Information Agents in Database Systems as a New Paradigm for Software Developing Process

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(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 9, No. 4, April 2011

Information Agents in Database Systems as a New
Paradigm for Software Developing Process.
Eva Cipi Betim Cico
department of informatics engineering, department of informatics engineering,
University of Vlora, Polytechnic University of Tirana,
Vlora, Albania, Tirana, Albania
eva.cipi@yahoo.com betim.cico@gmail.com

Abstract— This work aims at giving new possible solutions widely used in database applications? Can we add new
combining an information agents architecture and database services by setting new agents without compromising the
techniques in the management of information. We consider processing and time? Can we develop better solutions if we
agents as powerful tools for handling the systems’ complexity and build a new model by combining agents and data mining in
very efficient to bring modularity in software development. Here
database systems? In light of these questions we started to
is presented a case study of an agent-based architecture which
uses information agents dedicated to the specific tasks of the develop an application simulating a business environment.
business process management and other intelligent agents that We will note the performance of the system by observing
will try to extract the knowledge from databases and to offer agent behavior. The environment is a software component
intelligent decisions. shielding the agents from details of the real world and
providing the interfaces for perception, action and
Keywords- information agent; database system; software communication to the agents.[2] Modeling a software
development; multi-agent-based architecture; architecture is an essential step for the development of
complex systems, including Multiagent Systems (MAS).[3]
I. INTRODUCTION
Ideal solution is a logical value chain with different
This work is focused on designing a model of agent based components focused on providing the services required for
systems which will bring information agents as useful tools in handling time-variant information.[4]
management process of knowledge collection in order to gain
many advantages. Intelligent Agents are used for modeling III. INFORMATION AGENTS
simple rational behaviors in a wide range of distributed An “information agent” is a software agent that is closely
applications. Intelligent agents have received various, if not tied to a source or sources of data, as opposed to being tied
contradictory, definitions; by general consensus, they must closely to a human user’s goals (so called “interface agents”),
show some degree of autonomy, social ability, and combine or the processes involved in carrying out an arbitrary task (so
pro-active and reactive behavior [1]. First we discuss about called “task agents”).[5] In general such distinctions are
software agents and databases, the architectures that support necessarily part of a spectrum, but in this document we use the
traditional DBMS modules; and the need to integrate agent term “information agent” to denote a specific class of
techniques for the increase of the efficiency of knowledge. In implemented agents with certain input/process/output
general, Database Management Systems are known as passive behavior.[6] An information agent is an agent that has access
systems that become active only in response to requests from to at least one, and potentially many data sources, and is able
end users or application programs. A possible approach is to to collect and provide information obtained from these sources
make use of the information agent technology to add a reactive in order to answer queries given by users and/or other
capacity to the system that enables autonomous activity and information agents (the network of interoperating data sources
extensibility. Second we show a simulation that includes four are often referred to as intelligent and cooperative information
information agents that support four different tasks taking systems). The data sources may be of many types, including,
inputs from the same source and giving solutions as suggested for example, traditional databases as well as other information
messages. agents. Finding a solution to a query might involve an agent
accessing information sources over a network or a database.
II. RESEARCH OBJECTIVES
Information agent is an autonomous computational software
The research tries to show the relations between the agents entity that is especially meant to provide a proactive resource
and database techniques. We consider these relations very discovery, and to offer value-added information services and
useful because we believe the agents make their job much products. It is capable to provide transparent access to one or
faster and much better than other object. many different data sources. [7]
Several interesting questions arise in connection with the
current research: Can we find a good model which becomes
Identify applicable sponsor/s here. (sponsors)

31 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 9, No. 4, April 2011

Figure 1 describes the advantages of using information the efficiency of an agent?” Well it is very hard to make an
agents as powerful techniques for gathering information and agent to evaluate his performances. That’s why the man is the
using it to make good decisions in a brief time. one who establish a standard of what it means to be successful
in an environment and use it to measure the performance of
agents. The used architecture puts the agent between user
interface and DBMS. Users are represented by their agents in
the third layer. The purpose of the agents is to bring to the user
individualized information and relevant messages as good as
possible. To adapt its owner’s information demand the agent
collects message specific relevance evaluations given by its
owner.[10] The agents communicate through messages and
Figure 1. Information agent utilization advantages
evaluate information giving solutions for the user. In the
middle of the system there is an executive agent that has the
role to facilitate the communication between agents. It has also
IV. AGENTS AND DATABASE SYSTEMS the role to evaluate the performances of other agents and to
accept or to reject the registration of an agent into the agency.
The integration of both technologies would even increase
the complexity of the system. It would be imperative to V. CASE STUDY OF AN AGENT BASED SYSTEM IN
develop an architecture that is focused on finding one with a WAREHOUSE DATABASES
high level of abstraction that hides the complexity, with no For this case study we use agent based architecture and
direct consequences. The most powerful tools for handling tend to adapt it to the market environment. This architecture
things in software development are modularity and abstraction. uses information agents well defined to act and to do specific
[8] Agents represent a powerful tool for making systems actions of information management. The particularity of this
modular. If a problem domain is particularly complex, large, or architecture is the modularity: that means we can add other
unpredictable, then it may be that the only way it can agents specifying the task first. They extract and offer
reasonably be addressed is to develop a number of modular information in real time which can be used to take advantages
components that are specialized (in terms of their to make good decisions. The intelligent systems and especially
representation and problem solving paradigm) at solving a agent based systems can offer the needed tools for expertise
particular aspect of it. storing in a database management system.[11]
In such cases, when interdependent problems arise, the The case study will show that developing an agent based
agents in the system must cooperate with one another to ensure system on information management would be very useful. In a
that interdependencies are properly managed. In such domains, market environment of relationships between products, clients
an agent-based approach means that the overall problem can be and sellers there is a continuous exchange of information
partitioned into a number of smaller and simpler components, where the main requirement is the guarantee of the high level
which are easier to develop and maintain, and which are of service performance.[12]
specialized at solving the constituent sub problems.
A. DFD description
A. Architectures of information agents
In the figure 3. we present the Data Flow Diagram of the
In the Figure 2 there are three integration architectures agent based system. The system is based on database files
between agents and DBMSs: Layered, Integrated and Built-in. which store all the data. The agency is included in the
Each one of the three integration architectures has advantages Administration Software.
and disadvantages. Each agent needs to perform action to discover changes in its
environment. The agents can percept using queries (the
action). The DBMS (data software) accesses between agents
and database repository.
Through studying stakeholder requirements, we have
detected four services which the agents can cover successfully:
 Expertise of selling and inventory (selling agent)
 Display the changes of prizes (display agent)
Figure 2. Architectures for the integration of Agent Systems and DBMS
 Expertise order amounts (order agent)
The Layered architecture is the one implemented in most of  Suggestions of prices (price agent)
the existing approaches. An information agent is anything that
can be viewed as perceiving its environment through sensors
and acting upon that environment through effectors. [9] An
information agent is one that does the things like he percepts
them, analyzes them and based on these it acts without
remembering his history. A question is “how do we measure

32 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 9, No. 4, April 2011

many other factors that classify it as a critical system for the
business.

Figure 3. Data Flow Diagram of the agent based system.

We divide the module of Administration Software in these
functionalities made by developing four independent agents.
Figure 4 shows the data flow inside the system. The manager
needs information in two modes: off-line and on-line. Each
activated agent gives services and either offers suggestions on
prices or makes orders by detecting alert zones for every
record, or creates required reports, gives supply solutions, and
even shows the points where human service is needed. For
example, the visualization agent offers data to distribute in a
network of displays taking a map of coordinates for each
id_product.
B. The architecture. Figure 4. Example of the price agent algorithm
In order to save the modularity of the system, we use the
The approach taken gives another agent framework and has
layered architecture combined with build in architecture. We
a number of advantages coming from the artificial intelligence
think this is the best choice of three architectures in order to
world and standard object-oriented architectures. The adoption
develop and integrate new agents without implicating the
of Java guarantees a widely available, well supported
collection of autonomous agents with a particular expertise.
execution environment.
For example we can add a data mining agent. It can use data
that is already integrated. There are several actions that must VI. CONCLUSIONS AND FUTURE WORK
be made before the data gets to the data mining agent. These
At the end of this paper we give some consideration:
actions are: data cleaning, data integration, transformation and
pattern discovery. We will consider it in the future works.  This paper presents a model of database system
architecture that implements benefits of using agent
The algorithm in the figure 4 is used to present one of the
techniques and database management system. In the
agents: price agent. We activate the agent even though it process of studying different architectures, we have
conflicts its definition of the autonomy. The agent acts chosen the layered architecture in order to raise the
continuously asking the value of Control_parameter if it is level of abstraction.
positive or negative. The parameter is calculated by the agent
using data gathered from the relevant records. (see formula  We use unique method to develop independent
(1)). The agent can discover its environment in a second information agents where every agent has a specific
manner of perception: action.[13] It sends requests to the task to complete. Agents act independently,
DMBS and takes reports from the database for three variables nevertheless they can collaborate with users.
from each record:  We learned that distribution of functionalities to a
1. Daily_average(selling[i]) database system can be resolved very well using the
2. Expiry_date[i] information agent as an easy way to support database
3. Inventory[i] services complexity.
The agent offers the new price but it can not decide for a
new value confirmed. Here is the end of the agent task and the  We have developed four information agents
human operator can ignore or accept the decision of the agent. implementing the required functionalities. The results
given from the execution of simulation confirm the
The system is not completely independent because there are

33 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 9, No. 4, April 2011

validity of the model use. We show the simulation in repository for the standardized, integrated, and
the figure 5. validated data.
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 Our future work will try to extend the modularity of
system introducing intelligent agent to complete the
goals of the agency, always using one central

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