Achieving self-healing in service specific overlay networks
Other Title(s)
تحقيق المعالجة الذاتية في الشبكات الفوقية ذات الخدمة المتخصصة
Dissertant
Subayh, Bassam Muhammad Salim Yusuf
Thesis advisor
Bani Muhammad, Sad
al-Uqayli, Ibrahim
Comitee Members
al-Rababiah, Mamun S.
Ababinah, Ismail M.
Samarah, Samir
University
Al albayt University
Faculty
Prince Hussein Bin Abdullah Faculty for Information Technology
Department
Department of Computer Science
University Country
Jordan
Degree
Master
Degree Date
2011
English Abstract
An Overlay network is a virtual network implemented on top of a physical network.
The use of overlay networks has been suggested as an alternative solution that can provide additional services that do not exist in the underlying network, such as controlling the routing infrastructure, increasing network security, and reducing duplicate messages through multicast.
To get end-to-end Quality of Services (QoS) in the internet, Service Specific Overlay Networks (SSONs) has been designed to deliver media in heterogeneous environments.
A single SSON is built to meet each user service requirements.
The increase in complexity and heterogeneity of these networks, changing conditions in the network and different types of faults that may occur, renders their control and management more difficult.
Therefore, self-healing concept was introduced to handle these changes and assure highly reliable and dependable network system performance.
Self-healing is a property that allows a system to perceive whether it is working properly or not.
In addition it makes the necessary adjustment that can automatically restore the services affected by a failure in a manner that is seamless to the end user. In this thesis, a novel self-healing architecture for autonomic SSONs is presented.
The proposed self-healing architecture targets applications that involve multimedia delivery services and are designed to meet user requirements.
These services are realized using overlay networks.
A service consists of a Media Client (MC) that requests the service, a Media Server (MS) that provide the service, and a set of Media Ports (MPs) that are used to process the multimedia data along the end-to-end path.
Our proposed solution is uses new approaches for monitoring, diagnosing and recovering of services thus achieving self-healing.
Moreover, two novel algorithms were proposed to realize the proposed architecture functionality.
The proposed algorithms take into account the dynamic nature of SSONs.
They probe the dynamic changes of overlay members where a MP may fail, leave, or join the network.
Simulation has been conducted to test the validity of the proposed algorithms.
Results show the efficiency and validity of our approach in term of disruption time and how they are effective in terms of success rate, and network load.
Main Subjects
Information Technology and Computer Science
Topics
No. of Pages
66
Table of Contents
Table of contents.
Abstract.
Chapter One : introduction and motivation.
Chapter Two : literature survey and background.
Chapter Three : self-healing architecture for service specific overlay networks.
Chapter Four : simulation results.
Chapter Five : conclusion and future works.
References.
American Psychological Association (APA)
Subayh, Bassam Muhammad Salim Yusuf. (2011). Achieving self-healing in service specific overlay networks. (Master's theses Theses and Dissertations Master). Al albayt University, Jordan
https://search.emarefa.net/detail/BIM-321630
Modern Language Association (MLA)
Subayh, Bassam Muhammad Salim Yusuf. Achieving self-healing in service specific overlay networks. (Master's theses Theses and Dissertations Master). Al albayt University. (2011).
https://search.emarefa.net/detail/BIM-321630
American Medical Association (AMA)
Subayh, Bassam Muhammad Salim Yusuf. (2011). Achieving self-healing in service specific overlay networks. (Master's theses Theses and Dissertations Master). Al albayt University, Jordan
https://search.emarefa.net/detail/BIM-321630
Language
English
Data Type
Arab Theses
Record ID
BIM-321630
