Mobisys Seminar 28/10/08

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Mobisys Seminar 28/10/08

  1. 1. Pervasive Social Computing : Algorithms and Deployments Sonia Ben Mokhtar Mobisys Seminar 28th October 2008
  2. 2. Pervasive Social Computing (PSC) Social Networks Pervasive functionalities Middleware for pervasive computing Heterogeneous Platforms 10
  3. 3. I would like to have a coffee with other Scenarios breastfeeding mums in my neighborhood Arrange a tennis game around the campus at 5pm, intermediate player level, 1hour I am looking for a postdoc/internship in an English speaking country starting next September I would like to share a cab for going back home
  4. 4. Issues and Key Challenges • Issues – Environment Heterogeneity & Dynamics – Social-based user centrism – Distributed, Multi-activity social network – Context-awareness – Semantic-awareness – Privacy • Challenges – Middleware hosted in some (all) devices responsible for : • Specification of user tasks (social-, semantic-aware) • Disseminating user tasks (scalable, privacy- and context-aware) • Matching user tasks (social-, semantic- and context-aware) • Notifying the users of matching results
  5. 5. Related Work: Existing Middleware Paradigms • Tuple Space (distributed shared memory) – Stateful, non-scalable • Event-based (pub-sub) – Proactive – Persistency of subscriptions vs volatility of user tasks • RPC-based (SOC) – Persistency of services vs volatility of user tasks – Service requester and provider roles are merged
  6. 6. Outline • A Middleware for PSC (Overview) • Matching User Task Specifications – Algorithms & Evaluation • Middleware Deployment Strategies – Deployment Strategies & Evaluation • Conclusions & Future Work
  7. 7. A Middleware for PSC (Overview) User Task Specification UserId: toto Activity: Tennis NbrPersons: 1 Preferences: -A-->0.8 -B-->0.5 -C-->0.2 Context Properties: 5pm, UCL campus, 2hours TTL = 2hours from now
  8. 8. Outline • A Middleware for PSC (Overview) • Matching User Task Specifications – Algorithms & Evaluation • Middleware Deployment Strategies – Deployment Strategies & Evaluation • Conclusions & Future Work
  9. 9. Matching user tasks in PSC FIFO Local Satisfaction T? T1 T? T1 T2 … Tn Return T1 Return Ti: Max(Utility(T,Ti)) Overall Satisfaction Nearly Overall T? T1 T2 … Tn T? T1 T2 … Tn 1. Generate all the possible pairs 1. Generate all the possible pairs 2. Compute Best Combination 2. Generate a Combination of the Best C*={(Ti,Tj)}: Utility(C*)=Max pairs 3. Return Ti associated with T C+= {(Ti,Tj)}: Utility((Ti,Tj)) > Utility((Ti+1,Tj+1)) 3. Return Ti associated with T
  10. 10. Evaluation of the Matching Strategies • Mobility Traces: MIT • Social Network: Advogato • Scenario: – A node is elected to act as a broker (most popular) – Each time a node encounters the broker: Task Publication – When a node meets the broker again it is notified of the answer if any (matching, expiry) • Measurements: – Accuracy (generated utility, distribution of the utility) – Computational Overhead, delay to answer
  11. 11. Utility wrt Matching Strategy
  12. 12. Distribution of the Satisfaction wrt Matching Strategy
  13. 13. Overhead of the Matching Strategies
  14. 14. Delay to Answer wrt Matching Strategy
  15. 15. Matching Strategy: Discussion • Resource Constraints and Social Network is not important  Fifo • Resource Constraints and Social Network is critical  Local • Otherwise  Nearly or Combined
  16. 16. Outline • A Middleware for PSC (Overview) • Matching User Task Specifications – Algorithms & Evaluation • Middleware Deployment Strategies – Deployment Strategies & Evaluation • Conclusions & Future Work
  17. 17. Middleware Deployment Strategies: Stationary Highly Connected Overlay
  18. 18. Middleware Deployment Strategies: Mobile Loosely Connected Overlay Publication T2 Dissemination T1,T2 Notification T2 Notification T1 Matching T1,T2 Publication T1
  19. 19. Middleware Deployment Strategies: Mobile Independent Brokers
  20. 20. Evaluation of the Deployment Strategies • Mobility Traces: MIT, Cambridge • Social Network: Advogato, MovieLens, LastFM • Scenario: – N brokers are elected in the Network (popularity) – Each time a node encounters a brokers: Task Publication – When a node meets the broker again it is notified of the answer if any (matching, expiry) • Measurements: – Accuracy (distribution of utility wrt: strategy, number of brokers,Traces) – Communication Overhead (Number of messages, amount of traffic)
  21. 21. Distribution of the Satisfaction wrt Deployment Strategy
  22. 22. Communication Overhead of the Deployment Strategies
  23. 23. Distribution of the Satisfaction wrt Number of Brokers and Mobility Traces
  24. 24. Middleware Deployment Strategies: Discussion • If an infrastructure exists (e.g., campus)  Stationary Overlay • If no infrastructure and setting up one does not worth it (e.g., conference)  Mobile Overlay  A pre-analysis is worth doing to estimate the number of brokers to deploy
  25. 25. Effect of the Connectivity of the Social Network on the Utility
  26. 26. Outline • A Middleware for PSC (Overview) • Matching User Task Specifications – Algorithms & Evaluation • Middleware Deployment Strategies – Deployment Strategies & Evaluation • Conclusions & Future Work
  27. 27. Conclusions & FW • Pervasive Social Computing – Enable social interactivity among mobile users – Middleware for PSC support the scalable task publication/dissemination/notification, social-context-aware task matching • FW: The propagation of the social preferences by the brokers – In the same activity, across different activities • FW: Semantic specification and matching of user tasks – Emergent semantics vs Ontology-based approach

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