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Data-Centered Software Architecture (Blackboard (Domain (solving immature …
Data-Centered Software Architecture
Overview
A centralized data store that is shared by all surrounding software components
Components
Data Store
Software Component Agents
Blackboard
Flow of logic
New data -> trigger event -> knowledge source take action -> response to event -> new data -> change logic flow
Determined by current data status -----> Data driven
Domain
solving immature - complex AI problems
The problem spans multiple disciplines
Optimal, partial, or approximate solution is acceptable
Exhausted searching is impossible.
Consist of
Knowledge Source -> stores domain specific knowledge
Controller -> init above
Blackboard -> store data
Pros
Concurrency
Scalability
.....
Client: inactive/passive
Datastore: active
Cons
Repository
Pros
Scalability + Reusability
Integrity: easy to backup/restore
Cons
High dependency
Cost
Reliability + Availibility
Domain
Data transactions drive the control flow
large complex information system
...
Data store: passive
Client: active
Control flow logic
Access Repository via
Public Diagram
Interactively
By client
Variants
Distributed repository system
(distributed database system)
Data are replicated ---> Improve reliability and local accessibility
All data are distributed over all sites linked by network
Virtural Repository
== view in DB -> Simplify DB structure
Security management
On top of physical repository