Uwe Schwiegelshohn 17. Februar 2009

1. Layers in Grids Uwe Schwiegelshohn 17. Februar 2009 Dagstuhl, February 16, 2009 Layers in Grids

2. Advanced Scientific Domains Computational Physics System Engineering Computational Bio-medicine Local User Local User Virtual Simulation & Exploration Environment (ViSE) Communication & collaboration (ComCol) Virtual-lab Information Management for Cooperation (VIMCO) Physical apparatus Distributed Computing & Gigabit Local Area Network ViSE Net Client App. User MRI/CT Internet 2 Wide Area Network Philosophical Structure of ViroLab Courtesy of Peter Sloot Dagstuhl, February 16, 2009 Layers in Grids

3. Actual Structure of ViroLab Clinical Virologist Experiment developer Users Scientist Experiment Planning Environment Experiment scenario Patient Treatment Support Interfaces ViroLab Portal Virtual Laboratory runtime components (Required to select resources and execute experiment scenarios)‏ Community Runtime Computational services (services (WS, WTS, WS-RF), components (MOCCA), jobs (EGEE, AHE))‏ Data services (DAS data sources, standalone databases)‏ Services Virtualization Grids, Clusters, Computers, Network Infrastructure Hardware, OS Middleware: basic services, brokerage Courtesy of Marian Bubak Dagstuhl, February 16, 2009 Layers in Grids

4. Organization Layers Users Physics Medicine Finance Community/ VOs Support, Security,… Operation Services / Resources Dagstuhl, February 16, 2009 Layers in Grids

5. Simple Structure Dagstuhl, February 16, 2009 Layers in Grids

6. Easy Replacement Version 1.3 Version 1.5 Dagstuhl, February 16, 2009 Layers in Grids

7. (Double) Cone Structure Dagstuhl, February 16, 2009 Layers in Grids

8. Where to use layers in Grids? Organization, technology Relation between different layer architectures Correspondence between a layer in organization and a layer in technology? How many layers? As many as necessary, as few as possible Integration into existing layer structures Software layers, organizations Assignment of tasks to layers Interface between layers Tools to support the use of layers Questions Dagstuhl, February 16, 2009 Layers in Grids

9. Bypassing of layers see IP/TCP No generalized requirement, see security Distinction between implementation layers and structural layers Using attributes for distinction Distinction between functional and non functional properties Monitoring , control and steering of non functional properties Clean structure of service provisioning Easy replacement is not always possible: difference between internal changes and functional modifications Experience from the past in using layers LHC: baseline services <-> high level services: functional requirements Organizational question: responsibility Standard uses case for establishing a new community? Generalization of virolab Different approaches: service based, component based Collection of functions, no contradiction: a service in a layer will add something to a layer, the abstraction of a given layer can be implemented by different components. Discussion Dagstuhl, February 16, 2009 Layers in Grids

10. The classic layer approach does not work: Bottom up allocation Alternative approach: Definition of processes and mapping of these processes to “layers” Requirement to change the layering (layers are vehicles to master complexity) Example: issues in self * properties Layers are not implementation prescriptions, they are abstractions Achieving of layers: Minimizing the number of interfaces (economy) “New” dimension of problems in the data domain Annotation, similar problems occur in the commercial domain Necessity of many levels of data and its derivation. This must be supported. Layers are about responsibility Maturity matters: After a system is mature less layers may be necessary. Handling of failures Mapping of failures to the organizational structures Discussion Dagstuhl, February 16, 2009 Layers in Grids

11. Communication across layers Monitoring and tracking of the process flow across the layers as long as the flow stays within the system: system responsibility Failure handling, accounting, performance improvement, quality assurance Consistency of results with the actual data, not a new problem but a new dimension of the problem: key property of the scientific approach Service quality Coordination of complex tasks SLA management The top layer must understand the whole structure or each decision has to be percolated up to the top structure: multicriteria Management structure: community specific -> example virolab Parallel support layers: machines, services support different (all) communities Network operation maps to the virolab layer picture Discussion Dagstuhl, February 16, 2009 Layers in Grids