Genetic algorithm for dynamic clustering of wireless sensor networks

Other Title(s)

الخوارزمية الجينية للتجميع الداينميكي لشبكات المتحسسات اللاسلكية

Dissertant

Ibrahim, Inan Amin Khalil

Thesis advisor

Atiyyah, Bara Ali

Comitee Members

Khalid, Lamya Hafiz
al-Fayiz, Muhammad Z.
Stephan, Jane Jalil

University

University of Baghdad

Faculty

College of Science

Department

Department of Computer Science

University Country

Iraq

Degree

Master

Degree Date

2011

English Abstract

Wireless sensor networks (WSNs) have gradually emerged as a cutting-edge technology to develop new ambient intelligence for the 21st century.

The basic philosophy behind WSNs is that, while the capability of each sensor node is limited, the aggregated power for the entire network is sufficient to meet the required mission.

Because of the limited sensor‘s energy, energy-awareness is one of the most crucial and challenging bottlenecks in WSNs, which has triggered the race for developing effective and energy-awareness routing protocols.

Hierarchical routing protocols are the best key technique known in regard to drastically reduce the energy consumption and prolong the lifespan of the network.

Low Energy Adaptive Clustering Hierarchy (LEACH) is a fundamental and popular protocol in this class.

Other protocols, such as stable election protocol (SEP), are concerned with another contradictory objective which is critical for many applications where the feedback from the WSN must be reliable: extending the stability period of the network measured by the lifetime until the first node dies.

Evolutionary Algorithms (EAs) have also attracted attention for developing cluster-based routing protocols in WSNs.

The main goal of these EA-based clustered routing protocols is to reduce the consumption of energy resources of the network, and in turn, to prolong the network lifetime.

These EA-based protocols proved to outperform LEACH in prolonging WSN lifetime but at the expense of decreasing the time interval before the death of the first node.

The interest of this thesis is two-fold.

The first contribution concerns with reformulating the design of the most important characteristic of the EA (i.e., the objective function), so as to obtain a routing protocol that can maximize the network lifetime, or at the best scenario, guarantee a better tradeoff between the network lifetime and the lifetime until the first node dies (to our knowledge, no attempt has been made to obtain a better compromise between these two contradictory objectives).

The second contribution, on the other hand, concerns with designing an EA-based routing protocol that hypothesizes a possible energy-based heuristics for the individual solution's initialization, fitness evaluation, and mutation to properly maintain longer stability and shorter instability periods for WSNs (to the best of our knowledge, this is the first attempt to utilize EA in this direction).

To support the claims of the proposed EA-protocols, extensive simulations on 90 homogeneous and heterogeneous WSN models are evaluated and compared against LEACH, SEP, and one of the existing evolutionary-based routing protocols, hierarchical clustering algorithm based genetic algorithm (HCR).

For the first objective, the results report that the proposed EA-based protocols always prolong the network lifetime, and moreover, one of the proposed protocols, viz.

energy-aware evolutionary routing protocol (EAERP) gets the better tradeoff between the network lifetime until the first node dies and the total network lifetime.

For the second objective, the proposed protocols always prolong the stability period and decrease the instability period.

Main Subjects

Information Technology and Computer Science

Topics

• Artificial intelligence
• Data processing

No. of Pages

106

Table of Contents

• APA
• MLA
• AMA

Language

English

Data Type

Arab Theses

Record ID

BIM-605644