KNOWLEDGE GRIDS

Akshat MishraGRID SEMINAR WINTER 2008

Feb 2008

KNOWLEDGE GRIDS

• A multinational financial organization has data repositories in various locations allover the world

• The company performs data mining operation such as clustering classification and other knowledge discovery procedures.

• It uses data ming tools for knowlege discovery but faces problem doing co-ordinated work with all its centres.

DISTRIBUTED MINING

• Parallel platforms were used .• Implementing this task on geographically

distributed sites was a challenge• Grid computing could be a possible solution • How could it be done?

Evolution of Data Grids.

• Data Grids store large data sets and are moved with the same ease like files.

• Data Grids evolved into knowledge grid to aid distibuted high performance computation.

• Along with the basic infrastructure of a grid, provided tools for knowledge discovery.

• Knowledge Grids are distributed paralled software architecture supporting knowledge discovery

• Fig

ARCHITECTURE OF KNOWLEDGE GRID

Fig. 1. KNOWLEDGE GRID architectureDistributed Data Mining on Grids:Services Tools and Applications

ARCHITECTURE OF KNOWLEDGE GRID

• Two main services of Core-K Grid layer• Knowledge discovery services• Extends the globus monitoring

service ,manages metadata• The metadata include tools and resources to

be mined.• Mining Tools and algorithms are also mined• Distributed execution plans

ARCHITECTURE OF KNOWLEDGE GRID

• RAEMS(Resoe allocation and exection management services)

• To find suitable mapping between execution plan and available resources

• The goal is to satisfy application requirements• The layer can also use the facility of GRAM

ARCHITECTURE OF KNOWLEDGE GRID

• HIGHER LEVEL K GRID LAYER• DAS(Data Access Service)• DAS is reponsible for

searching ,selecting ,extracting,transforming and deleivering data to be mined

• It is based on user requirement• TAAS(Tools and algorithms access service)• TAAS is responsible for downloading algos &

tools

ARCHITECTURE OF KNOWLEDGE GRID

• EPMS(Execution plan management Service)• An execution plan is represented by graph• Graph describes data flow.• It is performed by a semi automatic tool• The tool takes data and programs selected by

the user and generates an abstract exectution plan

• Finally RPS analyzes the result pattern

Design proces of Data Mining

• fig2

Fig. 2. Design process of a data mining computationDistributed Data Mining on Grids: Services Tools and Applications

VEGA SOFTWARE MODULES

Vega Software ModulesDistributed Data Mining on Grids: Services Tools and

Applications

GRAPHICAL REPRESENTATION

• Visual Interface of VegaDistributed Data Mining on Grids: Services Tools and Applications

FIGURE 3 :Dis

AN EXAMPLE

WORKSPACE 1DISTRIBUTED DATA MINING ON GRIDS:SERVICES TOOLS AND APPLICATIONS

Another defintion of Knowledge Grid

• According to H.Zhuge knowledge grid is an intelligent sustainable internet application that enables people or virtual roles to effectively capture ,publish ,share and manage explicit knowledge resources

• It also provides on demand services to support innovation cooperative teamwork ,problem solving and decision making.

WHY KNOWLEDGE GRID

•Evolving of Internet meant that the number of pages kept on increasing•Info in the form blogs, forums etc are exploding on the net•The large explode of informaiton meant there is need to have a information service that spans over an administrative domain.

Evolving concept

• An emerging technology and evolving concept• Google ---->SEARCH ENGINE• YAHOO----->INDEXING INFORMATION ON THE

BASIS OF CATEGORY• Semantic web --->provides services along with

information services

References• Distributed Data Mining on Grids:Services Tools and

applicatios ,• IEEE TRANSACTIONS ON Systems,MAN and

Cybernetics,Vol 34,No6,December 2004• The knowledge grid,By Mario Cannataro and

Domenico Talia• http://en.wikipedia.org/wiki/Knowledge_Grid• A knowledge grid model and and platform for global

knowledge sharing By H.Zughe• Grid Portals By Fugang Wang• http://cyberaide.googlecode.com/svn/trunk/lectures/

GridPortal.ppt