gCube Technology - Part 2: Excellence Contract n

1
gCube Technology - Part 2 ExcellenceContract
n RI-212488

• George Kakaletris - NKUA
• D4Science JRA Manager

www.d4science.eu
2
gCube - Part 2 ExcellenceOutline

• Excellence in gCube
• gCube as a whole
• Advanced concepts
• Service highlights
• Recent related publications
• Looking into the future

3
gCube Technology - Part 2 Excellence

• Completeness
• Openness

• Excellence in gCube
• gCube as a whole
• Advanced concepts
• Service highlights
• Recent related publications
• Looking into the future

4
gCube Completeness

• gCube is a complete platform encompassing
• Multilayered development framework
• Infrastructure enabling and aggregation layer
• Data infrastructure logic
• Multi-domain application-level logic
• User interface and end-user application enabler
• User interface and end-user application
• Most competing systems face a single sub-domain
• Distributed processing
• Federated/Distributed/Centralized Information
  Management/Retrieval
• Specific application

5
gCube Completeness A full view of gCube

• Information Retrieval Services
• Metadata Indexing
• Content Indexing
• Personalisation
• Content Source Description Selection
• Data Fusion
• Search

• Presentation Services
• Application Support Layer
• Portals
• User Portlets
• Administrative Portlets
• Desktop clients

• Information Organisation Services
• Storage Management
• Collection Management
• Content Management
• Metadata Management
• Archive Import
• Metadata Brokerage
• Annotation Management
• Content Transformation
• Ontology Management

• Enabling Elements
• Runtime Environment provision (gCore/gHN)
• Infrastructure Management, Monitoring and
  Self-reorganisation
• VRE Management
• VO and Security Support Services
• Process Execution

6
gCube Openness Specifications Technologies

• WS-
• WSRF
• X-
• Inc. several metadata formats (DC, TEI, ISO etc)
• WS-BPEL
• JSR (several)
• JDL
• Glue Schema (part)
• GSI-Security
• OpenSearch
• Java
• Globus Toolkit
• gLite
• Distributed under Open Source License
• EUPL

• Can comply with
• OAI-PMH
• OAI-ORE
• JSDL
• Considered / Upcoming
• WS-DAI
• OpenGIS - related

YEAR 2 EXTENDED
https//quality.wiki.d4science.research-infrastruc
tures.eu/quality/index.php/Standards
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gCube Technology - Part 2 Excellence

• Resource Model
• Scope
• Information Model
• Schema Independence

• Excellence in gCube
• gCube as a whole
• Advanced concepts
• Service highlights
• Recent related publications
• Looking into the future

8
A powerful Resource Model

• A powerful resource model
• Captures the full breadth of diverse resources
  found in gCube infrastructures (Data, Software,
  Services, Hardware, Configurations )
• Is Open
• allows new resource types to be defined /
  registered
• allows extending resource descriptors with
  arbitrary information
• is implemented and exploited over plain, WS-world
  common standards (xml/xquery)
• Software as a resource, for
• Handling of dependencies
• An extended model for software packaging
  dependencies
• Extension of dependencies into the Service domain
• Permits complex scenarios of collocation for
  performance
• Beyond even typical coexistence of component and
  services versions message routing
• Handling of state and logic semantics
• e.g. the Search Operator Profile
• Monitoring Management
• Current resource model is
• Partially derived by Glue Schema 1.3
• Gradually adopting concepts of Glue Schema 2.0

9
Resource Scoping

• An innovative concept for creating virtual
  applications
• Logically grouping resources into applications
• Key features
• Handles resource visibility orthogonally to
  security
• Can be applied even in unsecured (parametrically
  secured) infrastructures
• Exploits the same pool of principals (VO groups )
• Is transparent to services
• Handled entirely by the gCube container and gCore
• Is implemented through standards (formal soap
  header extensions)
• External entities can achieve interoperability
• More benefits
• Multi-scoping of resources
• Hierarchical propagation model (Infrastructure,
  VO, VRE)
• Common implementation methods for similar
  features
• API-bound awareness of scope
• Hard/costly to apply
• Inconsistency prone
• Security-bound access
• Complex to achieve similar results

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Information Model
(Resource) Properties

• Powerful Information Model
• Capable of implementing, yet chronologically
  preceding, OAI-ORE
• Schema agnostic data/information hosting
• Supports efficient storage retrieval
• Compliant with latest developments in Cloud
  infrastructures
• The key concepts
• Information Object
• Payload and properties
• Open property model
• Typed relationships
• Specialized semantics for VRE specific needs
• Two-level type hierarchy (type and subtype)
• Related concepts examples
• OAI-ORE Can be satisfied with minimal
  specialization
• Enhanced publications (DRIVER) Can be satisfied
  with reasonable specialization
• MPEG7 Multiple redirections required to capture
  multimedia object relationships

Collection
Properties
Information Object
Type / Subtype
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A Complex Information Object
Update Description Size
My ePrints
DC EN Descriptors of My ePrints
ISO GeoTagging of My ePrints
idb
idb
ipo
My Annotations
idb/iab
ipo
ipo
Some PDF
ipo
DESC 1 (DC)
DESC 3 (ISO)
ipo
ipo
idb
idb
DESC 2 (DC)
Updated URL MimeType
DESC 4 (ISO)
ipo
MyPDF
idb
idb
AN1
idb/iab
MyPDF JPEG Thumbnail
ipo/ar
ipo/ar
ipo
ipo
ipo
MyPDF In mp TIFF Format
Item 2 Data Set 2
Item 2 Data Set 3 (ext)
Item 2 Data Set 1
ipo is-part-of idb is-descr-by iab
is-annot-by ar altern-repres
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Schema Agnostic Data Management and Access

• No assumptions are made on schemas in any system
  layer / operation stage
• Import, hosting, retrieval, presentation
• Computational intelligence based and traditional
  tools are exploited for assisting
  interoperability
• Enabling features
• Flexible Information Model
• Schema unbound importing capacities
• Schema agnostic hosting services
• Schema unbound processing services
• Schema adapting presentation components
• Sibling technologies
• Federated Information Retrieval systems usually
  cope with single (or limited) (meta)data
  manifestations
• Widely known DLMSes diverge
• Some are bound to single metadata manifestation
  (usually a form of DC)
• Some cope with single schema for the majority of
  functionality, while alternative schemas can be
  second-class citizens
• Some can efficiently handle multiple schemas but
  luck full set of services for exploitation
• Data processing services
• Mostly schema-agnostic engines, but do not handle
  data all-the-way

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gCube Technology - Part 2 Excellence

• Information System
• Archive Import
• Data Transformation
• Indexing
• Data Processing
• Information Retrieval
• User Applications

• Excellence in gCube
• gCube as a whole
• Advanced concepts
• Service highlights
• Recent related publications
• Looking into the future

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The Information System

• Allows and facilitates resource creation,
  publication and monitoring
• Integrates with gLite infrastructures
• Supports the advanced, open, resource model of
  gCube
• Supports and enforces access scoping rules
• Offers WS-DAIX-like interface for document access
• XQuery 1.0 support for structured documents
• XCollection access for semi-structured documents
• Encompasses a robust, effective and efficient
  architecture
• Registry, Information Collector, Notifier
  Services
• Publisher Client Libraries
• Distributed replicated
• Single point of reference
• Capable of handling 100Ks updates per day

• Related technologies
• MDS4 IS builds on MDS4
• UDDI
• Limited subset of IS
• Target only to subset of resources handled by
  gCube and IS (i.e. Web Services)
• LDAP Servers
• Limited subset of IS
• Would require excessive changes to support
  introduced concepts that would overrule their
  benefits assumptions

YEAR 2 ARCHITECTURE REFINEMENT IMPLEMENTATION
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The Archive Import Service

• A highly customizable, modular data importing
  linking service
• Is operated via a fully fledged scripting
  language
• Is based on plug-ins
• Is bundled with a mini development environment
  for the support of complex imports
• Offers unrivalled archive importing capacities
• Goes beyond de-facto standards
• Capable of importing OAI-ORE entities and
  supporting gCube information model
• Compliant with, yet exceeding OAI-PMH capacities
• Several access protocols provided out of the box
  (premade plug-ins)
• FTP, HTTP, Local FileSystem,
• XML, HTML, binaries,

• Related technologies are protocol bound
• access and transportation
• manifestations
• e.g. XML/CSV, OAI-PMH

YEAR 2 ARCHITECTURE REFINEMENT IMPLEMENTATION
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The gCube Data Transformation Service

• gDTS A Computational Intelligence-based Metadata
  and Content Transformation Engine
• Automatic transformation path identification
• Minimal path length is favorable
• Fine-grained sub typing of formats (e.g.
  resolution, fps etc)
• Pluggable algorithms for content transformation
• Operation
• Inputs
• the targeted format (opt detailed specification)
• the source object (opt source format
  specification)
• Outputs
• Suitable transformation path(s)
• Target object
• Tested both on grid and cloud infrastructures
• Master worker model
• Dynamically adaptation of worker node population
• Common Use Cases
• Adopted Thumbnailing, Text extraction,
  Transcoding etc
• Future Watermarking, Feature extraction etc

• Related technologies usually
• Are specialized, on a limited set of formats
• Database data (tabular)
• Textual data (XML, CSV etc)
• A single group of formats (e.g. video, or image,
  binary documents)
• Are centralized

YEAR 2 ARCHITECTURE EXTENSION IMPLEMENTATION
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Metadata Content Indexing Services

• Goes beyond related technologies such as Digital
  Libraries and even web search
• Supersedes most IR systems that have singe or
  dual type indices
• Favored are Full text indices FWD indices
• Beyond typical indexing
• Feature indexing (implemented/not employed)
• Combined with feature extraction and distance
  calculators
• Support ranked geo-temporal queries
• Special compacting algorithm for FWD indices
• Combined metadata content ranking algorithms

• Offers multiple types of indexing
• Forward Indices, Full-Text, geospatial/temporal,
  XML, feature
• Arbitrary (typed) field indexing
• Distributed architecture
• Multiple lookup services per index
• Node index cache technology
• Notification based replication
• High performance achievements
• 10 to 300ms index access time (over SOAP)
• High level of failure endurance
• gCF assisted service state recovery
• SMS storage backend integrity assurance
• Bundled with large set of instruments
• gDTS integration
• AIS integration
• IR Bootstrapper component

YEAR 2 ARCHITECTURE REFINEMENT, NEW CONCEPTS
IMPLEMENTATION
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The data processing pipeline

• Layered architecture
• Execution engine (complete)
• Workflow engine (partial)
• Workflow presentation systems (Not integrated)
• Multi-mode operation
• In-process, Intra-process, Intra-node
• Multi-protocol logic execution
• Executables (native, scripts)
• POJOs Native Javas (engine context)
• Web Services (WS, WSRF) HTTP APIs
• Multi-infrastructure (gLite, Hadoop, gCube, )
• Supports Elastic Cloud management application
• Large data set exchanges the gRS
• Workflow engine
• Favors optimisation over matching, the typical
  grid approach

• Related Technologies
• Condor Pegasus
• No native handling of heterogeneous techs
• Single infrastructure
• Match-based plans
• Limited control artefacts
• OGSA-DAI, DPQ
• Mostly data oriented
• Minimal optimisation capacities
• Single infrastructure
• Single protocol
• Minimal control artefacts
• Map-Reduce infrastructures
• A single model of processing embedded in
  processors

YEAR 2 RE-DESIGN IMPLEMENTATION
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Information Retrieval Services beyond typical
lookups

• All in one
• Built in capacities for federation (DIR
  components operators)
• Internally employed for collection selection
• Unlimited capacities for custom processing
• Fully featured
• Sorting
• Filtering
• Fusion / Merging
• Projection
• Custom source access
• Custom processing

• Related Technologies (IR systems)
• Directly invoke indices (no further processing
  capacities)
• Even re-sorting can be hard
• Exploit single predefined manifestation or are
  customizable upon a single custom manifestation
• The cons of our approach
• Impact on performance

YEAR 2 IMPLEMENTATION REFINEMENTS EXTENSION
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An example of Information Retrieval LifeCycle in
gCube
AIS
gDTS
Preprocessors
PP3
CSS
Search Operators
NLP
IDX Lookup 1
IDX Lookup 2
PES
Search Engine
Sort
Fuse
W/F
Parse
Pre-process
Planer
Project
Fetch Metadata
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gCube Technology - Part 2 Excellence

• The Process Execution Engine
• The plug-ins concept
• On-demand VREs
• The gCF

• Excellence in gCube
• gCube as a whole
• Advanced concepts
• Service highlights
• Recent related publications
• Looking into the future

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Papers

• The Process Execution Engine
• Dataflow Processing and Optimization on Grid and
  Cloud Infrastructures, M. Tsangaris et
  Al,Bulletin of the IEEE Computer Society
  Technical Committee on Data Engineering, Vol. 32
  No. 1, March 2009
• Nefeli Hint-based Execution of Workloads in
  Clouds, K. Tsakalozos et Al, Published ICDCS
  2010 The 30th International Conference on
  Distributed Computing Systems
• The gCF
• Taming development complexity in
  service-oriented e-Infrastructures the gCore
  application framework and distribution for
  gCube, Pagano, P et Al, Zero-In e-Infrastructure
  News Magazine

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Papers

• The plug-ins concept
• Functional adaptivity for Digital Library
  Services in e-Infrastructures the gCube
  Approach, Simeoni, F. et al 13th European
  Conference on Research and Advanced Technology
  for Digital Libraries, ECDL 2009, 2009
• Matchmaking for Covariant Hierarchies, Simeoni,
  F. Lievens, D., ACP4IS '09 Proceedings of the
  8th workshop on Aspects, components, and patterns
  for infrastructure software. 2009
• On-demand VREs
• On-demand Virtual Research Environments and the
  Changing Roles of Librarians, Candela, L. et Al,
  Library Hi Tech, 2009, 27, 239-251
• An Extensible Virtual Digital Libraries
  Generator, Assante, M. et Al, 12th European
  Conference on Research and Advanced Technology
  for Digital Libraries, ECDL 2008, Aarhus,
  Denmark, September 14-19, Springer, 2008, 5173,
  122-134

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gCube Technology - Part 2 Excellence

• Future work
• D4Science II
• Beyond

• Excellence in gCube
• gCube as a whole
• Advanced concepts
• Service highlights
• Recent related publications
• Looking into the future

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Future work

• Interoperability (D4Science-II)
• Extend standards adoption
• Promote specs into standardisation bodies
• Focus on interoperating with other, widely
  adopted systems
• Improve information retrieval features
• New roles for ontologies (D4Science-II)
• NLP features extension
• Further performance improvements
• Extend security concepts
• On interoperability (D4Science-II)
• Support uniformly fine-grained security policies
  for all resources and Information Objects

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Future work

• Process Execution
• Elastic cloud management integration
• Objectives-based process execution
• Without dismissal of previous assumptions of
  generality
• Multi e-infrastructure aggregation (D4Science II)
• Unification with Data Transformation Services and
  Information Retrieval
• Extensive multimedia handling
• Decomposition/Composition to/from gCube
  Information model
• Feature extraction indexing for Retrieval

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SUPPLEMENTARY
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gRS

• Large data set exchange the gRS
• Formalizes the exchange of large data sets in web
  services (paging, store forward, throttling /
  flow control)
• Adds the by-ref notion to data exchanged via
  services
• Confronts several performance issues of WS
  interactions
• Faster than observed similar OGSA-DAI data
  transfers
• Already ported to other implementations disjoint
  to D4Science
• gRS2 a full in-process to across-machine
  communication and data exchange mechanism
• Boosts performace

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Process Execution on Grid Cloud

• Dataflow Processing and Optimization on Grid and
  Cloud Infrastructures
• Authors M. Tsangaris, G. Kakaletris, H. Kllapi,
  G. Papanikos, F. Pentaris, P. Polydoras, E.
  Sitaridi, V. Stoumpos, Y. Ioannidis
• Published Bulletin of the IEEE Computer Society
  Technical Committee on Data Engineering, Vol. 32
  No. 1, March 2009
• Abstract Complex on-demand data retrieval and
  processing is a characteristic of several
  applications and combines the notions of querying
  search, information filtering retrieval, data
  transformation analysis, and other data
  manipulations. Such rich tasks are typically
  represented by data processing graphs, having
  arbitrary data operators as nodes and their
  producer-consumer interactions as edges.
  Optimizing and executing such graphs on top of
  distributed architectures is critical for the
  success of the corresponding applications and
  presents several algorithmic and systemic
  challenges. This paper describes a system under
  development that offers such functionality on top
  of Ad-hoc Clusters, Grids, or Clouds. Operators
  may be user defined, so their algebraic and other
  properties as well as those of the data they
  produce are specified in associated profiles.
  Optimization is based on these profiles, must
  satisfy a variety of objectives and constraints,
  and takes into account the particular
  characteristics of the underlying architecture,
  mapping high-level dataflow semantics to flexible
  runtime structures. The paper highlights the key
  components of the system and outlines the major
  directions of its development.

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Process Execution The Cloud

• Nefeli Hint-based Execution of Workloads in
  Clouds
• Authors Konstantinos Tsakalozos, Mema
  Roussopoulos, Vangelis Floros and Alex Delis
• Published ICDCS 2010 The 30th International
  Conference on Distributed Computing Systems
  http//icdcs2010.cnit.it/
• Abstract Virtualization of computer systems has
  made feasible the provision of entire distributed
  infrastructures in the form of services. Such
  services do not expose the internal operational
  and physical characteristics of the underlying
  machinery to either users or applications. In
  this way, infrastructures including computers in
  data-centers, clusters of workstations, and
  networks of machines are shrouded in clouds.
  Mainly through the deployment of virtual
  machines, such networks of computing nodes become
  cloud-computing environments. In this paper, we
  propose Nefeli, a virtual infrastructure gateway
  that is capable of effectively handling diverse
  workloads of jobs in cloud environments. By and
  large, users and their workloads remain agnostic
  to the internal features of clouds at all times.
  Exploiting execution patterns as well as
  logistical constraints, users provide Nefeli with
  hints for the handling of their jobs. Hints
  provide no hard requirements for application
  deployment in terms of pairing virtual-machines
  to speci?c physical cloud elements. Nefeli helps
  avoid bottlenecks within the cloud through the
  realization of viable virtual machine deployment
  mappings. As the types of jobs change over time,
  deployment mappings must follow suit. To this
  end, Nefeli offers mechanisms to migrate virtual
  machines as needed to adapt to changing
  performance needs. Using our prototype system, we
  show signi?cant improvements in overall time
  needed and energy consumed for the execution of
  workloads in both simulated and real cloud
  computing environments.

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On the idea of plug-ins

• Functional adaptivity for Digital Library
  Services in e-Infrastructures the gCube Approach
• Authors Simeoni, F. Candela, L. Lievens, D.
  Pagano, P. Simi, M. Agosti, M. Borbinha, J.
  Kapidakis, S. Papatheodorou, C. Tsakonas, G.
  (ed.)
• Published 13th European Conference on Research
  and Advanced Technology for Digital Libraries,
  ECDL 2009, 2009
• Abstract We consider the problem of
  e-Infrastructures that wish to reconcile the
  generality of their services with the bespoke
  requirements of diverse user communities. We
  motivate the requirement of functional adaptivity
  in the context of gCube, a service-based system
  that integrates Grid and Digital Library
  technologies to deploy, operate, and monitor
  Virtual Research Environments defined over
  infrastructural resources. We argue that
  adaptivity requires mapping service interfaces
  onto multiple implementations, truly alternative
  interpretations of the same functionality. We
  then analyse two design solutions in which the
  alternative implementations are, respectively,
  full-fledged services and local components of a
  single service. We associate the latter with
  lower development costs and increased binding
  flexibility, and outline a strategy to deploy
  them dynamically as the payload of service
  plugins. The result is an infrastructure in which
  services exhibit multiple behaviours, know how to
  select the most appropriate behaviour, and can
  seamlessly learn new behaviours.

32
On the idea of plug-ins

• Matchmaking for Covariant Hierarchies
• Authors Simeoni, F. Lievens, D.
• Published ACP4IS '09 Proceedings of the 8th
  workshop on Aspects, components, and patterns for
  infrastructure software. 2009
• Abstract We describe a model of matchmaking
  suitable for the implementation of services,
  rather than their composition. In the model,
  processing requirements are modelled by client
  requests and com- putational resources are
  software processors that compete for re- quest
  processing as the covariant implementations of an
  open service interface. Matchmaking then relies
  on type analysis to rank processors against
  requests in support of a wide range of dispatch
  strategies. We relate the model to the
  autonomicity of service provision and briefly
  report on its deployment within a
  production-level infrastructure for scientific
  computing.

33
On VREs (Librarians)

• On-demand Virtual Research Environments and the
  Changing Roles of Librarians
• Authors Candela, L. Castelli, D. Pagano, P.
• Published Library Hi Tech, 2009, 27, 239-251
• Abstract The aim of this paper is to discuss how
  new technologies for supporting scientific
  research will possibly influence the librarians
  work. The discussion is conducted in a context
  that takes into account the emergence of
  e-infrastructures as means to realise a new model
  of producing, using and sharing information
  resources and even to change the concept of
  information resource itself. At the core of this
  innovation there are virtual research
  environments, i.e. evolved versions of the
  current research libraries. The environments
  provide scientists with collaborative and
  customised environments supporting results
  production and exchange around the globe in a
  cost-efficient manner. The experiences made with
  these innovative research environments within the
  D4Science project is reported. On the basis of
  this experience, possible professional profiles
  are suggested for librarians working in these new
  evolved research libraries.

34
On VREs (Intantiation)

• An Extensible Virtual Digital Libraries Generator
• Assante, M. Candela, L. Castelli, D. Frosini,
  L. Lelii, L. Manghi, P. Manzi, A. Pagano, P.
  Simi, M.
• Christensen-Dalsgaard, B. Castelli, D. Jurik,
  B. A. Lippincott, J. (ed.)
• Published 12th European Conference on Research
  and Advanced Technology for Digital Libraries,
  ECDL 2008, Aarhus, Denmark, September 14-19,
  Springer, 2008, 5173, 122-134
• Abstract In this paper we describe the design
  and implementation of the VDL Generator, a tool
  to simplify and automatise the Digital Library
  development process. In particular, we discuss
  how our approach to the realisation of this tool
  simplifies the task of implementing, extending
  and modifying such a fundamental component. This
  tool models its issue as a generic search problem
  that can easily be adapted to different
  application scenarios. In particular, to
  guarantee its extensibility we carefully
  identify, isolate and organise the VDL Generator
  constituents, i.e. (i) the set of logical
  components that can be used when designing a
  Digital Library, (ii) the set of physical
  components that by implementing the logical
  components contribute to implement the Digital
  Library and (iii) the search strategy exploited
  to accomplish the generation task. Furthermore,
  we report on the experiences matured in
  implementing and exploiting such an innovative
  service in the context of the Diligent EU funded
  project and discuss future plans for its
  consolidation.

35
On gCore

• Taming development complexity in service-oriented
  e-Infrastructures the gCore application
  framework and distribution for gCube
• Authors Pagano, P. Simeoni, F. Simi, M.
  Candela, L.
• Published Zero-In e-Infrastructure News
  Magazine, EU FP7 Funded Project BELIEF-II, 2009,
  1, 19 21 http//www.beliefproject.org/zero-in/ze
  ro-in-first-edition-emagazine/taming-development-c
  omplexity-in-service-oriented-e-infrastructures
• Introduction e-Infrastructure is the term coined
  for innovative research environments that provide
  modern scientists with seamless access to shared,
  distributed and heterogeneous resources. Within
  this domain, service-orientation is a common
  assumption where it provides a common abstraction
  to hardware, data and even application services
  as shareable resources. This approach, however,
  complicates resource management, since
  deployment, configuration, staging, scoping,
  monitoring and secure operation of services
  become fully dynamic and a responsibility of the
  infrastructure. To fulfill this responsibility,
  infrastructures must be clear as to the
  description and run-time behaviour of services.
  This adds to the complexity typically associated
  with service development, whether generically
  related to distributed programming (e.g.
  concurrency, performance-awareness, and tolerance
  to partial failure) or specifically introduced by
  open technologies (e.g. reliance upon multiple
  standards, limited integration and documentation
  of development tools). This complexity challenges
  the operation, maintenance, evolution and
  thirdparty extension of the infrastructure,
  ultimately threatening its adoption.

36
IS Operation
gLite Infrastr.
gCube Service
gLiteBridge Service
WS-Notification PT
Notification
ISNotification Lib
Profile
ISPublisher Lib
Stateful WS-Resource
Aggregator Source
ISPublisher Lib
Profile
Registration PT
GCUBEResource Parsers Lib
ISPublisher Lib
ISClient Lib
Registry Service
RPD
ISNotification Lib
Notifier Service
WS-Topics
RPD
Stateful WS-Resource
Notification
gHN
Aggregator Source
ISPublisher Lib
XQueryAccess PT
IC Service
Aggregator Sink
WS-ServiceGroup
Aggregator Sink
Exist Common Lib
Exist 1.2
37
gCube Resource Model
38
Versioning in SOA

• Service oriented versioning seen only in
  advanced desktop systems
• Issues not solved yet in mainstream platforms
  like Java
• Is based on formalization and exploitation of the
  version semantics of WS
• Is supported by
• the resource model
• the s/w production cycle
• Allows smooth evolution of a production
  establishment
• Impacts positively the long term stability of the
  system
• Goes beyond typical coexistence of services
• Side-by-side deployment of several versions of
  the same service
• Transparent routing of client messages to
  appropriate producers

39
Highlights of technological excellence in
end-user applications

• TimeSeries Management
• The objective on-line curation of time series
• Go beyond common practice of desktop applications
  for efficient curation and face the challenge of
  large data size management over web interface
• Scientific Reporting
• Go beyond the practice on structured information
  stores and fixed data types
• Achieve integration of diverse platform services
  with templated report definition and production
• Dynamic document creation
• Complex information object
• Storage
• Metadata generation
• Indexing
• Workspace
• Achieve integration of a collaborative workspace
  with the content repository and information
  retrieval capacities of the platform, offering
  access to diverse virtual (e.g. queries) and
  compound objects

YEAR 2 ARCHITECTURE IMPLEMENTATION