SlideShare a Scribd company logo
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.
International Journal on Computational Sciences & Applications (IJCSA) Vol.3, No.4, August 2013
14
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
International Journal on Computational Sciences & Applications (IJCSA) Vol.3, No.4, August 2013
15
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
International Journal on Computational Sciences & Applications (IJCSA) Vol.3, No.4, August 2013
16
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
International Journal on Computational Sciences & Applications (IJCSA) Vol.3, No.4, August 2013
17
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
International Journal on Computational Sciences & Applications (IJCSA) Vol.3, No.4, August 2013
18
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.
International Journal on Computational Sciences & Applications (IJCSA) Vol.3, No.4, August 2013
19
Figure 4. Visualization of Network Ontology
International Journal on Computational Sciences & Applications (IJCSA) Vol.3, No.4, August 2013
20
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.
REFERENCES
[1] Berners-Lee, J. Hendler, and O. Lassila, "The Semantic Web", Scientific American, vol. 284, no. 5,
pp. 34-43, May 2001.
[2] M. Uschold and M. Gruninger, "Ontologies: Principles, methods and applications", Knowledge
Engineering Review, vol. ll, no.2, pp.93-155, 1996.
[3] Ling Jiang, Chengling Zhao and Haimei Wei, "The Development of Ontology-Based Course for
Computer Networks", International Conference on Computer Science and Software Engineering,
2008, 978-0-7695-3336-0/08, DOI 10.1109/CSSE.2008.185
[4] Yip Chi Kiong, Sellappan Palaniappan and Nor Adnan Yahaya, "Health Ontology System", 7th
International Conference on IT in Asia (CITA), 2011 IEEE, 978-1-61284-130-4/11.
[5] Mei-ying Jia, Bing-ru Yang, De-quan Zheng and Wei-cong Sun, "Research on Domain Ontology
Construction in Military Intelligence", Third International Symposium on Intelligent Information
Technology Application, 2009, IEEE, pp.116–119.
[6] Song Jun-feng, Zhang Wei-ming, Xiao Wei-dong and Xu Zhen-ning, "Study on Construction and
Integration of Military Domain Ontology, Situation Ontology and Military Rule Ontology for
Network Centric Warfare", The 2005 IEEE International Conference on e-Technology, e-Commerce
and e-Service.
[7] Maojun Huang, "On The Concept of Geographic Ontology—From The Viewpoints of Philosophy
Ontology, Information Ontology and Spatial Ontology", 18th International Conference on
Geoinformatics, 2010, IEEE.
[8] Gang Liu, Yanni Wang and Chonglong Wu, "Research and Application of Geological Hazard
Domain Ontology", 18th International Conference on Geoinformatics, 2010, IEEE.
[9] Fragiskos A. Batzias and Christina G. Siontorou, "Creating a specific domain Ontology for supporting
R&D in the science-based sector – The case of biosensors", Expert Systems with Applications,
Volume 39, Issue 11, 1 September 2012, Pages 9994–10015.
[10] Hui Xu and Debao Xiao, “Building Information Specification Ontology for Computer Network
Management based on Formal Concept Analysis”, International Conference on Information and
Automation, June 2009, pp. 312-317.
[11] Hui Xu and Debao Xiao, "Common Ontology-based Intelligent Configuration Management Model for
IP Network Devices", Innovative Computing, Information and Control, ICICIC '06, pp.385-388.
[12] A.K.Y. Wong, An Chi Chen, N. Paramesh, P. Rav, "Ontology Mapping for Network Management
Systems", Network Operations and Management Symposium, IEEE/IFIP, April 2004, Vol.1,pp.885-
886.
[13] M.J. Taylor, D. Gresty and R. Askwith, "Knowledge for Network Support", Information and Software
Technology, Volume 43, Issue 8, 1 July 2001, Pages 469–475.
[14] Dieter Fensel, Frank van Harmelen, Ian Horrocks, Deborah L. McGuinness and Peter F. Patel-
Schneider. "OIL: An Ontology Infrastructure for the Semantic Web", IEEE INTELLIGENT
SYSTEMS, MARCH/APRIL 2001, pp.38-45.
[15] OWL Web Ontology Language. Available: http://www.w3.org/TR/owl-features/
[16] World Wide Web Consortium (W3C). Available: http://www.w3.org/standards/semanticweb/
ontology
[17] Protégé. Available: http://protege.stanford.edu/
[18] An Introduction to the Gene Ontology. Available: http://www.geneontology.org/GO.doc.shtml
International Journal on Computational Sciences & Applications (IJCSA) Vol.3, No.4, August 2013
21
[19] About the Plant Ontology project. Available: http://www.plantontology.org/docs/otherdocs/poc
_project.html
[20] SWEET Ontologies. Available: http://sweet.jpl.nasa.gov/
[21] Foundational Model of Anatomy ontology - About. Available: http://sig.biostr.washington.edu/
projects/fm/AboutFM.html
[22] OilEd. Available: http://oiled.semanticweb.org/index.shtml
[23] KAON - The Karlsruhe Ontology and Semantic Web Tool Suite. Available: http://kaon.
semanticweb.org/
[24] DAML+OIL. Available: http://www.w3.org/TR/daml+oil-reference
[25] SHOE: Simple HTML Ontology Extensions. Available: http://www.cs.umd.edu/projects/plus/ SHOE/
[26] XOL Ontology Exchange Language. Available: http://www.ai.sri.com/pkarp/xol/

More Related Content

What's hot (20)

PDF
Computer Science Research Methodologies
IJCSIS Research Publications
 
PDF
Novel framework using dynamic passphrase towards secure and energy-efficient ...
IJECEIAES
 
PDF
DEVELOPMENT OF A CONCEPTUAL MODEL OF ADAPTIVE ACCESS RIGHTS MANAGEMENT WITH U...
IAEME Publication
 
PDF
Trends of machine learning in 2020 - International Journal of Artificial Inte...
gerogepatton
 
PDF
An overview of internet of things
TELKOMNIKA JOURNAL
 
PDF
CV January 2011
Alberto Trombetta
 
PDF
NETWORK INTRUSION DATASETS USED IN NETWORK SECURITY EDUCATION
IJITE
 
PDF
Artigo - Aplicações Interativas para TV Digital: Uma Proposta de Ontologia de...
Diego Armando
 
PDF
A crisis-communication-network-based-on-embodied-conversational-agents-system...
Cemal Ardil
 
DOCX
Curriculum Vitae
butest
 
PDF
Improved method for image security based on chaotic-shuffle and chaotic-diffu...
IJECEIAES
 
PDF
The road to internet of things :a survey
Sana
 
PDF
Rule-based Information Extraction from Disease Outbreak Reports
Waqas Tariq
 
PDF
n-Tier Modelling of Robust Key management for Secure Data Aggregation in Wire...
IJECEIAES
 
PDF
State regulation of the IoT in the Russian Federation: Fundamentals and chall...
IJECEIAES
 
PDF
Top 5 most_viewed_articles ijci
IJCI JOURNAL
 
PDF
A Deep Learning Model For Crime Surveillance In Phone Calls.
vivatechijri
 
PDF
Multi-objective NSGA-II based community detection using dynamical evolution s...
IJECEIAES
 
PDF
Understanding Architecture of Internet of Things
IJSRED
 
PDF
Trust-based secure routing against lethal behavior of nodes in wireless adhoc...
IJECEIAES
 
Computer Science Research Methodologies
IJCSIS Research Publications
 
Novel framework using dynamic passphrase towards secure and energy-efficient ...
IJECEIAES
 
DEVELOPMENT OF A CONCEPTUAL MODEL OF ADAPTIVE ACCESS RIGHTS MANAGEMENT WITH U...
IAEME Publication
 
Trends of machine learning in 2020 - International Journal of Artificial Inte...
gerogepatton
 
An overview of internet of things
TELKOMNIKA JOURNAL
 
CV January 2011
Alberto Trombetta
 
NETWORK INTRUSION DATASETS USED IN NETWORK SECURITY EDUCATION
IJITE
 
Artigo - Aplicações Interativas para TV Digital: Uma Proposta de Ontologia de...
Diego Armando
 
A crisis-communication-network-based-on-embodied-conversational-agents-system...
Cemal Ardil
 
Curriculum Vitae
butest
 
Improved method for image security based on chaotic-shuffle and chaotic-diffu...
IJECEIAES
 
The road to internet of things :a survey
Sana
 
Rule-based Information Extraction from Disease Outbreak Reports
Waqas Tariq
 
n-Tier Modelling of Robust Key management for Secure Data Aggregation in Wire...
IJECEIAES
 
State regulation of the IoT in the Russian Federation: Fundamentals and chall...
IJECEIAES
 
Top 5 most_viewed_articles ijci
IJCI JOURNAL
 
A Deep Learning Model For Crime Surveillance In Phone Calls.
vivatechijri
 
Multi-objective NSGA-II based community detection using dynamical evolution s...
IJECEIAES
 
Understanding Architecture of Internet of Things
IJSRED
 
Trust-based secure routing against lethal behavior of nodes in wireless adhoc...
IJECEIAES
 

Similar to AN ONTOLOGY FOR EXPLORING KNOWLEDGE IN COMPUTER NETWORKS (20)

PDF
TOGETHER: TOpology GEneration THrough HEuRistics
Subin Mathew
 
PDF
Iot ontologies state of art$$$
Sof Ouni
 
DOC
Representation of ontology by Classified Interrelated object model
Mihika Shah
 
PDF
Ontologies dynamic networks of formally represented meaning1
STIinnsbruck
 
PPT
22 owl section 1
Sharat Jagannath
 
PPTX
Module 1 notes for IoT BETCK105H (VTU) Introduction to IoT
ashwini870728
 
PDF
The Revolution Of Cloud Computing
Carmen Sanborn
 
PPTX
Connecting the Next Billion Devices to the Internet - Standards and Protocols
Steve Ray
 
PDF
Question answer template
Thanuw Chaks
 
PDF
Semantic IoT Semantic Inter-Operability Practices - Part 2
iotest
 
PDF
M1. sem web & ontology introd
Michele Missikoff
 
PPTX
Ontology
Ahmed Tememe
 
PPT
Internet of Things and Data Analytics for Smart Cities and eHealth
PayamBarnaghi
 
PDF
Cw32611616
IJERA Editor
 
PDF
Cw32611616
IJERA Editor
 
DOCX
FASE DE PLANEACION (INGLES)
andreseams
 
PDF
A category theoretic model of rdf ontology
IJwest
 
PPTX
TOPOLOGY
saranyajey
 
PPTX
Network Concepts..........................................
JohnnexterGubat3
 
PDF
G Antoniou Frank Van Harmelen A Semantic Web Primer
uintvenka15
 
TOGETHER: TOpology GEneration THrough HEuRistics
Subin Mathew
 
Iot ontologies state of art$$$
Sof Ouni
 
Representation of ontology by Classified Interrelated object model
Mihika Shah
 
Ontologies dynamic networks of formally represented meaning1
STIinnsbruck
 
22 owl section 1
Sharat Jagannath
 
Module 1 notes for IoT BETCK105H (VTU) Introduction to IoT
ashwini870728
 
The Revolution Of Cloud Computing
Carmen Sanborn
 
Connecting the Next Billion Devices to the Internet - Standards and Protocols
Steve Ray
 
Question answer template
Thanuw Chaks
 
Semantic IoT Semantic Inter-Operability Practices - Part 2
iotest
 
M1. sem web & ontology introd
Michele Missikoff
 
Ontology
Ahmed Tememe
 
Internet of Things and Data Analytics for Smart Cities and eHealth
PayamBarnaghi
 
Cw32611616
IJERA Editor
 
Cw32611616
IJERA Editor
 
FASE DE PLANEACION (INGLES)
andreseams
 
A category theoretic model of rdf ontology
IJwest
 
TOPOLOGY
saranyajey
 
Network Concepts..........................................
JohnnexterGubat3
 
G Antoniou Frank Van Harmelen A Semantic Web Primer
uintvenka15
 
Ad

Recently uploaded (20)

PDF
Go Concurrency Real-World Patterns, Pitfalls, and Playground Battles.pdf
Emily Achieng
 
PDF
CIFDAQ Market Insights for July 7th 2025
CIFDAQ
 
PPTX
Q2 FY26 Tableau User Group Leader Quarterly Call
lward7
 
PDF
Transcript: New from BookNet Canada for 2025: BNC BiblioShare - Tech Forum 2025
BookNet Canada
 
PPTX
AI Penetration Testing Essentials: A Cybersecurity Guide for 2025
defencerabbit Team
 
PDF
[Newgen] NewgenONE Marvin Brochure 1.pdf
darshakparmar
 
PDF
POV_ Why Enterprises Need to Find Value in ZERO.pdf
darshakparmar
 
PDF
What Makes Contify’s News API Stand Out: Key Features at a Glance
Contify
 
PDF
New from BookNet Canada for 2025: BNC BiblioShare - Tech Forum 2025
BookNet Canada
 
PDF
July Patch Tuesday
Ivanti
 
PDF
"AI Transformation: Directions and Challenges", Pavlo Shaternik
Fwdays
 
PPTX
WooCommerce Workshop: Bring Your Laptop
Laura Hartwig
 
PDF
CIFDAQ Token Spotlight for 9th July 2025
CIFDAQ
 
PPTX
AUTOMATION AND ROBOTICS IN PHARMA INDUSTRY.pptx
sameeraaabegumm
 
PDF
Smart Trailers 2025 Update with History and Overview
Paul Menig
 
PPTX
Future Tech Innovations 2025 – A TechLists Insight
TechLists
 
PDF
The Rise of AI and IoT in Mobile App Tech.pdf
IMG Global Infotech
 
PPTX
From Sci-Fi to Reality: Exploring AI Evolution
Svetlana Meissner
 
PDF
Building Real-Time Digital Twins with IBM Maximo & ArcGIS Indoors
Safe Software
 
PPTX
COMPARISON OF RASTER ANALYSIS TOOLS OF QGIS AND ARCGIS
Sharanya Sarkar
 
Go Concurrency Real-World Patterns, Pitfalls, and Playground Battles.pdf
Emily Achieng
 
CIFDAQ Market Insights for July 7th 2025
CIFDAQ
 
Q2 FY26 Tableau User Group Leader Quarterly Call
lward7
 
Transcript: New from BookNet Canada for 2025: BNC BiblioShare - Tech Forum 2025
BookNet Canada
 
AI Penetration Testing Essentials: A Cybersecurity Guide for 2025
defencerabbit Team
 
[Newgen] NewgenONE Marvin Brochure 1.pdf
darshakparmar
 
POV_ Why Enterprises Need to Find Value in ZERO.pdf
darshakparmar
 
What Makes Contify’s News API Stand Out: Key Features at a Glance
Contify
 
New from BookNet Canada for 2025: BNC BiblioShare - Tech Forum 2025
BookNet Canada
 
July Patch Tuesday
Ivanti
 
"AI Transformation: Directions and Challenges", Pavlo Shaternik
Fwdays
 
WooCommerce Workshop: Bring Your Laptop
Laura Hartwig
 
CIFDAQ Token Spotlight for 9th July 2025
CIFDAQ
 
AUTOMATION AND ROBOTICS IN PHARMA INDUSTRY.pptx
sameeraaabegumm
 
Smart Trailers 2025 Update with History and Overview
Paul Menig
 
Future Tech Innovations 2025 – A TechLists Insight
TechLists
 
The Rise of AI and IoT in Mobile App Tech.pdf
IMG Global Infotech
 
From Sci-Fi to Reality: Exploring AI Evolution
Svetlana Meissner
 
Building Real-Time Digital Twins with IBM Maximo & ArcGIS Indoors
Safe Software
 
COMPARISON OF RASTER ANALYSIS TOOLS OF QGIS AND ARCGIS
Sharanya Sarkar
 
Ad

AN ONTOLOGY FOR EXPLORING KNOWLEDGE IN COMPUTER NETWORKS

  • 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 [email protected] 2 [email protected] 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.
  • 2. International Journal on Computational Sciences & Applications (IJCSA) Vol.3, No.4, August 2013 14 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
  • 3. International Journal on Computational Sciences & Applications (IJCSA) Vol.3, No.4, August 2013 15 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
  • 4. International Journal on Computational Sciences & Applications (IJCSA) Vol.3, No.4, August 2013 16 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
  • 5. International Journal on Computational Sciences & Applications (IJCSA) Vol.3, No.4, August 2013 17 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
  • 6. International Journal on Computational Sciences & Applications (IJCSA) Vol.3, No.4, August 2013 18 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.
  • 7. International Journal on Computational Sciences & Applications (IJCSA) Vol.3, No.4, August 2013 19 Figure 4. Visualization of Network Ontology
  • 8. International Journal on Computational Sciences & Applications (IJCSA) Vol.3, No.4, August 2013 20 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. REFERENCES [1] Berners-Lee, J. Hendler, and O. Lassila, "The Semantic Web", Scientific American, vol. 284, no. 5, pp. 34-43, May 2001. [2] M. Uschold and M. Gruninger, "Ontologies: Principles, methods and applications", Knowledge Engineering Review, vol. ll, no.2, pp.93-155, 1996. [3] Ling Jiang, Chengling Zhao and Haimei Wei, "The Development of Ontology-Based Course for Computer Networks", International Conference on Computer Science and Software Engineering, 2008, 978-0-7695-3336-0/08, DOI 10.1109/CSSE.2008.185 [4] Yip Chi Kiong, Sellappan Palaniappan and Nor Adnan Yahaya, "Health Ontology System", 7th International Conference on IT in Asia (CITA), 2011 IEEE, 978-1-61284-130-4/11. [5] Mei-ying Jia, Bing-ru Yang, De-quan Zheng and Wei-cong Sun, "Research on Domain Ontology Construction in Military Intelligence", Third International Symposium on Intelligent Information Technology Application, 2009, IEEE, pp.116–119. [6] Song Jun-feng, Zhang Wei-ming, Xiao Wei-dong and Xu Zhen-ning, "Study on Construction and Integration of Military Domain Ontology, Situation Ontology and Military Rule Ontology for Network Centric Warfare", The 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service. [7] Maojun Huang, "On The Concept of Geographic Ontology—From The Viewpoints of Philosophy Ontology, Information Ontology and Spatial Ontology", 18th International Conference on Geoinformatics, 2010, IEEE. [8] Gang Liu, Yanni Wang and Chonglong Wu, "Research and Application of Geological Hazard Domain Ontology", 18th International Conference on Geoinformatics, 2010, IEEE. [9] Fragiskos A. Batzias and Christina G. Siontorou, "Creating a specific domain Ontology for supporting R&D in the science-based sector – The case of biosensors", Expert Systems with Applications, Volume 39, Issue 11, 1 September 2012, Pages 9994–10015. [10] Hui Xu and Debao Xiao, “Building Information Specification Ontology for Computer Network Management based on Formal Concept Analysis”, International Conference on Information and Automation, June 2009, pp. 312-317. [11] Hui Xu and Debao Xiao, "Common Ontology-based Intelligent Configuration Management Model for IP Network Devices", Innovative Computing, Information and Control, ICICIC '06, pp.385-388. [12] A.K.Y. Wong, An Chi Chen, N. Paramesh, P. Rav, "Ontology Mapping for Network Management Systems", Network Operations and Management Symposium, IEEE/IFIP, April 2004, Vol.1,pp.885- 886. [13] M.J. Taylor, D. Gresty and R. Askwith, "Knowledge for Network Support", Information and Software Technology, Volume 43, Issue 8, 1 July 2001, Pages 469–475. [14] Dieter Fensel, Frank van Harmelen, Ian Horrocks, Deborah L. McGuinness and Peter F. Patel- Schneider. "OIL: An Ontology Infrastructure for the Semantic Web", IEEE INTELLIGENT SYSTEMS, MARCH/APRIL 2001, pp.38-45. [15] OWL Web Ontology Language. Available: http://www.w3.org/TR/owl-features/ [16] World Wide Web Consortium (W3C). Available: http://www.w3.org/standards/semanticweb/ ontology [17] Protégé. Available: http://protege.stanford.edu/ [18] An Introduction to the Gene Ontology. Available: http://www.geneontology.org/GO.doc.shtml
  • 9. International Journal on Computational Sciences & Applications (IJCSA) Vol.3, No.4, August 2013 21 [19] About the Plant Ontology project. Available: http://www.plantontology.org/docs/otherdocs/poc _project.html [20] SWEET Ontologies. Available: http://sweet.jpl.nasa.gov/ [21] Foundational Model of Anatomy ontology - About. Available: http://sig.biostr.washington.edu/ projects/fm/AboutFM.html [22] OilEd. Available: http://oiled.semanticweb.org/index.shtml [23] KAON - The Karlsruhe Ontology and Semantic Web Tool Suite. Available: http://kaon. semanticweb.org/ [24] DAML+OIL. Available: http://www.w3.org/TR/daml+oil-reference [25] SHOE: Simple HTML Ontology Extensions. Available: http://www.cs.umd.edu/projects/plus/ SHOE/ [26] XOL Ontology Exchange Language. Available: http://www.ai.sri.com/pkarp/xol/