1. GRIDSpace: Semantic Grid Services on the Web — Evolution towards a SoftGrid
Oct 29 –
The International Conference on Semantics, Knowledge and Grid, Xi’ an, China
Tharam S. Dillon, Chen Wu, Elizabeth Chang
DEBI Institute, Curtin University of Technology, Australia

2. Agenda Introduction Overview of Technologies Motivation GRIDSpace
Grid Service
Semantic Grid
Web2.0
Motivation
GRIDSpace
Conceptual Model
Overall Architecture
Conclusion and future work

3. Introduction Distributed computing Observation Goal Grid computing
Open Grid Services Architecture (OGSA)
Semantic Grid
Web applications
SOA
IDC estimates that by 2010, 80% software profits from SOA
Observation
Three areas of research are separate
Grid Services, Semantic Grid, and Web2.0
Goal
Towards an organic Grid Ecosystems “on the Web”

4. Grid Services OGSA Alternative to OGSA, previous studies proposed:
Grid service: a potentially transient Web service based on Grid protocol expressed by WSDL (Comito et al. 2005)
“Transient” is the key
Grid: Virtual resource pool
Web services: End-to-end Functional invocation
Grid service requires extra “virtual” management
E.g. service instantiation, state management, etc.
provides Infrastructure Services, Data Services, Resource Management Services, Execution Management Services, Security Services, Self Management Services, and Information Services
Alternative to OGSA, previous studies proposed:
Grid-based Web services
Web-based Grid services

5. Semantic Grid Semantic Grid
an extension of the current Grid in which information and services are given well-defined meaning (Roure et al. 2005)
But how it can be realised?
Semantic Web + Semantic Web Services
Semantic Grid reference architecture (Corcho et al. 2006)
Principles for migrating from OGSA to Semantic Grid
Web Services Modelling Ontology and Web Services Modelling Language (Toma et al. 2006)
Semantic Space (Zhuge and Li 2007)

6. First, Grid resources must be formalised into services based on open standards,
Second, service composition is the key for applications and users
In current Web2.0 settings, service composition comes as the Mashup, Web applications that combine information from several sources and is provided through simple Web APIs. In Grid computing settings, we believe Mashup plays a key role in forming the Virtual Organisation,
Third, Grid users at varying levels (i.e. end users, scientists, professionals) shall all contribute to the Grid platform during their participation.

7. Adopting both the service-oriented and user-oriented strategy to approach this level of service state management gives rise to the notion of “Transient Virtual Organisation”, which involves the lifecycle management of self-organised, dynamic Service Space
The existing Web services architecture based on Remote Procedure Call (RPC) is not indeed “Web-oriented”, raised concern that “Web services do not have much in common with the Web” [16], and has potential weakness such as scalability, performance, flexibility, and implementability [17].
GRIDSpace architecture is motivated by four major factors – Soft aspect of Grid, service-orientation, transient service space, and Web-oriented architecture – that are built on top of Grid services, Service-Oriented Computing, Semantic Grid, and Web2.0.

8. Web 2.0 Web 2.0 is an attitude or philosophy
E.g. Using Web 2.0 for Service discovery (Wu and Chang 2007)
to think of Web as a platform of services
Applications are built by composing services
Users add “extra value” to these services through deeper level of participation for their own benefits
Creating values from making connections
Mashup is the key for value creation
Mashup helps to form Virtual Organisation
We differentiate
Service mashup (data level)
User mashup (meta-data level)

9. It provides infrastructure to enable service discovery and “mashup” at various levels.
Grid services within a Service Space are referred to as ‘members’ of that Service Space.
In GRIDSpace, we have identified and instantiated three types of Grid Service Spaces: OGSA Space, Semantic Grid Space, and Virtual Organisation

10. Thinking of Web as services
“If you hit the Amazon.com gateway page, the application calls more than 100 services to collect data and construct the page for you” (Gray, 2006)
Werner Vogels, Amazon CTO

11. Thinking of Web as a Value Chain
Many vivid examples “on the Web”
Google
eBay
Amazon

12. Motivation of GRIDSpace
Negligence of the “soft” aspect of the Grid computing, root cause:
Resources sharing vs. Service orientation
Resource: provided on the ‘as is’ basis, thus needs infrastructure to ‘push’ to the users
Service: provided on the ‘demand’ basis and has been ‘pulled’ from low level components or resources
OGSA attempts to bridge the gap through ‘transformation on the surface’
But we need radical solution to “soften” Grid
Incrementally value adding is the key
We envision a Grid that supports hardware, software, and software/hardware hybrid resources
It expands from the ‘middleware’ to a truly ‘SoftGrid’

13. Semantic Grid Space (SGS) refers to a focused Service Space where a group of related Grid services forms a domain-specific Grid service community in order to facilitate dependable collaboration through trust-driven service selection and semantic-based service discovery.
Transient Virtual Organisation (VO) is a demand- driven Service Space that allows a small group of Grid services to form an ad hoc team working collectively in order to fulfil particular user demands during a given period of time.
ad-hoc Grid service mashup – Grid service mediation, expansion, customisation, and integration are essential for a VO to satisfy real-world user requirements.

14. Conceptual Model for GRIDSpace
OGSA Space
Semantic Grid Space
Virtual Organisation
Grid Middleware Fabric
Applications
Grid Service
Grid Layer
Application Layer
Semantic Grid
Service Space Layer
Web
2.0

15. Architectural Design for GRIDSpace

16. Scientists can apply two approaches to semantically enrich existing Grid services.
The first top-down approach is based on the concept of ontology engineering [22], where scientists and domain experts manually annotate relevant Grid services using specific domain ontologies and/or knowledge databases.
The second empirical approach builds on practical methods such as data/text mining, business intelligence, machine learning that can be carried out (semi-) automatically without intensive human involvement.

17. Semantic Grid Space nurtures Grid services mainly through three means: semantic enrichment, semantic classification, and semantic discovery
rather than relying on the Service Broker, end users can also track down constantly-changing Grid services in any Service Spaces through the user-centred Grid Service Portal (GSP).
A GSP refers to a locally-accessible and highly-customisable user interface that provides a personalised view of activities and information essential to performing Service Space functions.
GSP acts as a proxy on behalf of the end users to maintain a list of communication channels to involved Service Spaces. Unlike a traditional HTTP proxy server shared by a group of corporate users, SSP is dedicated to serve only one user, thus creating the ‘user-centred’ view. SSP also reveals the notion of ‘User Mashup’– a core concept underpinning the attitude of Web2.0 [9].

18. Service Value Chain
Global Space
Domain Syndication
Dynamic Alliance

19. User Mashup (see Figure 3) in the context of GSP refers to an activity in which the user can ‘hack’ standard Service Space communication protocols, and hence extensively customises user interface or features based on his own preferences
User Mashup provides a powerful yet simple mechanism by which infinite ‘virtual’ syndications of Service Spaces can be created for each SSP.
A Virtual Syndication of Service Spaces is a fresh, highly filtered, and combinatory view of several Services Spaces within a GSP. It is created, customised, and solely owned by each individual SSP user and does affect other users

20. User-centred Grid Service Portal

21. Prototype
Some preliminary implementation work…

22. Global Space
Sparse matrix A for Grid Services Collection

23. Preliminary Prototype
Grid Service Syndication  Semantic Grid
A Cluster
Sim = 0.24
Semantic
Space for
WSDL

24. Preliminary Prototype
Grid Service User Mashup and Grid Portal

25. Future Work User-Centred SoftGrid Infrastructure Application
A Grid that can be used by users in daily life
Application
User provides/consumes values:
Data
Computation
Intelligence
Infrastructure provides:
Connection
Search
Mashup
Management

26. Conclusion Grid computing is about large-scale resource sharing
OGSA strives to integrate Grid with SOA
We advance the software middleware in OGSA towards the notion of software/hardware/hybrid
This leads to the GRIDSpace conceptual model and architectural design
We envision a truly SoftGrid in the near future

27. About Tharam S. Dillon
PhD in Electronic Engineering from Monash University
Professor of Digital Ecosystems and Business Intelligence Institute at Curtin University of Technology
Was Dean of Information Technology, University of Technology Sydney
Was Chair Professor of the Department of Computer Science and Computer Engineering at La Trobe University
Was Head of the School of Engineering at La Trobe University
Was Professor of Computing and Acting Head of the Department of Computing at Hong Kong Polytechnic University
Research interests: Distributed Computing, Business Intelligence, Data Mining, Neural Networks, XML-based Systems, Ontologies

28. Thank you! http://debii.curtin.edu.au