Multi-Agent Architecture for Distributed IT GRC Platform

Abstract— The IT-GRC platform is a solution that is based on
the paradigm of distributed systems, based on multi-agent systems
(MAS) in its different parts namely the user interface, the static
and dynamic configuration of the organization management
profiles, the choice of the best repository and the processing of
processes, it takes advantage of the autonomy and learning aspect
of ADMs as well as their high-level communication and
coordination. However, these technological components are
difficult to manipulate, or users lack the necessary skills to use
them correctly. In this situation, the modeling of a communication
architecture is necessary, in order to adapt the functionalities of
the platform to the needs of the users. To help achieve these goals,
it is necessary to develop a functional and intelligent
communication architecture, adaptable and able to provide a
support framework, allowing access to system functionalities
regardless of physical and time constraints.
Index Terms—Multi-agent systems, IT GRC, frameworks, best
practices, communication system, distributed system, information
system.
I. INTRODUCTION
aced with a competitive market for IT solutions,
information systems are made up of heterogeneous
components, with increasingly complex information flows
and processes. The decision of stakeholders in the area of IT
governance has become sensitive. Hence the need for adequate
tools of IT governance.
The modeling of an IT GRC platform must take into account
several parameters. First, the system must ensure and evaluate
the alignment of the business objectives of the company with
the objectives and strategy SI. Then, it must choose the best
reference framework for the Governance, Risk and Compliance
of Information Systems. This repository of good practices
aligns the strategy of information systems through a set of
guidelines that serve as benchmarks for business processes.
The platform of governance, risk management and information
systems compliance that we proposed in a previous work,
communicates with the stakeholders of the IS, namely the
Director of Information System (DSI) and the Business
Managers from each department. It has an intelligent semantic
engine that allows translating the objectives expressed by its
users, in language understandable by the most widespread
March 5, 2018
S. ELHASNAOUI, with LPRI Laboratory, EMSI, Casablanca, Morocco, and
with LRI Laboratory, Systems architecture team, Hassan II University,
Casablanca, Morocco (elhasnaoui.soukaina@gmail.com)
reference systems (COBIT, ITIL, PMBOK, ISO27001,
ISO27002, ISO27005, MEHARI, and EBIOS). In order to
implement the appropriate IT GRC processing, a multi-criteria
decision system is integrated, making it possible to choose the
best repository for a given request. Our IT GRC platform
encapsulates each repository into an expert system for end-to-
end evaluation in an interactive way with the user. These
repositories are updated each time a new version of these has
appeared.
The IT GRC platform is composed of several systems that
lead to good governance. Each of these systems is responsible
for performing specific tasks:
• EAS-Strategic: aligns the business needs of the company
with IT objectives and IT processes;
• EAS-Decision: receives the IT objectives expressed by
EAS-Strategic. It is able to choose for a request from the
strategic layer the best reference for IT governance, risk
management and compliance;
• EAS-Processing: encapsulates each IT GRC repository in an
intelligent and autonomous system that deploys the actions and
implements all the recommendations of the best repository
chosen by EAS-Decision in an interactive way, which allows to
manage the activities desired end-to-end IT processes and
generate action plans.
However, these technological components are difficult to
manipulate, or users lack the necessary skills to use them
correctly. In this situation, the modeling of a communication
architecture is necessary, in order to adapt the functionalities of
the platform to the needs of the users. To help achieve these
goals, it is necessary to develop a functional and intelligent
communication architecture, adaptable and able to provide a
support framework, allowing access to system functionalities
regardless of physical and time constraints.
A functional architecture defines the logical and physical
structure of the components that make up a system, and the
interactions between these components [1], [2] and [3]. If we
focus on intelligent and distributed architectures, the main
paradigm to consider is the multi-agent system.
EAS-COM is a new architecture focused on product
development based on multi-agent systems. It integrates this
technology to facilitate the development of a flexible
distributed system by taking advantage of the characteristics of
H. IGUER, S. FARIS and H.MEDROMI, are with LRI Laboratory, Systems
architecture team, Hassan II University, Casablanca, Morocco
(hajar.iguer@gmail.com),(sophiafaris1989@gmail.com),
(hmedromi@yahoo.fr)
Multi-agent architecture for distributed IT GRC
platform
S. ELHASNAOUI, H. IGUER, S. FARIS and H.MEDROMI
F
International Journal of Computer Science and Information Security (IJCSIS),
Vol. 16, No. 2, February 2018
68 https://sites.google.com/site/ijcsis/
ISSN 1947-5500

agent interaction to model the functional system.
This paper is organized as follows. We start with a state of the
art communication systems. Then, two architecture versions
will be presented from our communication system according to
the two existing communication models: communication by
information sharing and communication by sending message.
Finally, we present a new hybrid approach to workflow
management within the IT GRC platform based on multi-agent
system. The latter combines the two communication models.
This approach makes it possible to manage the communication
between the different layers of the platform while ensuring the
follow-up of the steps, from the expression of an IT service (IT
objective in terms of IT process) to the processing of IT
processes included and the proposal of action plans to put in
place.
II. STATE OF THE ART OF COMMUNICATION SYSTEMS
A. Motivation
To support the construction of distributed systems, we are
witnessing a constant evolution of models that make extensive
use of software engineering, model analysis, etc., to facilitate
the implementation of these systems.
However, the implementation of distributed systems is not
tied to a specific communication system that manages the
workflows between these applications. Nevertheless, the
technological choice of the most appropriate communication
system is a fundamental task to ensure the integration of the
components and the scalability of the system.
A large number of research work, which works in different
areas of workflow management, can be found in various
literatures. Each research area has its own specifications and
requirements for managing a treatment request. Information
flow management is important for the use and sharing of
resources in a distributed system to establish meaningful
communication. Many studies have combined communication
management with agent technology. This involves the support
of different approaches for the implementation of this
technology.
A communication system aims at interconnecting and
implementing the distributed platform systems in order to
effectively address the problems faced by companies in terms
of reusability, interoperability and reduced coupling between
the different systems that implement their systems. Information
systems [4]. Thus, ensuring interoperable communication
between different distributed applications is the main problem
for distributed systems. Workflow management techniques
could meet these requirements. In addition, workflow
management is implemented as an interconnection of less
complicated tasks [5]. The concept of workflow has been
studied in many areas of research.
B. Context and methodology
Infrastructure based on multi-agent systems generally
facilitates autonomous communication between distributed
systems [6]. Recently, various improvements have been
implemented on communication based on multi-agent systems.
These improvements can overcome some interoperability
issues, but different types of technologies and development
models used can cause interoperability issues. Like the software
architecture of any system and the most important part, some
necessary requirements can be included in a communication
system such as availability, autonomy recovery from a failure
and transmission guarantee. On the other hand, existing work
based on agent technology has some gaps in communication
systems [7]. Building a flexible, self-contained communication
system would be a good initiative to manage workflows in the
IT GRC distributed platform. In addition, the use of agent
technology can be useful for facilitating communication in a
distributed platform, as it provides significant attributes such as
adaptation, interactivity, multi-protocol support and
implementation. Light work [8].
C. Research work related to communication management in
distributed systems
Many research studies have been found in the literature
concerning the improvement of communication systems within
distributed platforms, based on agents and multi-agent systems.
Most of these works address specific problems and some are
too general and not specific to a particular problem [9]Several
research studies have been conducted to solve the various
communication problems such as synchronization, reliability,
the communication language of the agents. As Table 1 shows,
there are twelve relevant research studies based on agent
technology that relate to communication in distributed systems.
The table summarizes and compares different approaches based
on attributes related to communication. We can divide these
works into 2 categories: synchronous and asynchronous
communication. The works were selected from several types of
technologies. The attributes used in the evaluation were
essentially chosen from generic specifications and requirements
for communication in distributed systems. The significance of
each of the attributes included in this comparative study are as
follows
• Type of communication: and type of communication
style
• Availability: The availability of the application to
respond to requests for treatments at any time.
• Autonomy: refers to the intelligent level of the system
to manage and implement queries.
• Message type: This is the type of message used in
communication.
• Scalability: is the ability to manage distributed system
expansion
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N°
Communication systems within distributed
platforms
Communication
Type
Availability Autonomy
Message
Type
Scalability
1
An Agent Platform for Reliable Asynchronous
Distributed (1) Asynchronous medium high ACL Low
2
Agent-Based Middleware for Web Service
Dynamic (2) synchronous Low high WSDI medium
3 XML-based Mobile Agents (3) synchronous Low high XML Low
4 An Agent-Based Distributed Smart Machine (4) synchronous Low high
KQML /
ACL
medium
5
An Agent XML based Information Integration
Platform (5) synchronous Low high SOAP Low
6
A Cross-Platform Agent-based Implementation
(6) synchronous Low high ACL high
7
Communication System among Heterogeneous
Multi
-Agent System (7)
synchronous Low high ACL medium
8 FACL (Form-based ACL) (8) synchronous medium high
Forme
based (ACL) Low
9
ACL Based Agent Communications in Plant
Automation (9) Asynchronous medium high ACL medium
10
Multi-agent Systems for Distributed
environment (10) synchronous Low high
ACL /
KQML medium
11
SOA Compliant FIPA Agent Communication
Language (11) synchronous Low high ACL medium
12
An Agent-Based Distributed Information
Systems Architecture (12) synchronous Low high ACL high
Table 1. Scientific work related to communication management
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The research work cited in Table III-1 is as follows:
(1). [10],
(2). [11],
(3). [12],
(4). [13],
(5). [14],
(6). [15],
(7). [16],
(8). [17],
(9). [18],
(10).[19],
(11).[20],
(12).[21].
The comparative study shown in Table 3-1 shows that the
systems (1) and (9) rely on asynchronous communication while
the other systems are based on synchronous communication.
We emphasize that for systems (6) and (12) the criterion of
scalability is taken into account, while the availability criterion
is not. All these architectures ensure the autonomy of their
systems. However, these architectures have certain limitations
concerning the environment in which they are integrated. In
fact, they do not specify the parameters of information flows,
nor the learning and adaptation of information.
In addition, this comparative study shows that most of these
architectures do not deal with the security aspect for data
exchange, nor for access control to distributed systems. They
are satisfied by checking the user's identifications through a
login and a password.
It should be noted that while the presented architectures provide
access to distributed systems based on ADMs, they have
limitations in terms of distribution, data adaptation, and the
scalability aspect that is not addressed in most architectures
studied.
We propose a new architecture to overcome the different
limitations encountered. This architecture is distributed,
intelligent and able to meet the requirements of governance,
risk management and compliance of information systems in
terms of distribution, adaptation of the data provided to the user
according to different constraints. It ensures the scalability of
the IT GRC platform to ensure the exchange of data with added
processing systems
III. BASIC ARCHITECTURE OF EAS-COM COMMUNICATION
SYSTEM
EAS -COM (see Figure 1: EAS-COM is represented by the
cross-section of the platform) is a communication system that
facilitates the integration of distributed systems from the IT
GRC platform. This system is dynamic, flexible, robust,
adaptable to each user's request, scalable and easy to use and
maintain. However, this architecture is extensible to integrate
the desired processing system, without dependence on a
specific programming language. The systems integrated in the
IT GRC platform follow an integrated communication protocol.
Another important feature is that, thanks to the capabilities of
the agents, the systems developed can make use of learning
techniques to manage decisions made previously and which are
recorded in knowledge bases. EAS -COM offers a new
perspective, where multi-agent systems and web services are
integrated to provide communication needs, leverage their
strengths, and avoid their weaknesses.
Fig1. Positioning the EAS-COM Communication System in the IT GRC
Platform
A. Introduction to EAS-COM subsystems
The communication system using multi-agent systems
requires answering the following questions:
• Which functions should be modeled as agents?
• How to decompose the communication system to be
supported by a multi-agent system approach?
• What types of interactions should exist between agents?
• What skills and resources do agents need?
• What priorities should be considered in workflow
management studies, and how are these priorities to be
addressed by agents?
In order to solve the communication problem within the IT
GRC platform, we break down the EAS-COM system into
subsystems. Each subsystem is responsible for performing a
specific communication task.
There is a strong link between the choice of agents and the
purposes for which they are designed. As a result, we study
workflows between IT GRC platform components based on
significance. With this in mind, we carry out the following main
tasks:
1) Categorize the IT services received from the
strategic layer;
2) Request and receive decision processing
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(interaction with the decision layer) with respect to
the best repositories;
3) Manage processing systems (sending IT services to
process and receiving processing results) taking into
account the quality of their processing and
performance. Each task can be assigned to an agent
or group of agents.
We call the multi-agent system assigned to the categorization
of IT services (interaction with the strategic layer) "Strategic-
com". It contains agents responsible for tasks (1).
We call the assigned multi-agent system to communicate with
the decision-com decision-making layer. It contains agents
responsible for performing the task (2).
We call the multi-agent system assigned to the processing
management of IT services (interaction with the processing
layer) "processing-com". Agents in this multi-agent system are
responsible for task (3). They must interact in order to achieve
this goal and to generate a representation of the action plan of
the treatment results.
Fig 2. EAS-COM architecture subsystems
B. Strategic-COM
The Strategic-COM subsystem provides communication
with the strategic layer represented by the EAS-STRATEGIC
system. The latter expresses the strategic needs of the user in
terms of IT service (IT Service) by defining the IT processes
(IT Processes) that must be managed by the IT GRC platform.
The IT services deducted are redirected to EAS-COM, and
more precisely to the Strategic-COM subsystem.
Recall that Strategic-COM is supposed to categorize the IT
processes included in the requested IT service. Categorization
is the combination of each IT process into one or best practice
repositories that can define the management activities of the
requested IT process.
Here is the diagram explaining the procedure for categorizing
an IT service received by the strategic layer.
Fig3. Procedure for Categorizing an IT Service by Strategic-COM
The IT Service categorization procedure is as follows:
First, the IT service received must be broken down
according to the IT processes it includes.
Each IT process is associated with one or more benchmarks
of good practice according to the discipline to which it
belongs (IT Governance, IT Risk Management, IT
compliance)
A constitution of the elements of the matrix is carried out
just after. The elements of the matrix have the following
form: {Proc i, (Ref 1, Ref 2, ... Ref n)}
The constituent elements are subsequently grouped in
order to build the final matrix in the form: {{Proc a, (Ref i,
Ref j, ... Ref n)}, {Proc b, (Ref i, Ref j ... Ref n)}, ...., {Proc
z, (Ref i, Ref j, ... Ref n)}}. This matrix represents the
categorized IT service ready to be processed by the second
EAS-COM subsystem.
We have defined three types of agents: Collector Agent,
Manager Agent, and Constructor Agent.
The Collector Agent and Constructor Agent focus primarily on
organizational tasks, while the Agent Manager performs
processing tasks. The main objective of the agent manager is to
guarantee the categorization of the processes of an IT service,
assigning them one or more repositories that can manage them.
It communicates the categorization result of each IT process to
the Builder agent, which, in turn, resembles this information to
send the categorized IT service to be consumed by the Decision
Decision Layer (EAS-Decision).
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Fig 4. Strategic-COM Agents
Collector Agent:
Collector Agent performs an organizational task. He is
responsible for the reception of IT Services Strategic Layer
(EAS-Strategic). To achieve its goal, it checks the structure of
the received web services, it classifies them according to the
date of their creation by the user (date of creation is specified in
all IT service). At the end of his treatment, he transfers the IT
Services to the Manager Agent.
Agent Manager
Manager Agent is the heart of Strategic-COM. It categorizes IT
services by associating each IT process with one or more
appropriate standards for its implementation. At the end of the
processing, it merges the elements of the matrix, which will
constitute the IT service categorized in the form {Process IT,
{ref1, ref2... refn}}. This result will be transferred to the
constructor agent.
The Agent Manager has a knowledge base, it concerns that the
agent knows the repositories that can manage the IT processes
issued by the strategic layer. This knowledge depends at the
beginning of the mapping of COBIT processes with the other
repositories. This mapping list will be fed as and when learning
the IT GRC platform. The knowledge of the agent manager can
be divided into two types: knowledge of IT GRC disciplines (IT
Governance, risk and compliance management) and their
associated repositories and knowledge about categorizations
that were done previously.
When categorizing IT Processes, the knowledge of the Manager
agent against the repositories of good practices is enriched and
updated, which allows the agent to associate a set of repositories
of good practice when his treatment to come. The enrichment
of knowledge is possible since the agent Manager constantly
monitors the changes of its environment and exchange
information with the Updater.
Constructor agent
The objective of this agent is to provide a readable
representation of the IT service he handles, while preserving as
much as possible the data setting of the IT Service (the user
creator of the IT service, the date of its creation, and priority of
IT processes ...). To achieve this goal, it retrieves the result of
the categorization of the IT processes provided by the Manager
agent and rebuilds the final matrix that represents the
categorized IT service that will be sent to the decision-making
layer (EAS-Decision) in the form of web service.
Fig 5. Distribution of Strategic-COM Agents according to their tasks
C. Decision-COM-agent DD
The Decision-COM subsystem provides communication with
the decision layer represented by the EAS-Decision system.
This communication consists of sending the categorized IT
service to the decision-making layer represented by the EAS-
DECISION system. Once the decision is made, compared to the
best repositories to associate with each of the IT processes
included in the IT service, Decision-COM receives the result of
the decision, represented by the decided IT service. The latter
must have the following format: {(Proc a, ref i), (Proc b, ref j)...
(Proc z, ref n)}.
We define the agent: DD Agent performing an organization
task. Its main objective is to ensure the communication of the
IT service with the decision layer. It receives the categorized IT
service from the Builder agent and translates it into a web
service to be able to send it to the decision layer, and it stays
tuned to receive the result of the decision. Once it is received,
it is transferred to the processing-Com subsystem for
processing.
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Fig 6: Decision-COM Agents
D. Processing-COM
The Processing-COM subsystem provides communication
with the processing layer represented by the EAS-
PROCESSING systems. EAS-PROCESSING-type processing
systems treat IT processes, following the recommendations
dictated by the repository chosen by the EAS-COM decision-
making system, in order to generate the action plans to be put
in place to meet the strategic needs of the organizations. Users
of the IT GRC platform. The processing requests are triggered
by the EAS-COM communication system and more precisely
by the Processing-COM subsystem.
We define four types of agents: Agent ComIn, Agent Admin,
Agent Directory, and Agent ComOut.
The ComIn and ComOut agent focuses on the organization
tasks, while the Admin Agent and Directory perform processing
tasks. The main goal of the Admin Agent is to ensure that the
process processing included in the IT service is allocated to the
correct processing systems. It interacts with processing-Com
agents in order to achieve an optimal choice of processing
systems. During this interaction, the Admin agent interacts with
the ComOut agent to resolve multiple processing requests from
the same processing system. To achieve all these goals, agents
act according to their knowledge and skills.
ComIn agent:
The Agent Agent ComIn is a communicating agent. It
receives the decided IT service from the Decision-com
subsystem and the transfer to the Admin Agent to determine the
processing systems that can manage the IT processes included
in the decided IT service.
Admin Agent
The Admin Agent invokes the processing system that is best
placed to complete the IT service processing and generate the
action plans to be put in place.
If there are multiple systems that can resolve the requested
task, the Admin Agent has the ability to select the optimal
choice. This ability of the decision in relation to the choice of
processing system depends on the performance of the latter, its
number of execution, availability.... This information is stored
in its knowledge base that it uses during the resolution of
conflicting situations. With each choice made, it communicates
with the ComOut agent and determines the best system to
trigger.
During processing, the Admin Agent stores important
information such as, the useful results he has obtained from
previous treatments and changes in his environment. When the
Admin agent chooses the processing system, he evaluates the
results of his action, updates his knowledge. Then he goes to
the choice of the system that will manage the IT process.
Agent Directory
The Directory Agent takes care of the recording of the
systems processing reports, as well as information about them
(system performance, number of execution,). This information
is taken into consideration by the Admin Agent to choose the
most relevant processing system.
ComOut agent
Notifying and triggering processing systems that can handle
all processes in an IT service is a complex task that can lead to
additional processing time, and therefore can slow down the
execution of requests. Therefore, we need to partition the
processing request to all processing systems. The control of the
notification of each system is therefore assigned to a specific
agent (ComOut agent). In this step, we propose a new approach
in which the triggering of IT service process processes can be
partitioned. Our idea is to trigger the set of processing systems
chosen to implement the processes of the same IT service.
During this trigger, the ComOut agent receives the list of
processing systems to be notified. This list should contain the
information of these systems namely the name of the system,
the description, the IP address of the server in which the
processing system is running.
This method provides simultaneous processing of all processes
included in the IT service. However, there may be situations
where multiple requests for processing are not allowed, such as
requests for processing multiple processes by the same
processing system, which could significantly reduce the
performance of the same. In this case, the Admin agent asks the
ComOut agent to check the status of the affected system and
inform him that he is busy and cannot accept further requests
until he finishes. The Admin Agent must then decide to choose
another processing system that could handle the request or wait
until it becomes available. Therefore, the importance of the
EAS-COM Processing-COM subsystem lies in the acceleration
it gives to the triggering process, and hence the process
processing of a requested IT service.
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Fig 7. Distribution of Processing-COM Agents according to their tasks
IV. CONCLUSION
In this paper, we presented the main features of EAS-COM,
the subsystems that make it up and the agents that federate each
of these subsystems. We have not specified the mode of
communication to be considered between the system agents and
between EAS-COM and the other distributed systems of the IT
GRC platform.
In the next works, we propose architectures of the EAS-COM
system based on the modes of communication: Communication
by information sharing and communication by sending
message.
REFERENCES AND FOOTNOTES
REFERENCES
[1] Elhasnaoui, S., Medromi, H., Faris, S., Iguer, H., &
Sayouti, A. (2014). Designing a Multi Agent
System Architecture for IT Governance Platform.
International Journal of Advanced Computer
Science and Applications IJACSA, 5(5).
[2] Elhasnaoui, S., Chergui, M., Chakir, A., Sekhara, Y.,
Nahla, H. & Medromi, H. Empirical study on the
interaction and workflow management between
information system and business departments of an
organization to integrate IT GRC processes: Case of
Moroccan organizations. International Journal of
Engineering Research And Management (IJERM),
Volume 03 Issue 05 (May 2016).
[3] Elhasnaoui, S., Moussaid, L., Medromi, H., &
Sayouti, A. A Communication System Architecture
Based on Sharing Information to Integrate
Components of Distributed Multi-Agent Systems
within an IT GRC Platform. International Journal of
Advanced Engineering Research and Science, Vol-
3,Issue-12,December 2016
[4] Ibrahim, M., N.b., Hassan, M.F.B.: A Survey on
Different Interoperability frameworks of SOA
Systems Towards Seamless Interoperability. In:
Escon 2010, IEEE, Kuala Lumpur (2010)
[5] Yuan, P., Jin, H., Qi, L., Li, S.: Research on an
MOM-based service flow management system. In:
Jin, H., Pan, Y., Xiao, N., Sun, J. (eds.) GCC 2004.
LNCS, vol. 3251, pp. 783–786. GCC, Heidelberg
(2004)
[6] Kao, Y.-C., Chen, M.-S.: An Agent-Based
Distributed Smart Machine Tool Service System.
3CA IEEE, Los Alamitos (2010)
[7] Goel, S., Sharda, H., Taniar, D.: Message-oriented-
middleware in a distributed environment. In: Böhme,
T., Heyer, G., Unger, H. (eds.) IICS 2003. LNCS,
vol. 2877, pp. 93–103. Springer, Heidelberg (2003)
[8] Bellissard, L., De Palma, A.F.N., Herrmann, M.,
Lacourte, S.: An Agent Platform for Reliable
Asynchronous Distributed Programming. IEEE,
France (1999)
[9] Raja, M.A.N., Ahmad, H.F., Suguri, H.: SOA
Compliant FIPA Agent Communication Language.
IEEE, Los Alamitos (2008)
[10]Bellissard, L., De Palma, N., Freyssinet, A.,
Herrmann, M., & Lacourte, S. (1999). An agent
platform for reliable asynchronous distributed
programming. In Reliable Distributed Systems,
1999. Proceedings of the 18th IEEE Symposium on
(pp. 294-295). IEEE.
[11]Lin, A., & Maheshwari, P. (2005). Agent-based
middleware for web service dynamic integration on
peer-to-peer networks. AI 2005: Advances in
Artificial Intelligence, 405-414.
[12]Steele, R., Dillon, T., Pandya, P., & Ventsov, Y.
(2005, April). XML-based mobile agents. In
Information Technology: Coding and Computing,
2005. ITCC 2005. International Conference on (Vol.
2, pp. 42-48). IEEE.
[13]Kao, Y. C., & Chen, M. S. (2010, May). An agent-
based distributed smart machine tool service system.
In Computer Communication Control and
Automation (3CA), 2010 International Symposium
on (Vol. 2, pp. 41-44). IEEE.
[14]Li, X. (2010, April). An Agent/XML based
information integration platform for process industry.
In Computer Engineering and Technology (ICCET),
2010 2nd International Conference on (Vol. 3, pp. V3-
526). IEEE.
[15]Cervera, E. (2005). A cross-platform agent-based
implementation. IEEE, Los Alamitos.
[16]Yoon, Y. J., Choi, K. H., & Shin, D. R. (2008,
September). Design and Implementation of
Communication System among Heterogeneous
Multi-Agent System. In Networked Computing and
Advanced Information Management, 2008. NCM'08.
Fourth International Conference on (Vol. 1, pp. 267-
269). IEEE.
[17]Chusho, T., & Fujiwara, K. (2000). Facl: A form-
based agent communication language for enduser-
initiative agent-based application development. In
Computer Software and Applications Conference,
2000. COMPSAC 2000. The 24th Annual
International (pp. 139-148). IEEE.
ISSN 1947-5500

[18]Feng, Q., & Lu, G. (2003, September). Fipa-acl based
agent communications in plant automation. In
Emerging Technologies and Factory Automation,
2003. Proceedings. ETFA'03. IEEE Conference (Vol.
2, pp. 74-78). IEEE.
[19]Ahmad, H. F. (2002). Multi-agent systems: overview
of a new paradigm for distributed systems. In High
Assurance Systems Engineering, 2002. Proceedings.
7th IEEE International Symposium on (pp. 101-107).
IEEE.
[20]Raja, M. A. N., Ahmad, H. F., Suguri, H.,
Bloodsworth, P., & Khalid, N. (2008, August). SOA
compliant FIPA agent communication language. In
Applications of Digital Information and Web
Technologies, 2008. ICADIWT 2008. First
International Conference on the (pp. 470-477). IEEE.
[21]Purvis, M., Cranefield, S., Bush, G., Carter, D.,
McKinlay, B., Nowostawski, M., & Ward, R. (2000,
January). The NZDIS project: an agent-based
distributed information systems architecture. In
System Sciences, 2000. Proceedings of the 33rd
Annual Hawaii International Conference on (pp. 10-
pp). IEEE.
Soukaina ELHASNAOUI received the
PhD in engineering science from the
Hassan II University, ENSEM, 2017,
Casablanca, Morocco.
He is professor permanent at Moroccan
School of engineering sciences (EMSI).
Her actual main research interest concern
IT Governance, risk management end
compliance based on Multi Agents
Systems.
Hajar Iguer
received the PhD in engineering science
from the Hassan II University, ENSEM,
2017, Casablanca, Morocco.
He is professor permanent at International
University of Casablanca (UIC) Her actual
main research interest concern IT
Governance, risk management end
compliance based on Multi Agents
Systems.
Sophia Faris
Graduated as an engineer in computer
science from the National School of
Electricity and Mechanics, Casablanca,
Morocco in 2011. She is in charge of the
documentation and production department
at the Wilaya of Casablanca-Settat Region.
Her actual main research interest concern IT
Governance, risk management end
compliance based on Multi Agents Systems.
Hicham Medromi received the PhD in
engineering science from the Sophia Antipolis
University in 1996, Nice, France.
He is director of the National Higher School
of electricity and mechanics (ENSEM)
Hassan II University, Morocco. His actual
main research interest concern Control Architecture of Mobile
Systems Based on Multi Agents Systems.
ISSN 1947-5500

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