الفهرس 
Chapter 1: IntroductionOnly 14 pages are availabe for public view
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Abstract
The field of Ad-hoc networks has seen a rapid expansion of visibility and work due to
the rapid increase of inexpensive, widely available wireless devices and the network
community’s interest in mobile computing. Such networks are taking special great
attention from research community due to their wide range of applications. One of the
most important requirements, in Ad-hoc networks, is to avoid the partitioning
problem of the network that may happen due to dynamic movement or failure of
special node(s) called ”Critical Node(s)”. A critical node refers to the node that its
removal from the network will break the network into many partitions.
Many researchers presented different algorithms to detect critical node(s) in ad hoc
networks. Nevertheless, most of these algorithms did not take the situation where
two nodes together may also cause network separation if they are moved or
removed at the same time. Indeed, because of the expensive and difficulty of real
experiments, simulation technique is the primary methodological framework for
research and development of such networks. However, an important problem in
simulation of ad hoc networks is how to generate a connected graph to represent the
network.
This thesis first presents a literature survey of the most recent methods that concern
the generation of network graphs. Then, it introduces two novel and fast algorithms
for generating topologies of Ad-hoc networks. The proposed approaches enable the
user to generate various network topologies by deciding number of nodes, radio range
and minimum distance between any two adjacent nodes in the graph. Finally, this
thesis presents a new technique called Two Critical-Nodes Detection Algorithm
(TCNDA) to detect both individual critical node(s) and each pair of nodes that are
critical together in Ad-hoc networks.
The proposed approaches are evaluated and compared with the most recent
algorithms by simulation. Numerical results demonstrate that the proposed
approaches speed up simulation of Ad-hoc networks and achieve an essential
computational cost reduction in comparing with the most recent methods.