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