1. Dipanjan Chakraborty Anupam Joshi CSEE University of Maryland Baltimore County
Anamika:
Distributed Service Discovery and Composition Architecture for Pervasive Environments

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

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

9. “Service Composition”
Definitions
“Service”
Hardware or software entity residing on any device or platform
Has distinct functional description
Can be utilized by other services/clients
“Service Discovery”
Process of discovering the availability of a service in the neighborhood
“Service Composition”
Integration and execution of multiple services in the planned order to satisfy a request

10. Ad hoc Environment
Network formed by multiple heterogeneous nodes in the reachable vicinity of one another
Some nodes are mobile, some are not
Environment around a device changes dynamically
Services exist on those devices

11. Issues of Service Discovery in an Ad hoc Environment
Discovery Architecture
Registry-based/centralized/semi-centralized
In Ad hoc Environment
Global request broadcasting
Global Advertisement and caching
Discovery method
Unique identifier/Interfaces/attributes
Language/network independence
Scalability

12. Issues of Service Composition in Ad hoc Environments
Services are distributed in the Environment
Efficient Service Discovery
Composition needs to be done in a de-centralized manner
Fault tolerance and graceful recovery
Solution should efficiently utilize node/service topology

13. General Architecture Application Layer Service Integration
Network Layer (DSDV/AODV/CSGR etc)
Service Integration
Layer
Application Layer
Broker Arbitration and Delegation
Service Execution
Fault Recovery Module
Planner
Service Discovery Layer (Bluetooth SDP, Salutation-lite etc)

14. Anamika: System Components

15. Anamika: Network Manager
Communication between Bluetooth peers done over RFCOMM
Connect-transmit-disconnect mode of operation
Segmentation and reassembly of Anamika messages
Implementation done on IBM’s Bluedrekar transport driver

16. 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

17. GSD= Group-based Service Discovery
GSD Protocol Summary
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

18. 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

19. Group-based Request Routing

20. 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

21. 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

22. 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

23. 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

24. Results
Simulation carried in Glomosim simulator
25 to 100 nodes
Movement pattern=random way-point
Radio Range of each node=31 meters

25. Results

26. Results

27. Results

28. Results

29. Results

30. Future Work
Simulation of the whole composition architecture
Implementation of a pro-active service discovery and composition architecture
Mathematical modeling of the discovery and composition process