1 Towards Building Generic Grid Services Platform A component oriented approach Jeyarajan Thiyagalingam Stavros Isaiadis, Vladimir Getov Distributed and High Performance Systems Group University of Westminster, England.

2 Motivation Grid Everywhere and Pervasive Computing strategies demand more software infrastructure. Applying the Grid concept to Grid, non-Grid and mobile contexts. This requires more than socket-on-the-wall concept. Small devices may take part in computation – but we also want them to offer services. More coupling with consumer computational devices – PDAs, laptops, etc. and not necessarily supercomputing clusters.

3 So, what's wrong so far? OGSA on these devices? Existing Grid Infrastructure: –is too rich in features. –too costly to deploy on non-Grid contexts. –most of these features may not necessarily be appropriate for the non-Grid contexts. –is difficult to change, tailor or transplant – once deployed.

4 Where we went wrong? In the marriage with the Use-Cases. High-end applications & devices pushed the requirements. any feature should be part of our features idea. Software infrastructure didnt anticipate the future.

5 What we could do? Re–think the design: Hard to tinker the existing ones. Consider a wide range of applications & devices. Include Grid and non-Grid contexts in consideration. Design and select the appropriate features: Build intelligence & learning include adaptivity & reconfigurability Make it lightweight and Anticipate the future.

6 Generic Services Grid Platform Plan –Identify a common set of core features and implement them as part of the services platform. –Implement the rest of the features as on-demand pluggable components or componentise as much as possible.

7 Generic Services Grid Platform: What we have? On-going work at Westminster No experimental/performance results. Sensible?

8 Quick Definitions Feature –An implemented feature inside the core platform. Feature Knowledge –Information relating to a new component which might be plugged in at a future time.

9 Feature Set Core operating support Core connectivity Services Knowledge Engine Component Management Engine (CME) Service Management Engine (SME) (policy driven) Feature Set can be re-defined later.

10 Feature Knowledge Set Standard Grid Services as components or as Web Services. Future Generation Services – Self Healing, Grid in P2P systems, etc. Developed as adaptive components - They should be reconfigurable and should adapt themselves to the environment. New Feature Sets can be plugged in later.

11 Overall System

12 Functionality Platform is built with minimal functionalities. –but should offer full range of services. At the beginning, platform builds the list of available components/services ( through discovery). If necessary, the platform can use its foreknowledge about service locations. When a job is submitted, the SME/CME parts analyse the job description and construct an action plan.

13 Functionality … II An action plan describes the sequence of operations to be carried out to complete a job, but in a completely job-dependent way. The plan is constructed based on a policy. The platform demands and plugs-in components as needed – instead of pre-loading all of them. The CME part of the platform deals with management of components, plugging them, unplugging them, etc.

14 Functionality … III If a service is not available locally, the service is obtained from a remote site. Policies are used wherever applicable. If there are no policies, adaptive/learning engine should handle the situation. Services/Components adapt their behaviour to the changing conditions. If a service component evolves while in use, the platform updates the interaction map, its composition representations and re-configure the component without any service disruption.

15 Engineering The Platform: Plan Consider a wide range of applications & devices. Identify the Services which are generic to all Grid applications and implement them as feature set. Develop the platform –Such that new feature sets and feature knowledge sets can be defined. –Encompass adaptivity, intelligence, reconfiguration mechanisms. –As a context based policy driven platform. Implement services as adaptable and reconfigurable Web-Services.

16 Engineering The Platform: Challenges Representation of feature set, feature knowledge set, action plans, reconfiguration plans and policies. Adaptivity: –May require smarter discovery protocols –Cross component interaction, optimization etc. –Intelligence through learning – may be difficult. Interaction within the feature set components, adaptive guidance, self-initiation and re-configuration. Security: As part of the feature list? or as part of the feature knowledge set?

17 Conclusions A component specific solution to build Generic Grid Services Platform. Addresses the longevity, flexibility and expandability. Beginning to address the strategies: Pervasive Computing and Grid Everywhere. Aligns with the WSRF roadmap. Opens up other research questions and avenues. –Cross component interaction, optimisation, software reconfiguration, interface morphing, security in mobile environments, etc.