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WORLD Project – KO Meeting University of Catania

WORLD Project – KO Meeting University of Catania. UNICT proposal WP1: System Architecture T1.2: WORLD system plan WP5: Cross-layer Wireless Multimedia and Active QoS-Mapping T5.2: Opportunistic access and node auto set up T5.3: Game-Theory-based distributed radio resource management

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WORLD Project – KO Meeting University of Catania

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  1. WORLD Project – KO MeetingUniversity of Catania Laura Galluccio

  2. UNICT proposal WP1: System Architecture T1.2: WORLD system plan WP5: Cross-layer Wireless Multimedia and Active QoS-Mapping T5.2: Opportunistic access and node auto set up T5.3: Game-Theory-based distributed radio resource management WP6: Applications and secure End-to-End QoS-provisioning (leadership) T6.2: Opportunistic scalable video and audio coding for adaptive streaming applications T6.4: Multimedia Peer-to-Peer (P2P) WLAN connections Research Activities (AR) Laura Galluccio

  3. T1.2: World System Plan We will collaborate to the definition of • System and network architecture (Context awareness and reconfigurability techniques, QoS support mechanisms) • Protocol architecture (Cross layer interactions, QoS transversal support) Laura Galluccio

  4. T5.2: Opportunistic Access and Node auto set up

  5. T5.2: Opportunistic Access and Node auto set up • Nodes opportunistically enter and exit the P2P network • Mechanisms to let nodes self-reconfigure and discover other devices and services will be needed • Discovery procedures should be characterized both in terms of performance and algorithms Laura Galluccio

  6. T5.2: Opportunistic Access and Node auto set up • To automatically set up nodes, it will be required to: • Localize • Distribute a catalogue of the available resources Laura Galluccio

  7. Localization • Infostation nodes are also available into the network • Some nodes are equipped with GPS • Other nodes do not • Location information is needed to implement a distributed algorithm for resources propagation into the network • We will develop a middleware allowing nodes localization through some fixed position-aware nodes Laura Galluccio

  8. Localization • This middleware will allow to • Perform an algorithm to let the nodes calculate their position exploiting position-aware nodes • Send beacon packets • Use these packets to estimate the packet loss probability (PLP) • Use the PLP to evaluate the bit error probability (BEP) • Estimate the SNR • Obtain the distribution of the SNR Laura Galluccio

  9. Resources catalogue: A mobile world • Rapid increase in the amount of multimedia contents created “on the road” • Pervasive use of personal portable devices • Users typically share contents by non-mobile systems (P2P sharing program; social network) • User friendly interface to easily share and exchange data through heterogeneous information systems and communication technologies but in the near future

  10. What is our target? • To provide a general purpose platform whose aim is to create data sharing services in mobile environment in a modular and adaptive way • Some scenarios: • Music festivals: where people could share contents (photos, songs, videos) • Municipal services • Cultural activities • Mobile social network

  11. Existing solutions • Several works in literature deal with the problem of data sharing in mobile environments • Solutions based on novel protocols or different transmission techniques are proposed to solve the architectural and technical problems: • Web-service based platform (Internet access is required) • Instant messaging architecture (server based scheme) • Mobile P2P solutions (using the cellular network) • The majority of the existing solutions are related to specific applications and use an infrastructured scheme

  12. Idea ShareAnywhere (SA) will be a platform which provides an application framework where mobile devices make use of user-friendly methods to share and exchange digital contents among heterogeneous systems and through different communication technologies.

  13. Logical Architecture InfoStations: Network nodes revealing the presence of mobile nodes and providing resources CMS: Non-mobile system front-end to upload the resources Mobile Nodes: Cellular phones, PDAs and Notebooks running an appropriate software Database: element storing all the system resources

  14. T5.3: Game-Theory based distributed radio resource management

  15. T5.3: Game-Theory based distributed radio resource management • Infostations will be used by mobile nodes to download the required information when located in the proximity • In case of multimedia applications playout buffers length should be taken into account when considering the possibility to download frames during the limited proximity time • Requests being sent to the infostation nodes should be managed according to a priority-like mechanism taking into account the limited proximity time, the remaining energy and the above mentioned playout buffer residual length • A game modeling of this problem will be provided Laura Galluccio

  16. T5.3: Game-Theory based distributed radio resource management • A traditional CSMA/CA model will be modified to allow support of priority differentiation in traffic management • Network management will be performed by means of a jamming policy • Game modeling will imply • Use of a utility function (U)=node throughput (r ) • Use of a penalty function (P)=difference in throughput due to nodes deviation from the expected throughput • Use of a payoff function (f) f=U-P to be maximized based on the different nodes priority (q) • -node priority (q) depending on playout buffer residual length (Q), residual energy (E) and residual time in the proximity of the infostation(T) Laura Galluccio

  17. T5.3: Game-Theory based distributed radio resource management • Strategy: identified with the values assumed by the contention window size at the observation time • Access probability • Node throughput Laura Galluccio

  18. T5.3: Game-Theory based distributed radio resource management • Payoff • Priority • Expected throughput Laura Galluccio

  19. T5.3: Game-Theory based distributed radio resource management Definition of a distributed algorithm for reaching the Pareto Optimal Equilibria and letting the system work around it

  20. T6.2: Opportunistic scalable video and audio coding for adaptive streaming applications

  21. T6.2: Opportunistic scalable video and audio coding for adaptive streaming applications • The main target of this activity will be evaluation of the impact of using opportunistic techniques for support of multimedia traffic in P2P wireless networks • Multimedia Coding impacts on • File size and consequent storage requirements • The way the resource is distributed into the network (many copies at different coding quality can be distributed) • Resource distribution should consider inter-contact time distribution! Laura Galluccio

  22. T6.2: Opportunistic scalable video and audio coding for adaptive streaming applications • Two strategies will be prosecuted: • Software implementation • Simulation

  23. T6.4: Multimedia Peer-to-Peer (P2P) WLAN connections

  24. Due to the limited bandwidth resources in wireless channels redundancy should be reduced To this purpose network coding can be used in P2P multihop communication environments Network coding allows to combine different files’ chunks so as to reduce energy consumption, increase capacity and thus throughput, and should be variable according to network conditions Drawbacks are longer processing and thus increase in delivery delay We will analitically characterize the problem Then, we will define and test an algorithm for estimating system performance T6.4: Multimedia Peer-to-Peer (P2P) WLAN connections Laura Galluccio

  25. T6.4: Multimedia Peer-to-Peer (P2P) WLAN connections • Energy efficient data routing will be addressed as well • Knowledge of position is required and can be obtained by mean of localization techniques as discussed above • Once known the position, geographical forwarding can be exploited to forward information

  26. T6.4: Multimedia Peer-to-Peer (P2P) WLAN connections • Same Payload size SD • Header size equal to SH andSHNC~2SH • Node density around node A equal to A

  27. T6.4: Multimedia Peer-to-Peer (P2P) WLAN connections

  28. T6.4: Multimedia Peer-to-Peer (P2P) WLAN connections

  29. T6.4: Multimedia Peer-to-Peer (P2P) WLAN connections

  30. T6.4: Multimedia Peer-to-Peer (P2P) WLAN connections

  31. T6.4: Multimedia Peer-to-Peer (P2P) WLAN connections

  32. T6.4: Multimedia Peer-to-Peer (P2P) WLAN connections

  33. T6.4: Multimedia Peer-to-Peer (P2P) WLAN connections

  34. T6.4: Multimedia Peer-to-Peer (P2P) WLAN connections

  35. T6.4: Multimedia Peer-to-Peer (P2P) WLAN connections

  36. T6.4: Multimedia Peer-to-Peer (P2P) WLAN connections

  37. T6.4: Multimedia Peer-to-Peer (P2P) WLAN connections

  38. T6.4: Multimedia Peer-to-Peer (P2P) WLAN connections

  39. T6.4: Multimedia Peer-to-Peer (P2P) WLAN connections

  40. T6.4: Multimedia Peer-to-Peer (P2P) WLAN connections

  41. Summarizing… • WP5: Cross-layer Wireless Multimedia and Active QoS-Mapping • T5.2: Opportunistic access and node auto set up • Localization (just started!) • Resource catalogue (ongoing!!!) • T5.3: Game-Theory-based distributed radio resource management (ongoing!!) • WP6: Applications and secure End-to-End QoS-provisioning (leadership) • T6.2: Opportunistic scalable video and audio coding for adaptive streaming applications (just started!) • T6.4: Multimedia Peer-to-Peer (P2P) WLAN connections (ongoing!)

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