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Dipanjan Chakraborty Anupam Joshi CSEE University of Maryland Baltimore County
Anamika: Distributed Service Discovery and Composition Architecture for Pervasive Environments
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I am Wireless LAN enabled!!
Service I am Wireless LAN enabled!! Blender!! I have GPS service!!
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Service Discovery Are you a Toaster ?? I am looking for a printer!!
Do you have MP3 songs?
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“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
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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
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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
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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
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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)
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Anamika: System Components
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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
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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
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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
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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
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Group-based Request Routing
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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
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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
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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
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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
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Results Simulation carried in Glomosim simulator 25 to 100 nodes Movement pattern=random way-point Radio Range of each node=31 meters
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Results
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Results
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Results
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Results
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Results
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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
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