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Using Peer-to-Peer Data Routing for Infrastructure-Based Wireless Networks

Using Peer-to-Peer Data Routing for Infrastructure-Based Wireless Networks Sethuram Balaji Kodeswaran , Olga Ratsimor, Anupam Joshi, Tim Finin, Yelena Yesha ebiquity.umbc.edu. eBiquity Group Technical Roots. Web Services. DB. Semantic Web. AI. Intelligent Information Systems. Mobility.

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Using Peer-to-Peer Data Routing for Infrastructure-Based Wireless Networks

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  1. Using Peer-to-Peer Data Routing for Infrastructure-Based Wireless Networks Sethuram Balaji Kodeswaran, Olga Ratsimor, Anupam Joshi, Tim Finin, Yelena Yesha ebiquity.umbc.edu

  2. eBiquity Group Technical Roots Web Services DB SemanticWeb AI IntelligentInformationSystems Mobility Trust Networking& Systems Security Assurance PervasiveComputing Privacy

  3. Overview • Introduction • Motivation • Network Model • Typical Usage Scenario • Numi Framework Overview • Simulation Results • Sample Application • Conclusion and Future Work • Q&A

  4. Introduction • Combining infrastructure and ad hoc communication to meet mobile users data needs • Mobile devices offer unused resources to support the needs of their peers • Infrastructure components monitor device mobility and orchestrate utilization of available “excess” resources • Mobile devices use peer-to-peer interactions to obtain data carried by peers on their behalf

  5. Motivation • Widespread use of personal devices • Devices with limited and varying capabilities • Data-intensive services • Improved ad-hoc capabilities • Expensive cellular WAN connectivity • Increased Popularity of HotSpots (commercial community networks) • Starbuck’s, Borders, T-Mobile Hotspots, PersonalTelco, Seattle Wireless, Consume • Islands of high speed network connectivity separated by areas of no network access

  6. Landing Zones are islands of high speed cheap network connectivity around a Service Portal limited only by that portal’s wireless range Transit Zones are regions where there is no network connection In Landing Zones, mobile hosts communicate with service portals only In Transit Zones, mobile hosts communicate with each other Landing Zone MH1 MH2 Transit Zone Landing Zone Network Model

  7. Network Components Service Portals • Infostations offering high-speed network connectivity and hosting services that can be used by nearby mobile hosts • Portals use their wireless capabilities to interact with mobile hosts that are in range • Portals use wireline connectivity to communicate among themselves. Mobile Hosts • Mobile hosts are wireless mobile devices that can communicate both with infrastructure and neighboring peer mobile hosts that are within range (ad hoc mode). Services • Service Agents • Service Data Units • Service Data Volumes

  8. Bob Susan Typical Usage Scenario

  9. Network Component Interactions • Node to Portal Interaction • A mobile host, in a landing zone, can request a set of new services (upon user's request) or it can ask for additional data for currently running services (transparent to the user) • Portal to Portal Interaction • Portals notify neighbors of service/data provided to a passing by mobile node. This ensures that data that would be needed by mobile hosts are properly scheduled to be delivered to them • Node to Node Interaction • The Node-to-Node interaction is employed by a mobile host to obtain any additional data from another mobile hosts in transit zones

  10. Heartbeat Generator Agent is responsible for broadcasting device presence messages Location Monitor Agent is responsible for identifying whether or not that device is currently in a landing zone or a transit zone Message Handler Agent is responsible for handling the messaging needs of the framework Logger Agent records every interaction that takes place on the local device Numi Framework Numi Node Framework Node Heartbeat Generator Numi Task Scheduler Location Monitor Data Handler Agent Message Handler Node Service Manager Logging Agent Numi Portal Framework Portal Heartbeat Generator Numi Task Scheduler Location Monitor Data Handler Agent Message Handler Portal Service Manager Logging Agent Music Service Agent

  11. Task Scheduler Agent is responsible for scheduling prescribed tasks at various times Data Handler Agentis used for transferring data volumes between MHs and between an MH and an SP Portal Service Agents run on top of our Numi platform on SPs and offer services to a user Node Service Agent runs within NUMI on an MH offering a service to the user Service Manager Agent is responsible for managing service agents on a platform Numi Framework Numi Node Framework Node Heartbeat Generator Numi Task Scheduler Location Monitor Data Handler Agent Message Handler Node Service Manager Logging Agent Numi Portal Framework Portal Heartbeat Generator Numi Task Scheduler Location Monitor Data Handler Agent Message Handler Portal Service Manager Logging Agent Music Service Agent

  12. Simulation Environment • Simulations conducted using GlomoSim • 802.11 used as MAC protocol • Geographical region considered is 10 sq Kilometers • Node mobility assumed to be piece-wise linear • Numi configuration: • Node presence interval 8 sec • Node zone refresh interval 1 sec • Portal presence interval 8 sec • Portal zone refresh interval 1 sec • Presence message validity 10 secs • Data Query Manager runs every 100ms to identify next data segment needed • Simulated behavior of an application that is non-real time and whose data needs are fairly predictable (example playlist, newspaper, eBooks, etc)

  13. Simulation Experiments Compared the performance of the following schemes: • Data Hoarding (DH): Device tries to cache as much data as needed until it reaches the next portal on its route. If device runs out of data, a service disruption is assumed to occur • Ad hoc Querying (AQ): Device tries to cache as much data as needed until it reaches the next portal on its route .If device runs out data, device queries its immediate neighborhood for next segment. If query fails, a service disruption is assumed to occur • Ad hoc Querying with Peer Routing (AQPR): Similar to above scheme but in addition, devices offer their excess capacity to the network portals to use for transporting data segments for other peers

  14. Service Disruption vs Number of Portals Device capacity < 1MB Number of nodes 100 Speed < 20 mt/sec Data segment size < .2 MB

  15. Service Disruption vs Nodes in Network Device capacity < 1MB Number of portals 3 Speed < 20 mt/sec Data segment size < .2 MB

  16. Service Disruption vs Node Speed Device capacity < 1MB Number of nodes 100 Number of portals 5 Data segment size < .2 MB

  17. Service Disruption vs Total Universe of Responses Device capacity < 1MB Number of nodes 100 Number of portals 5 Speed < 20 mt/sec Data segment size < .2 MB

  18. Service Disruption vs Device Memory Number of nodes 100 Number of portals 5 Speed < 20 mt/sec Data segment size < .2 MB

  19. Prototype Application • A Music Jukebox application that allows a user to listen to his favorite MP3 playlist on his PDA • Implemented in Java (Personal Java) • Network Model Used • 3 PCs equipped with 802.11b wireless LAN cards acting as Service Portals • 3 iPAQs equipped with 802.11b wireless LAN cards acting as Mobile Hosts • Web Browser on iPAQ used as User Interface • Service Portals run Tomcat Servlet Engine for accepting user’s requests

  20. Mobility Coordinator • We have developed an additional simulation component called the Mobility Coordinator • Control messages can be sent to any mobile host to change its current cell ID • Only messages tagged with the same cell ID that a mobile device belongs to are accepted. Others are dropped

  21. Conclusion and Future Work • Utilize a combination of infrastructure and ad hoc communication to provide uninterrupted services to a user • Mobile devices offer up excess capacity to the network for supporting peers • Ongoing work • Group and Multi-hop scheduling • Route deviations and its effects • Optimal Portal Placement strategies • Security and Privacy Issues

  22. ebiquity.umbc.edu

  23. MH1 MH2 Typical Usage Scenario Portal 2 P 5 P 6 P 3 P 4 Portal 1

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