Publication detail

Extending Networking Curriculum with Applied Artificial Intelligence

MATOUŠEK, P. RYŠAVÝ, O. BURGETOVÁ, I.

Original Title

Extending Networking Curriculum with Applied Artificial Intelligence

English Title

Extending Networking Curriculum with Applied Artificial Intelligence

Type

conference paper

Language

en

Original Abstract

Artificial Intelligence (AI) and related technologies like data mining, machine learning or neural networks became very popular in recent years. Many IT companies today require graduated students to understand and be able to apply these technologies. Application potential of AI is not limited only to robotics, image processing or intelligent agents but also in engineering areas like computer networking and communication. However, on most universities, networking courses focus mainly on transmission protocols, network services and hardware design only while AI, machine learning or neural networks are taught separately. This causes a gap that emerges between AI theory and engineering approach. Thus, teachers of engineering courses are challenged how to introduce their students to an application of AI in the engineering areas, e.g., electronics, communication, embedded systems, power grids, etc. This paper shows how selected AI techniques presently used in computer networks can be incorporated into networking curriculum and demonstrated to students which extends student competencies and prepares them better into future jobs. We also present two case studies where AI techniques are applied on networking data in order to solve typical engineering problems.

English abstract

Artificial Intelligence (AI) and related technologies like data mining, machine learning or neural networks became very popular in recent years. Many IT companies today require graduated students to understand and be able to apply these technologies. Application potential of AI is not limited only to robotics, image processing or intelligent agents but also in engineering areas like computer networking and communication. However, on most universities, networking courses focus mainly on transmission protocols, network services and hardware design only while AI, machine learning or neural networks are taught separately. This causes a gap that emerges between AI theory and engineering approach. Thus, teachers of engineering courses are challenged how to introduce their students to an application of AI in the engineering areas, e.g., electronics, communication, embedded systems, power grids, etc. This paper shows how selected AI techniques presently used in computer networks can be incorporated into networking curriculum and demonstrated to students which extends student competencies and prepares them better into future jobs. We also present two case studies where AI techniques are applied on networking data in order to solve typical engineering problems.

Keywords

computer networking, curriculum, artificial intelligence, engineering education

Released

23.08.2019

Publisher

Institute of Electrical and Electronics Engineers

Location

Ruse

ISBN

978-1-7281-3222-8

Book

Proceedings of EAEEIE 2019

Edition

NEUVEDEN

Edition number

NEUVEDEN

Pages from

11

Pages to

16

Pages count

6

URL

Documents

BibTex


@inproceedings{BUT159982,
  author="Petr {Matoušek} and Ondřej {Ryšavý} and Ivana {Burgetová}",
  title="Extending Networking Curriculum with Applied Artificial Intelligence",
  annote="Artificial Intelligence (AI) and related technologies like data mining, machine
learning or neural networks became very popular in recent years. Many IT
companies today require graduated students to understand and be able to apply
these technologies. Application potential of AI is not limited only to robotics,
image processing or intelligent agents but also in engineering areas like
computer networking and communication. However, on most universities, networking
courses focus mainly on transmission protocols, network services and hardware
design only while AI, machine learning or neural networks are taught separately.
This causes a gap that emerges between AI theory and engineering approach. Thus,
teachers of engineering courses are challenged how to introduce their students to
an application of AI in the engineering areas, e.g., electronics, communication,
embedded systems, power grids, etc. This paper shows how selected AI techniques
presently used in computer networks can be incorporated into networking
curriculum and demonstrated to students which extends student competencies and
prepares them better into future jobs. We also present two case studies where AI
techniques are applied on networking data in order to solve typical engineering
problems.",
  address="Institute of Electrical and Electronics Engineers",
  booktitle="Proceedings of EAEEIE 2019",
  chapter="159982",
  doi="10.1109/EAEEIE46886.2019.9000455",
  edition="NEUVEDEN",
  howpublished="online",
  institution="Institute of Electrical and Electronics Engineers",
  year="2019",
  month="august",
  pages="11--16",
  publisher="Institute of Electrical and Electronics Engineers",
  type="conference paper"
}