This document presents an ontology for exploring knowledge in computer networks that was developed using OWL format. Over 500 concepts related to various aspects of computer networks like scope, scale, topology, etc. were identified and classified. Relationships between concepts were analyzed and over 550 relationships between 33 types of relationships were identified. The ontology was implemented using the Protege tool and can help users search for concepts in the computer networks domain on semantic web applications.

1. International Journal on Computational Sciences & Applications (IJCSA) Vol.3, No.4, August 2013
DOI:10.5121/ijcsa.2013.3402 13
AN ONTOLOGY FOR EXPLORING KNOWLEDGE IN
COMPUTER NETWORKS
SAKTHI MURUGAN. R1
, P. SHANTHI BALA
2
AND DR. G. AGHILA
3
Department of Computer Science, Pondicherry University, Puducherry, India
1
sakthimuruga@gmail.com
2
shanthibala.cs@gmail.com
ABSTRACT
Ontology is applied to impart knowledge in various fields of Information Technology made it more
intelligent in the past few decades. Many Ontologies was built on various domains like biology, medicine,
physics, chemistry, and mathematics. The Ontology in computer science domain are limited and even the
Ontology is not explored in detail. The knowledge in the field of computer networks is very large, which
makes it more difficult for a human to expertise in. This paper proposes the Ontology in computer network
domain on various perspectives like scope, scale, topology, communication media, OSI model, TCP/ IP
model, protocol, security, network operating system, network hardware and performance. The Ontology is
developed in OWL format, which can be easily integrated with any other semantic based applications. The
network Ontology can be employed in Semantic Web applications to help the users to search for concepts
computer networks domain.
KEYWORDS
Computer Networks, Ontology, OWL, Semantic Web
1. INTRODUCTION
The Semantic Web is an extension of the current web in which information provides well-defined
meaning that enables system and people for better understanding and can enable to work
effectively [1]. The abundance knowledge available in web is made organized with the help of
semantic web. Ontology is called as the core of Semantic Web since it is needed to develop
semantic web applications.
Ontology is a, "formal and explicit specification of a shared conceptualization" [2]. These
Ontologies can be represented as Web Ontology Language (OWL) [15], RDFS, DAML+OIL
[24]. W3C [16] recommends OWL definition of Ontology on web than other available like OIL
[14], SHOE [25] and XOL [26]. The main advantage of Ontology is once developed it can be
integrated and reused in all the applications, it allows to share more data, uses simple tags to
provide semantic information.
The development of Ontology in various domains has proved its efficiency in various ways.
Though Ontology is the transformation of philosophy to Information Systems, little effort has
been made to develop in domain of Information Systems compared to other growing research
domains.The way computer communicates having evolved in the past few decades. This
evolution leads to the introduction of new concepts and technologies being introduced frequently
to improve the speed, efficiency, security and various aspects in domain of computer networks.

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This introduction of large concepts makes it hard to expertise in its entire sub domain. We have
developed the Ontology for computer networks, which consists of 500+ concepts. These concepts
are built with W3C standard whereby integrating these Ontologies can alleviate the difficulty of
user. This paper is organized as follows: Section 2 describes the related work being carried out in
various domain Ontology. Section 3 explores the various concepts, relations and properties of
computer networks domain. Section 4 describes the implementation of Ontology and finally
Section 5 concludes the paper.
2. RELATED WORK
Many well published Ontology are publicly available like Gene Ontology (GO) [18] which
consists of gene and gene products of various species, Plant Ontology (PO) [19] which consists of
concepts about anatomy, morphology and stages of plants, Semantic Web for Earth and
Environmental Terminology (SWEET) [20] contains 6000 unique concepts and 200 distinct
Ontology in SWEET 2.2, Foundational Model of Anatomy Ontology (FMA) [21] contains
120000 terms with 75000 distinct concepts with 168 types of relationships.
Various domain Ontologies has been developed like Yip et al. [4] developed Ontology for
healthcare domain. Mei-Ying Jia et al. [5] developed Domain Ontology in Military Intelligence.
Song Jun-Feng et al. [6] worked for Network Centric Warfare on Construction and Integration of
Ontology for military domain, situation and military rule. Maojun Huang [7] developed
Geographic Ontology from the viewpoints of Philosophy Ontology, Information Ontology and
Spatial Ontology. Gang Liu et al. [8] developed Ontology for geological hazard information.
Fragiskos et al. [9] created Ontology for biosensor domain to support R&D in the science-based
sector.
Ontology developed to support reasoning for a model is more common in case of Computer
Network than those developed to provide domain knowledge. Hui Xu and Debao Xiao [10][11]
developed Information Specification Ontology to manage Computer Network based on Formal
Concept Analysis and configure IP based network based on Ontology than that of normal SNMP.
A.K.Y. Wong et al. [12] have developed Ontology to map the protocols of different networking
device providers. M.J. Taylor et al. [13] have developed knowledge for network support based on
case studies of organizational approach to troubleshoot network problems.
Ontology developed to provide domain knowledge in a broader domain like computer networks is
very limited. Ling et al. [3] developed an educational Ontology for computer networks, which
explores concepts, communication sub network, application sub network, standards and network
security with the main purpose to be used as a teaching aid. The major drawback of the existing
system is the relations between the concepts have not been analyzed properly. In general "is-a"
and "part-of" is used in common for all the relations, which makes the Ontology weak.
3. COMPUTER NETWORKS ONTOLOGY
3.1. Classification of Computer Networks
The domain of computer networks can be categorized based on scope, scale, topology,
communication media, OSI model, TCP/ IP model, protocol, security, network operating system,
network hardware and performance.The main concepts explored under scope are Intranet,
Extranet and Internet in terms of services provided and technology used. Scale is classified as
LAN, MAN and WAN and how it could be achieved. Topology is ranked out based on its types
and standards. Communication media are

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analyzed based on its types of variant, the way it operates and standards. The main concepts make
out of OSI and TCP/ IP model are its layers and functionalities. Protocol is a vast area explored in
terms of Ethernet standards and technologies, Internet Protocol (IP) versions, classes, support to
upper layers. Security itself a vast sub domain which is categorized in terms of threats, attacks,
encryption techniques, malicious software's and approaches to system security. The network
operating system is classified based on its types of operating system used in router, types of
server operating system and types of operating system used for peer-to-peer communication.
Network hardware concepts are analyzed based on its types and functionalities. The factors to be
considered to improve the performance of communication are explored under performance.
Figure 1 shows the part of developed Ontology with the relation between them.
The relations are used to complete the meaning of the concepts. For example concepts 'IANA' and
'Internet Protocol' uses the relation 'allocate' which has knowledge 'IANA allocate Internet
Protocol', concepts 'Transport Layer' and 'Datagram' uses relation 'transmits' which contains
knowledge 'Transport Layer transmits Datagram'.
Figure 1. Part of Developed Ontology

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2.2. Ontology Development
The Ontology development process is to first identify the key concepts and then the relation
between the concepts and finally classify the concepts based on their properties.The main
drawback of the existing system is the concepts not explored in detail, and the relation between
the concepts is not analyzed, which provides open world semantics. In our Ontology we analyzed
about 550-relationship instance with 33 types of relationship. Semantic annotations are available
for most of the concepts, which make the user get to know more details about the concepts.
The key concepts or sub concepts are represented as Classes. We found key concepts in the
domain of computer networks and analyzed all the equivalent concepts to find the relation
between the concepts. We studied the properties of each concept to categories all sub concepts
under one main concept and we found the total number of concepts grouped under one main
concept in Table 1. Table 2 and Table 3 are the sub concepts of Security and Protocol
respectively.
Table 1. Explored Concepts in Computer Networks.
Sl. No. Concepts No. of Sub Concepts
1 Scope 47
2 Scale 8
3 Topology 24
4 Communication Media 94
5 OSI Model 37
6 TCP/ IP Model 8
7 Protocol 121
8 Security 125
9 Network Operating System 24
10 Network Hardware 48
11 Performance 7
Table 2. List of Concepts Related to Security.
Sl. No. Concepts No. of Sub Concepts
1 Goals 3
2 Threads 4
3 Attacks 19
4 Cryptography 23
5 Intrusion Detection System 18
6 Virtual Private Network 13
7 Firewall 14
8 Malicious Software 26

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Table 3. Protocol Related Concepts.
Sl. No. Concepts No. of Sub Concepts
1 Ethernet 19
2 Internet Protocol 68
3 SONET/ SDH 10
4 ATM 22
4. IMPLEMENTATION
There are many tools like Protégé [17], OilEd [22] and KAON [23], which are used to develop
Ontology. We used Protégé user interface in developing the Ontology for Computer Networks.
Through study about the concepts are made before categorizing it. There are some sub concepts,
which are to be categorized under different main concepts whose complex relations can be easily
retrieved through the developed Ontology.
The part of code of developed Ontology is given in Figure 2. This code is in XML format where
"www.w3.org/2002/07/owl#" has the schema definition for Ontology development. The concepts
'Internet' and 'World Wide Web' are declared as classes in the Ontology, and the relation between
them is 'uses' which is declared as object property. The actual knowledge stored in the code is
'Internet uses World Wide Web'.
Figure 2. Screenshot of part of developed Ontology

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Figure 3 shows the various concepts explored with Networking Hardware in Protégé tool. The
'Thing' is the system class of the Protégé tool under which the user defined classes are created.
Figure 3. Concepts explored in Networking Hardware
Figure 4 shows the visualization of the developed Ontology. OWLViz plug-in has been used to
show the visualization. It identifies the concepts from the classes in the OWL file and creates a
default 'is a' relationship between those concepts which are related by the SubClassOf tag.

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Figure 4. Visualization of Network Ontology

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5. CONCLUSION
This paper report the first stage of research which focus on the development of Ontology for the
domain of computer networks with 500+ concepts, 550 relationship instance with 33 types of
relationship, which is considered as fuel to run the Semantic applications, so that the user can
seek for domain knowledge. The domain of computer networks has evolved and still growing, so
the Ontology we have developed tends to dynamically grow with new invention and advancement
in technology over time.
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