><ul><li>about the environments he is immersed in </li></ul></ul><ul><li>Mobile Pervasive Computing: </li></ul><ul><ul><li>Devices moving around </li></ul></ul><ul><ul><li>Looking for information from sensing devices </li></ul></ul><ul><ul><li>Not necessarily connected to a central server </li></ul></ul><ul><ul><li>Opportunistically exchanging information on the fly </li></ul></ul>
  4. 4. System Architecture
  5. 5. Application Scenarios <ul><li>ITS - scenario 1: </li></ul><ul><ul><li>Mobile Nodes querying a large WSN (cars looking for a free parking) </li></ul></ul><ul><ul><li>With the absence of a central server </li></ul></ul><ul><ul><li>Need for new routing framework to handle a WSN with a mobile sink </li></ul></ul><ul><li>ITS - scenario 2: </li></ul><ul><ul><li>Mobile nodes querying gateway nodes </li></ul></ul><ul><ul><li>Exchanging information on the fly </li></ul></ul><ul><ul><li>Need for new data management techniques for handling large amount of volatile data </li></ul></ul>
  6. 6. Application Scenarios <ul><li>Mobile Social Networking </li></ul><ul><ul><li>Nodes interact among them on the basis of users’ profiles and interests </li></ul></ul><ul><ul><li>Groups of friends get created in a localized way </li></ul></ul><ul><li>In particular we deal with: </li></ul><ul><ul><li>A real implementation for smartphone </li></ul></ul><ul><ul><li>Social analysis deriving from the use of this mobile service in a real environment </li></ul></ul><ul><ul><li>Routing algorithm based on degree of friendship </li></ul></ul><ul><ul><li>Service evolution driven by mobility </li></ul></ul>
  7. 7. ITS: mobile sinks querying a large WSN <ul><li>Mobile Sink querying a WSN </li></ul><ul><ul><li>Representing cars looking for a parking place </li></ul></ul><ul><li>System architecture specifically tailored for ITS scenarios: </li></ul><ul><ul><li>MS e.g. a car </li></ul></ul><ul><ul><li>Sensing nodes e.g. presence sensors </li></ul></ul><ul><ul><li>Gateway nodes e.g interface nodes for the MS NOT providing continuous connection to the MS </li></ul></ul>
  8. 8. ITS: the routing framework <ul><li>Geographic forwarding </li></ul><ul><li>MS experiences frequent disconnections </li></ul><ul><li>Deadlock management </li></ul><ul><li>Mobility prediction </li></ul><ul><li>Load balancing strategies </li></ul><ul><ul><li>Delay aware routing </li></ul></ul><ul><ul><li>Energy aware routing </li></ul></ul>
  9. 9. ITS: simulation results <ul><li>Simulations performed in Omnet++ </li></ul><ul><li>Network dimensioning </li></ul><ul><li>Comparative study to evaluate load balancing techniques </li></ul><ul><li>Time to first node failure evaluated varying mobility and # of nodes </li></ul>
  10. 10. ITS: Data management issues <ul><li>Data management and compression scheme : </li></ul><ul><ul><li>Are needed in context aware applications for mobile nodes or in ITS applications </li></ul></ul><ul><ul><li>Largely deployed WSN </li></ul></ul><ul><ul><li>WSN can be considered as a Sensor Map (Image) </li></ul></ul><ul><ul><li>Local information has to be more precise while only coarse approximation can be kept for further information </li></ul></ul><ul><ul><li>Wavelet compression and data management scheme can help </li></ul></ul><ul><ul><li>Application scenario is described in figure </li></ul></ul>
  11. 11. Data management for large WSN: Simulation results <ul><li>Simulation conducted in Omnet++ </li></ul><ul><li>Large number of sensors (128x128 sensor grid) </li></ul><ul><li>Variable number of nodes (100 – 600) </li></ul><ul><li>Variable mobility pattern </li></ul><ul><li>Distortion between real sensor image and stored sensor image is measured </li></ul>
  12. 12. 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
  13. 13. State of the Art <ul><li>Opportunistic networking has been deeply investigated from a theoretical point of view: </li></ul><ul><ul><li>Bionets EU project </li></ul></ul><ul><ul><li>Haggle EU project </li></ul></ul><ul><ul><li>Several conferences and research intiatives </li></ul></ul><ul><li>Only few real developments have been proposed: </li></ul><ul><ul><li>To understand networking performance of the implemented protocols </li></ul></ul><ul><ul><li>To investigate social aspects related to proximity communications </li></ul></ul>
  14. 14. Motivation for a real implementation <ul><li>Mobile Phones are used: </li></ul><ul><ul><li>For Voice/video calls </li></ul></ul><ul><ul><li>As Messaging device </li></ul></ul><ul><ul><li>As MP3 player </li></ul></ul><ul><ul><li>As Cameras </li></ul></ul><ul><ul><li>To surf the web </li></ul></ul><ul><li>What if users could share data: </li></ul><ul><ul><li>Using their mobile phones </li></ul></ul><ul><ul><li>Leveraging on proximity communications rather than relying on a backhaul connection </li></ul></ul><ul><ul><li>Simply editing their preference and search options every once in a while </li></ul></ul><ul><ul><li>Putting the mobile phone in the pocket and then TRANSPARENTLY exchanging information when meeting other users, according to personal interests </li></ul></ul>
  15. 15. A middleware for pervasive environment <ul><li>U-Hopper: </li></ul><ul><ul><li>User centric Heterogeneous Opportunistic Middleware </li></ul></ul><ul><ul><li>provides users with ‘missing’ functionalities </li></ul></ul><ul><ul><li>Is Java + Bluetooth based </li></ul></ul><ul><ul><li>Can be used on every phone with J2ME support or Linux J2SE laptop </li></ul></ul><ul><li>Supported applications (december 2008): </li></ul><ul><ul><li>Profile editing (limited) </li></ul></ul><ul><ul><li>Advertisement and Business card exchange </li></ul></ul><ul><ul><li>Sensor data reading (images) and exchange </li></ul></ul><ul><ul><li>Contact exchange to trace contact evolution </li></ul></ul><ul><ul><li>Ring-tones exchange </li></ul></ul>
  16. 16. U-Hopper System Architecture <ul><li>Profile Manager (PM): </li></ul><ul><li>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 . </li></ul><ul><li>Service Container (SC) : </li></ul><ul><li>is the environment where context-aware services are executed. Such Container provides seamless access to resources such as content storage, opportunistic data retrieval, etc. </li></ul><ul><li>Content Manager (CM): </li></ul><ul><li>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. </li></ul>
  17. 17. U-Hopper System Architecture <ul><li>Interest Manager (IM): </li></ul><ul><li>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. </li></ul><ul><li>Content Acquisition (CA): </li></ul><ul><li>stores/update/removes data according to user preferences and service requirements. </li></ul><ul><li>Opportunistic Communication (OC) Unit </li></ul><ul><li>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. </li></ul>
  18. 18. Information exchange SERVER CLIENT Retreive DATA Retreive DATA Store DATA Store DATA Open Connection Send INTERESTS Send DATA Send INTERESTS Send DATA Close Connection
  19. 19. U-Hopper in pills… <ul><li>The middleware: </li></ul><ul><ul><li>J2ME version + J2SE version </li></ul></ul><ul><ul><li>Leverage on Bluetooth for communication </li></ul></ul><ul><ul><li>Persistency: RMS on J2ME and MySQL Db on J2SE devices </li></ul></ul><ul><ul><li>Used as a pure middleware </li></ul></ul><ul><li>Multiple applications with U-Hopper </li></ul><ul><ul><li>P2P data exchange (ring-tones + advertisement) </li></ul></ul><ul><ul><li>Business cards exchange </li></ul></ul><ul><ul><li>Sensor data reading and exchange </li></ul></ul><ul><ul><li>Others (not yet implemented…) </li></ul></ul>
  20. 20. U-Hopper application: mobile P2P Opportunistic Information Exchange BlueTooth Module Mobile Node MN Interests: U2 / Walk-On MN2 MN1 Interests: U2 / Walk-On
  21. 21. MSN: an analysis <ul><li>Office environment test bed: </li></ul><ul><ul><li>Interests collected through questionnaires </li></ul></ul><ul><ul><li>Contact pattern registered using U-hopper </li></ul></ul><ul><ul><li>21 participants for a 3 weeks period </li></ul></ul>
  22. 22. MSN: The contacts pattern <ul><li>Graph-based representation of the network of contacts </li></ul><ul><li>An edge exists between any 2 vertexes if contact time is at least 30 minutes per day. </li></ul>
  23. 23. MSN: emulation results <ul><li>Nodes infection ratio has been evaluated: </li></ul><ul><ul><li>Injecting packets in the network </li></ul></ul><ul><ul><li>According to users’ interests </li></ul></ul><ul><ul><li>On three different formats: text, music video </li></ul></ul><ul><ul><li>Packets have a varying TTL </li></ul></ul>
  24. 24. MSN: introducing the social dimension <ul><li>Questionnaires have been distributed: </li></ul><ul><ul><li>To understand the real interests of users </li></ul></ul><ul><ul><li>To map networking interaction with real interests </li></ul></ul><ul><li>Interests have been added to users profiles </li></ul><ul><li>A java simulator has been developed: </li></ul><ul><ul><li>With real contact traces </li></ul></ul><ul><ul><li>Mapping them with real interests </li></ul></ul><ul><li>We have defined a metric to understand impact of sociality into opportunistic networking </li></ul>
  25. 25. MSN: users affinity <ul><li>Affinity : </li></ul><ul><li>Preferences are: </li></ul><ul><li>The resulting graphs </li></ul><ul><li>with affinity>0.75 => </li></ul>
  26. 26. MSN: friendship based routing <ul><li>Users exchange data if their interests match enough </li></ul><ul><li>Interests are weighted according to a predefined # of friends K that have those interests </li></ul><ul><li>K-nearest friends are selected for info diffusion </li></ul>
  27. 27. MSN: friendship routing results <ul><li>We evaluated: </li></ul><ul><ul><li>Network Infection Rate i.e. how much messages are propagated in the network? </li></ul></ul><ul><ul><li>Utility: upon receiving a message, how much does it much user’s interests? </li></ul></ul>
  28. 28. MSN: the T9 service evolution <ul><li>Opportunistic networking is used to have a service evolving in a distributed way </li></ul><ul><li>Users exchange services parameters </li></ul><ul><li>The service evolve in such a way that user perception of the service increases </li></ul><ul><li>We defined a mathematical framework to do that </li></ul><ul><li>The example used is T9 service where we showed dictionary evolution to better fit users’ request </li></ul>
  29. 29. MSN: the T9 service evolution <ul><li>Fitness: </li></ul><ul><ul><li>is defined as the satisfaction a user experiences when using a service </li></ul></ul><ul><ul><li>The higher the fitness the higher the degree of satisfaction </li></ul></ul><ul><li>In the T9 example: </li></ul><ul><ul><li>User fitness is low if he has to search to many time for a word </li></ul></ul><ul><ul><li>Fitness is high if all words come at first </li></ul></ul><ul><li>Mobile opportunistic networking could help </li></ul><ul><ul><li>If I meet a user with high fitness he sends me his dictionary </li></ul></ul><ul><ul><li>My dictionary enlarges and my fitness increases </li></ul></ul><ul><li>We have defined an analytical framework and a simulation framework: </li></ul><ul><ul><li>to understand how the T9 service could evolve with mobile interactions </li></ul></ul><ul><ul><li>The impact of mobility for increasing users’ fitness </li></ul></ul>
  30. 30. 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
  31. 31. Conclusion <ul><li>In this work, a system architecture: </li></ul><ul><ul><li>has been defined, designed and implemented </li></ul></ul><ul><ul><li>to work in mobile pervasive environments </li></ul></ul><ul><ul><li>assuming no centralized connections </li></ul></ul><ul><li>The designed system architecture: </li></ul><ul><ul><li>solve the ITS scenario issues (routing and data management) </li></ul></ul><ul><ul><li>deals with the MSN challenges </li></ul></ul><ul><li>Challenges of such scenarios have been faced and overcome from: </li></ul><ul><ul><li>an analytical point of view </li></ul></ul><ul><ul><li>through an extensive simulation analysis </li></ul></ul><ul><ul><li>implementing a prototype and applying it to real world </li></ul></ul>
  32. 32. <ul><ul><ul><li>Thank You!!! </li></ul></ul></ul><ul><ul><ul><li>David Tacconi </li></ul></ul></ul><ul><ul><ul><li>Email: </li></ul></ul></ul><ul><ul><ul><li>Web: </li></ul></ul></ul>