Data-Centered
Architecture
In data-centered architecture, the data is centralized and
accessed frequently by other components, which modify data. The main purpose of
this style is to achieve integrality of data. Data-centered architecture
consists of different components that communicate through shared data
repositories. The components access a shared data structure and are relatively
independent, in that, they interact only through the data store.
The most well-known examples of the data-centered architecture is
a database architecture, in which the common database schema is created with
data definition protocol – for example, a set of related tables with fields and
data types in an RDBMS.
Another example of data-centered architectures is the web
architecture which has a common data schema (i.e. meta-structure of the Web)
and follows hypermedia data model and processes communicate through the use of
shared web-based data services.
Types of Components
There are two types of components −
· A central
data structure or data store or data repository, which is responsible
for providing permanent data storage. It represents the current state.
· A data
accessor or a collection of independent components that operate on the
central data store, perform computations, and might put back the results.
Interactions or communication between the data accessors is only
through the data store. The data is the only means of communication among
clients. The flow of control differentiates the architecture into two
categories as Repository Architecture Style and Blackboard
Architecture Style. A brief detail about both the categories is given below
−
Repository Architecture Style
In Repository Architecture Style, the data store is passive and
the clients (software components or agents) of the data store are active, which
control the logic flow. The participating components check the data-store for
changes.
A client sends a request to the system to perform actions (e.g.
insert data). The computational processes are independent and triggered by
incoming requests. If the types of transactions in an input stream of
transactions trigger selection of processes to execute, then it is traditional
database or repository architecture, or passive repository. This approach is
widely used in DBMS, library information system, the interface repository in
CORBA, compilers, and CASE (computer aided software engineering) environments.
Advantages
Repository Architecture Style has following advantages −
· Provides
data integrity, backup and restore features.
· Provides
scalability and reusability of agents as they do not have direct communication
with each other.
· Reduces
overhead of transient data between software components.
Disadvantages
Because of being more vulnerable to failure and data replication
or duplication, Repository Architecture Style has following disadvantages −
· High
dependency between data structure of data store and its agents.
· Changes
in data structure highly affect the clients.
· Evolution
of data is difficult and expensive.
· Cost
of moving data on network for distributed data.
Blackboard Architecture Style
In Blackboard Architecture Style, the data store is active and its
clients are passive. Therefore the logical flow is determined by the current
data status in data store. It has a blackboard component, acting as a central
data repository, and an internal representation is built and acted upon by
different computational elements.
Further, a number of components that act independently on the
common data structure are stored in the blackboard. In this style, the
components interact only through the blackboard. The data-store alerts the
clients whenever there is a data-store changes. The current state of the
solution is stored in the blackboard and processing is triggered by the state
of the blackboard.
When changes occur in the data, the system sends the notifications
known as trigger and data to the clients. This approach is
found in certain AI applications and complex applications, such as speech
recognition, image recognition, security system, and business resource
management systems etc.
If the current state of the central data structure is the main
trigger of selecting processes to execute, the repository can be a blackboard
and this shared data source is an active agent.
A major difference with traditional database systems is that the
invocation of computational elements in a blackboard architecture is triggered
by the current state of the blackboard, and not by external inputs.
Parts of Blackboard Model
The blackboard model is usually presented with three major parts −
Knowledge Sources (KS)
Knowledge Sources, also known as Listeners or Subscribers are
distinct and independent units. They solve parts of a problem and aggregate
partial results. Interaction among knowledge sources takes place uniquely
through the blackboard.
Blackboard Data Structure
The problem-solving state data is organized into an
application-dependent hierarchy. Knowledge sources make changes to the
blackboard that lead incrementally to a solution to the problem.
Control
Control manages tasks and checks the work state.
Advantages
Blackboard Model provides concurrency that allows all knowledge
sources to work in parallel as they independent of each other. Its scalability
feature facilitates easy steps to add or update knowledge source. Further, it
supports experimentation for hypotheses and reusability of knowledge source
agents.
Disadvantages
The structural change of blackboard may have a significant impact
on all of its agents, as close dependency exists between blackboard and
knowledge source. Blackboard model is expected to produce approximate solution;
however, sometimes, it becomes difficult to decide when to terminate the
reasoning.
Further, this model suffers some problems in synchronization of
multiple agents, therefore, it faces challenge in designing and testing of the
system.