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Principles of Personalisation of Service Discovery Electronics and Computer Science, University of Southampton myGrid UK e-Science Project Juri Papay,

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Presentation on theme: "Principles of Personalisation of Service Discovery Electronics and Computer Science, University of Southampton myGrid UK e-Science Project Juri Papay,"— Presentation transcript:

1 Principles of Personalisation of Service Discovery Electronics and Computer Science, University of Southampton myGrid UK e-Science Project Juri Papay, Simon Miles, Michael Luck, Luc Moreau, Terry Payne

2 The Aim Personalisation of Service Discovery

3 Service Discovery Requirement for Service Discovery Increasing number of services on Grid Workflows encoding experiments Lab-based databases and tools Starting to use on-line tools of one discipline in another Services that provide experimentally neutral but necessary functionality Potential flood of useless information!

4 Personalisation of Service Discovery To take an example, a new researcher joins a lab They want to use, in their in-silico experiments, the services that existing experts in the lab trust When they use the service discovery mechanism provided to them, they should first discover recommended services (they may then decide to widen the scope of discovery if they don’t find what they want)

5 Forming a Solution Principles of Personalised Service Discovery

6 Principles Through working on the personalisation of service discovery, we have identified three key principles that should be observed These have informed the design of our own implementation in myGrid

7 Principle of Personalised Service Discovery #1 Service discovery should be based on the service adverts currently available in public registries. Service providers should not have to publish their services multiple times to take advantage of personalised service discovery. Provider-Independent: Personalisation should be independent from provision

8 Principle of Personalised Service Discovery #2 While aggregating the contents of public service registries may aid the user in discovering what they need, there are many services that will not be applicable to their requirements, so filtering must take place before, as well as during, discovery. Aggregation & Filtering: Aggregation should be used to widen and filtering to narrow discovery to make it most applicable

9 Principle of Personalised Service Discovery #3 User knowledge and opinions of services should be encoded and taken into account in discovery. However, users may not want their knowledge or opinions to be publicly accessible, so metadata should be stored locally and access controlled. Private Profile-Based Discovery: Personalisation should be based on the individual’s personal profile

10 A Personalised Service Registry Annotation, Aggregation, Notification and Filtering

11 Design Our design is based around a personalised service registry which fulfils the three principles Its key features are Attachment of metadata to service adverts Locally deployed registries, with locally determined access control, aggregating the contents of remote publicly accessible registries Subscription to notifications of change in remote registries, to keep personal registries up to date

12 Metadata Attachment Service providers may adopt various ways of describing their services, access policies, contract negotiation details etc. Resource consumers also impose their own selection policies on the services they prefer to use, such as QoS and reputation metrics The myGrid service registry allows third-parties to attach metadata to published service descriptions and then for those annotations to be used in subsequent service discovery Metadata can refer to ontologies so as to provide knowledge in a previously agreed and hopefully less ambiguous way

13 Aggregation and Filtering Personalised registries replicate the contents of remote registries locally, so that they can be annotated and used in discovery in an efficient and private manner A local policy file automatically determines whether a service is useful enough to be kept based on its description and metadata The myGrid service registry supports the sending of notifications when service adverts, their interfaces or their metadata are added, removed or changed

14 Keeping Up to Date As new services and potentially useful services are advertised, they should have the potential to be discovered by users The local contents can be kept up to date with the remote registries either by the local registry regularly polling the remote registry, or, if the remote registry permits it, the local registry subscribing to notifications of change in the remote registry

15 Implementation The myGrid Personalised Service Registry

16 Example Interaction Returning to the example given before, we can see how this would be manifested using personalised service registries

17 Implementation To enable Web Service clients to move easily to using the myGrid registry, it extends the UDDI de-facto standard for service descriptions and WSDL standard for describing interfaces Other protocols can be supported by wrapper interfaces around the same canonical model Aggregation, filtering, access control and sending of notifications are controlled by a policy file Notifications between registries use the myGrid notification service to allow for asynchronous messaging and decoupling of publishers and subscribers

18 Sequence of Messages Between Registries

19 Conclusions We have developed a service registry that allows access-controlled metadata attachment and policy- controlled aggregation and filtering of remote registry contents Through this work, we have determined the three principles which should be observed in personalised service discovery: Personalisation should be independent from provision Aggregation should be used to widen and filtering to narrow discovery to make it most applicable Personalisation should be based on the individual’s personal profile

20 Future Work The basic myGrid service registry is being made more scalable, reliable and secure under the OMII managed programme Current work on the policy definitions can be found in a forthcoming paper for the Specialist Group on Artificial Intelligence conference

21 ibm


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