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Improving the understanding of the dynamic properties of advanced communication networks by using agent-based modeling approach

Improving the understanding of the dynamic properties of advanced communication networks by using agent-based modeling approach / Nur Syazana Mat Yusof
Rangkaian komunikasi moden semakin maju dan kompleks. Oleh itu, sistem kompleks menjadi bidang baru bagi penyelidik untuk meneroka bagaimana aspek sistem menimbulkan tingkah laku kolektif sistem dan bagaimana sistem berinteraksi dengan persekitarannya. Tingkah laku sistem yang kompleks adalah bagaimana konstituen rangkaian bertindak bersama untuk membentuk tingkah laku keseluruhan, bukan hanya tingkah laku aspek konstituen. Kerumitan sedemikian dapat dilihat dalam banyak jenis rangkaian komunikasi yang canggih seperti rangkaian ad-hoc tanpa wayar, rangkaian sensor mudah alih dan rangkaian radio kognitif. Dalam rangkaian ini, kerumitan yang tidak dapat diramal adalah timbul daripada mobiliti, jalur lebar terhad, latensi, gangguan dari rangkaian jiran dan perubahan tipologi. Di samping itu, stesen mudah alih dalam rangkaian ad-hoc dijangka akan menjadi autonomi dalam membuat keputusan mereka sendiri dan untuk bekerjasama dengan stesen bergerak lain dalam mengatur rangkaian. Kerumitan rangkaian komunikasi yang semakin meningkat ini mempunyai implikasi yang mendalam untuk pemodelan dan simulasi. Oleh kerana rangkaian menjadi lebih kompleks, ujian dan penilaian reka bentuk dan pelaksanaan menjadi lebih sukar. Terdapat banyak model sedia ada yang digunakan untuk menggambarkan rangkaian yang rumit. Projek ini cuba menggunakan model pemodelan dan simulasi baru, iaitu pendekatan pemodelan berasaskan ejen. Oleh itu, projek ini menggunakan model perisian bernama Netlogo untuk membantu memahami dan mengonsepkan projek ini. Keputusan menunjukkan bahawa pemodelan berasaskan agen adalah model yang lebih baik berbanding dengan model tradisional seperti Swarm dan MASON, terutamanya ketika memodelkan rangkaian komunikasi rumit. _______________________________________________________________________________________________________ Modern communication networks are getting more advanced and complex. Therefore, complex systems become a new field for researchers to explore how aspects of a system give rise to the collective behaviors of the system and how the system interacts with its environment. The behavior of a complex system is how network constituent act together to form the behavior of the whole, not only the behavior of the constituent aspects. Such a complexity can be seen in the many types of advanced communication networks such as wireless ad-hoc network, mobile sensor network, and cognitive radio networks. In these networks, complexity and unpredictable arise from the mobility, limited bandwidth, latency, interference from neighboring networks, and typological changes. In addition, mobile stations in ad-hoc networks are expected to be autonomous in making their own decision and to cooperate with other mobile stations in organizing the network. This rising complexity of the communication networks has a profound implication for modeling and simulation. As the networks are becoming more complex, testing and evaluation of the design and implementation are becoming more difficult. There are many existing models used to depict complex networks. This project use new modeling and simulation approach, which is the agent-based modeling approach. Thus, this project will go through a software model named as Netlogo to aid in understanding and conceptualizing about this project. The results show that agentbased modeling is a better model compared to traditional models such as Swarm and MASON, especially when modeling complex communication networks.
Contributor(s):
Nur Syazana Mat Yusof - Author
Primary Item Type:
Final Year Project
Identifiers:
Accession Number : 875007706
Language:
English
Subject Keywords:
Modern; communication networks; advanced
First presented to the public:
6/1/2018
Original Publication Date:
8/10/2018
Previously Published By:
Universiti Sains Malaysia
Place Of Publication:
School of Electrical & Electronic Engineering
Citation:
Extents:
Number of Pages - 102
License Grantor / Date Granted:
  / ( View License )
Date Deposited
2018-08-14 12:18:25.27
Date Last Updated
2019-01-07 11:24:32.9118
Submitter:
Mohd Jasnizam Mohd Salleh

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