![](/images/graphics-bg.png)
Genetic algorithm for dynamic clustering of wireless sensor networks
العناوين الأخرى
الخوارزمية الجينية للتجميع الداينميكي لشبكات المتحسسات اللاسلكية
مقدم أطروحة جامعية
مشرف أطروحة جامعية
أعضاء اللجنة
Khalid, Lamya Hafiz
al-Fayiz, Muhammad Z.
Stephan, Jane Jalil
الجامعة
جامعة بغداد
الكلية
كلية العلوم
القسم الأكاديمي
قسم علوم الحاسبات
دولة الجامعة
العراق
الدرجة العلمية
ماجستير
تاريخ الدرجة العلمية
2011
الملخص الإنجليزي
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.
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الموضوعات
عدد الصفحات
106
قائمة المحتويات
Table of contents.
Abstract.
Abstract in Arabic.
Chapter One : Introduction.
Chapter Two : Routing problem in wireless sensor networks.
Chapter Three : Metaheuristics and the clustering problem.
Chapter Four : Cluster-based routing protocols with Metaheuristic methodology.
Chapter Five : Simulation results and discussion.
Chapter Six : Conclusion and future work.
References.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Ibrahim, Inan Amin Khalil. (2011). Genetic algorithm for dynamic clustering of wireless sensor networks. (Master's theses Theses and Dissertations Master). University of Baghdad, Iraq
https://search.emarefa.net/detail/BIM-605644
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Ibrahim, Inan Amin Khalil. Genetic algorithm for dynamic clustering of wireless sensor networks. (Master's theses Theses and Dissertations Master). University of Baghdad. (2011).
https://search.emarefa.net/detail/BIM-605644
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Ibrahim, Inan Amin Khalil. (2011). Genetic algorithm for dynamic clustering of wireless sensor networks. (Master's theses Theses and Dissertations Master). University of Baghdad, Iraq
https://search.emarefa.net/detail/BIM-605644
لغة النص
الإنجليزية
نوع البيانات
رسائل جامعية
رقم السجل
BIM-605644
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
![](/images/ebook-kashef.png)
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر
![](/images/kashef-image.png)