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Dipanjan Chakraborty Anupam Joshi CSEE University of Maryland Baltimore County

Dipanjan Chakraborty Anupam Joshi CSEE University of Maryland Baltimore County. Anamika: Distributed Service Discovery and Composition Architecture for Pervasive Environments. Printing to the Nearest Printer. Wireless Sync between PDAs. Composition of Multiple Services. Wireless Office.

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Dipanjan Chakraborty Anupam Joshi CSEE University of Maryland Baltimore County

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  1. Dipanjan ChakrabortyAnupam JoshiCSEEUniversity of Maryland Baltimore County Anamika: Distributed Service Discovery and Composition Architecture for Pervasive Environments

  2. Printing to the Nearest Printer

  3. Wireless Sync between PDAs

  4. Composition of Multiple Services

  5. Wireless Office

  6. Discover and Compose Information from robots on the fly

  7. Service • “Service” • Hardware or software entity residing on any device or platform • Has distinct functional description • Can be utilized by other services/clients

  8. Service I am Wireless LAN enabled!! Blender!! I have GPS service!!

  9. Service Discovery Are you a Toaster ?? I am looking for a printer!! Do you have MP3 songs?

  10. MANET

  11. MANET

  12. MANET

  13. MANET

  14. MANET

  15. MANET

  16. MANET MANET

  17. MANET MANET

  18. MANET MANET

  19. MANET MANET

  20. MANET MANET

  21. MANET MANET

  22. MANET MANET

  23. MANET MANET

  24. Issues of Discovery and Composition in Ad hoc Environments • Service Discovery needs to be distributed • Network-wide reachability • Efficient utilization of underlying network bandwidth • Composition needs to be done in a de-centralized manner • Fault tolerance and graceful recovery • Solution should efficiently utilize node/service topology

  25. Application Layer Service Integration Layer Service Execution Layer Broker Arbitration and Delegation Fault Recovery Module Network Layer (DSDV/AODV/CSGR, GSR) General Architecture Planner Service Discovery Layer (GSD)

  26. Group-Based Service Discovery (GSD) • GSD= Group-based Service Discovery • Peer-to-peer caching of service advertisements • No global advertisements • No global request broadcast • Describe services semantically in DARPA Agent Markup Language (DAML) • Enhance service matching mechanism based on semantic description

  27. GSD Protocol Summary • Class/subClass hierarchy of DAML used to classify services to different groups based on functionality • Intelligently forward requests to appropriate nodes • Prevent request flooding • Efficient in terms of bandwidth usage and discovering a service in a MANET

  28. Request Routing in GSD

  29. Combining Routing with Discovery • Service Invocation requires data streaming • Usually underlying ad hoc routing protocol (AODV, DSR, TORA etc) used • Disadvantages of using standard routing protocols • Repeats a few steps performed during discovery • Node-address centric packet delivery • Routing Layer is not service-aware

  30. Advantages of Integrating Routing with Discovery • Reduced network load • Steps performed during routing is combined with discovery • Usage of available routes (formed during discovery) to stream service data • Service-based route redirection • Resilience to node failure

  31. Features of Integrated Discovery and Routing Protocol (GSR) • Uses path traversed by a service request and a service advertisement to form a data path • Data path used to stream service data • Service-based route redirection in case of service/node failure • End-to-end state-based session maintenance • Handles node and link failure • Session-based packet buffering and retransmission upon session reconnection

  32. Service Composition Techniques • “Request Processor” uses DAML-S to model Composition Knowledge • Dynamic Broker Selection Technique • No assumption about the platform of the broker/central entity • Broker Arbitration and Delegation • Source of the request starts a process which decides the broker platform • Parameters based on current processor usage, memory capability, longevity, services available in its vicinity etc

  33. Dynamic Broker Selection Technique (contd.) • Broker discovers *all* the required services • Fault tolerance • Source-monitored fault-tolerance • Assumption: Source remains ‘alive’ all the time • Periodic ‘checkpoints’ being sent to the source • Source issues a new composition request in case of failure

  34. Service Composition Techniques • Distributed Brokering Technique • Broker Arbitration and Delegation • Requester is responsible to determine the ‘first’ broker • Parameters to select a broker are similar to the ‘dynamic Broker selection’ mechanism • More emphasis on services that are needed ‘immediately’ • ‘first’ broker not responsible for the whole composition • Composes only ‘as much’ as it can • ‘radius’ of composition is small • ‘first’ broker selects another broker when it has completed the ‘partial’ composition

  35. Distributed Brokering Technique (contd.) • Fault Recovery • Similar to the one used in ‘dynamic entity selection’ mechanism • Each broker keeps the client informed about the partial state of composition and execution • Client issues a new composition request with the subset that is remaining

  36. Practical Implementation • proof-of-concept level implementation using Bluetooth • IBM Bluedrekar driver • Ericsson Development Kits • Laptops (Dell, IBM T series) used for hosting services

  37. Anamika: Network Manager • Communication between Bluetooth peers done over RFCOMM • Connect-transmit-disconnect mode of operation • Segmentation and reassembly of Anamika messages

  38. Anamika: Service Discovery • Peer-to-peer service discovery (Group-based Service Discovery) • Dynamic caching of discovered services in peers • Semantic description based service matching (using DAML-S and DReggie Ontology) • Service Discovery also provides invocation information

  39. Group-based Service Discovery Results • Simulation carried in Glomosim simulator • 25 to 100 nodes • Movement pattern=random way-point • A(b,c) => pause for A seconds and then move to the next location with speed varying from b to c m/s • Radio Range of each node=31 meters

  40. Group-based Service Discovery Results • Simulation carried in Glomosim simulator • 25 to 100 nodes • Movement pattern=random way-point • Radio Range of each node=31 meters

  41. Increase in Nodes Receiving Advertisements with Increase in Adv. Diameter

  42. Explanation • In static topology • Number of nodes receiving advertisements increase quadratically with adv. Radius • In mobile topology increase in number of nodes receiving advertisements is approximately linear • Significantly affects the scalability • Important result for mobile application architecture development

  43. Message Statistics comparing GSD with Broadcast

  44. Message Statistics comparing GSD with Broadcast

  45. Message Statistics comparing GSD with Broadcast

  46. Explanation • Average number of messages exchanged is lower in GSD • Mobility affects the number of messages but GSD in general performs better • Broadcasts are very much reduced in GSD leading to the improvement in the total traffic

  47. More GSD Results

  48. GSD Results

  49. GSD Results

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