| dc.description.abstract | Wireless mesh networks, WMNs, are networks with the ability to self-form, self-configure, and self-repair.
These features were inherited from the ad-hoc mobile networks, MANETs. However, WMNs appear as an
alternative to the use of MANETs due to their differences in architecture and radio technologies used. Within
WMNs, three paradigms of architecture stand out: WMNs with infrastructure, WMNs clients and WMNs hybrid
(as the combination of the two previous architectures). Furthermore, WMNs, having radio technologies based
on the 802.11 standard, are more convenient than the MANETs for routing information to the Internet. Both
MANETs and WMNs make use of mesh routers, MRs, for routing information.
The large number of mobile devices introduced in recent years has forced the creation of new topological
architectures based on WMNs. A clear example of modern architectures is the so-called WMN spontaneous.
This type of architecture is characterized by being made up only of mobile devices or end user nodes. Within this
type of architecture. The main characteristic is that all nodes act simultaneously both as user interface devices as
well as traffic routers for their peers. However, in order to optimize and make more efficient the operation of the
network. through topology control techniques, only a certain number of devices can be selected to act as the
network routers. This selection process classifies the nodes into two groups: the MRs and the client nodes of the
mesh network MCs. Thus, the routing of the traffic will be controlled only by the MRs. While the MCs will only
act as end-user devices
Studies such as [1, 2] have shown improvements in the performance of spontaneous WMNs networks,
through the use of topology control. This technique was carried out by combining two graph theory metrics,
betweenness centrality, and modularity. These two metrics were used to abstract the information from the
topology of the client mesh networks. In order to select only the most important nodes in the network as routers.
Through this topology control significant improvements in overall network efficiency are achieved over a network
in which all devices act as routers.
On the other hand, it is important to emphasize that being made up of end user devices, spontaneous WMNs
generate dynamic scenarios within their topology. This topology is constantly changing as users move from one
location to another. For this reason, mathematical models have been established in the literature that attempt to
emulate, in the most realistic way possible, the dynamic behavior of nodes on the network. These models have
been called mobility models. In a previous study [2], these realistic mobility models have been evaluated from
the perspective of efficient topology control.
Under these premises, the main objective of this work is to find and characterize the topological differences
within six realistic mobility models available in the literature and applied to the evaluation of wireless mesh
networks. These differences were established using six different graph theory metrics. Using the concept of
spontaneous WMNs, networks were simulated and evaluated in which the topologies changed according to the
chosen mobility model. In the end, conclusions were established that indicated which mobility models presented
the most relevant results within each metric.
Additionally, to illustrate an example of application of the analyzes carried out to mobility models. The
concepts of network integrity and robustness were used. For this, two mobility models were analyzed on each
metric. In each model, nodes were eliminated simulating a network attack. In order to evaluate the impact on the
packet delivery rate, PDR, resulting each time a node was eliminated. It could be observed that not all the metrics
delivered satisfactory results, so the application of network robustness based on these metrics specifically was
discarded. Complementarily, for these metrics an analysis of PDR and delay was made simulating networks with
a topological structure based on communities. Finally, conclusions were established on each mobility model and
each metric. Also, it was indicated the most relevant results obtained on each one.
This work has been carried out using different open access software tools widely used in the scientific
community. For the mobility traces, BM and SUMO have been used. For the simulation of the WMNs with
information traffic, the discrete event network simulator NS-3 has been used. The graph theory metrics have
been obtained using Gephi software. Lastly, the comparisons between the mobility models and the metrics have
been obtained using the Python platform | |
