Data - Centered Software Architecture

Black board

Properties

Each knowledge source is relatively independent

Application Domain

Exhausted searching is impossible

Optimal, partial, or approximate solution is acceptable

Suitable for solving immature and complex AI problems

The problem spans multiple disciplines, each of which has
complete different knowledge expertise

Only interact and respond to the blackboard subsystem

They don’t need to interact with each other

Cons

Tight dependency between the blackboard and knowledge
source

Testing of the system is a challenge

Synchronization of multiple agents is an issue

Pros

Scalability: easy to add new knowledge source

Reusability of knowledge source agents

Concurrency: all knowledge sources can work in parallel

Repository

Cons

Overhead cost of moving data on network

Data store reliability and availability

High dependency between data structure of data store

Examples

CASE tools – IBM Rational Rose

Database management system

UDDI registry for Web Services

IDE (Interactive Development Endowment)

Clients of the data store are active

Client may access the repository

Its clients taking control of flow logic

Data store is passive

Variants of Data Repository

Virtual repository

Built up on the top of multiple physical repositories

Most DB allows users to create views that are virtual repositories
since they do not exist physically.

Benefits

Built up on the top of multiple physical repositories

Most DB allows users to create views that are virtual repositories
since they do not exist physically

Distributed repository system

All data are distributed over all sites linked by network

Data are replicated in order to