Kohonen som with conscience function neural net based energy efficient clustering and routing wireless sensor networks
Other Title(s)
استخدام كوهينين مع دالي الضمير العصبونية لتوفير الطاقة و ذلك بإيجاد نموذج محسن للعنقدة و التوجيه اللاسلكي للشبكات
Dissertant
Thesis advisor
Comitee Members
Viktorov, Oleg
al-Hammuz, Sadiq
University
Middle East University
Faculty
Faculty of Information Technology
Department
Computer Science Department
University Country
Jordan
Degree
Master
Degree Date
2014
English Abstract
The current development within communication field lead to continuous and urgent needs for new data transfer techniques that can perform the communication process with high performance .
WSN emerged recently as a common and significant type of network which can be used within the environment that cannot be continuously managed by the human being.
To enhance WSN performance in terms of several criteria, including; lifetime and energy, then several procedures can be employed, such as; clustering.
KSOM was emerged as a technique for clustering in WSN.
The aim of this thesis is to evaluate the WSN performance in terms of average lifetime and consumed energy after adding conscience function of neural network.
The system is simulated in MATLAB software environment.
The performance was evaluated in two stages, the first stage investigate and compare the performance for Kohenon and KSOM, and the second stage investigates the effect of adding conscience function of neural network to the KSOM.
The results confirmed the effectiveness of KSOM and it is improvement for both energy consumption and network lifetime in comparison with Kohenon technique.
Furthermore the conscience function of the NN will in turns enhance the performance of the WSN over KSOM algorithm, and hence over SOM algorithm.
KSOM achieved an enhancement of 30.7% and 2.22% over Kohenon algorithm in terms of Lifetime and average energy respectively at 400 nodes number.
Furthermore, enhancements of 13.33% and 3.03% were achieved due to applying conscience function in terms of average lifetime and average consumed energy respectively at 200 nodes.
Main Subjects
Information Technology and Computer Science
No. of Pages
71
Table of Contents
Table of contents.
Abstract.
Abstract in Arabic.
Chapter One : Introduction.
Chapter Two : Related works.
Chapter Three : Methodology and system implementation.
Chapter Four : Results and discussion.
Chapter Five : Conclusion and future works.
References.
American Psychological Association (APA)
al-Azzam, Sad. (2014). Kohonen som with conscience function neural net based energy efficient clustering and routing wireless sensor networks. (Master's theses Theses and Dissertations Master). Middle East University, Jordan
https://search.emarefa.net/detail/BIM-699510
Modern Language Association (MLA)
al-Azzam, Sad. Kohonen som with conscience function neural net based energy efficient clustering and routing wireless sensor networks. (Master's theses Theses and Dissertations Master). Middle East University. (2014).
https://search.emarefa.net/detail/BIM-699510
American Medical Association (AMA)
al-Azzam, Sad. (2014). Kohonen som with conscience function neural net based energy efficient clustering and routing wireless sensor networks. (Master's theses Theses and Dissertations Master). Middle East University, Jordan
https://search.emarefa.net/detail/BIM-699510
Language
English
Data Type
Arab Theses
Record ID
BIM-699510
