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Using multiple metrics with the optimized link state routing protocol for wireless mesh network


Abstract and Figures

Wireless mesh networks (WMNs) can be used in many different ap-plications. However, they lack standards and, as a consequence, a number of issues must still be addressed to ensure the proper functioning of these networks. Amongst these issues, routing is this paper's main concern. Thus, we propose the use of multiple metrics with the proactive Optimized Link State Routing (OLSR) protocol, in order to provide quality of service routing. Even though it has already been proved that routing with multiple metrics is an NP-complete problem, we show how the techniques of Analytic Hierarchy Process (AHP) and Pruning may be combined to perform multiple-metric routing, offering the best available routes based on the considered metrics. A study on the performance of the metrics considered for the proposal is also carried out in the NS simulator.
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Using Multiple Metrics with the Optimized Link State Routing
Protocol for Wireless Mesh Networks
Waldir A. Moreira Jr.1,4, Elisangela Aguiar2,4, Antˆ
onio Abel´
em3,4, Michael Stanton5
1Programa de P´
ao em Ciˆ
encia da Computac¸˜
ao (PPGCC)
2Programa de P´
ao em Engenharia El´
etrica (PPGEE)
3Faculdade de Computac¸˜
4Grupo de Redes de Computadores e Comunicac¸˜
ao Multim´
ıdia (GERCOM)
Universidade Federal do Par´
a, Rua Augusto Corrˆ
ea 01, 66075-110, Bel´
em, PA, Brazil
5Instituto de Computac¸˜
Universidade Federal Fluminense, Rua Passo da P´
atria 156, bloco E, sala 350,
24210-240, Niter´
oi, RJ, Brazil
{mraranha, eaguiar, abelem},
Abstract. Wireless mesh networks (WMNs) can be used in many different ap-
plications. However, they lack standards and, as a consequence, a number of
issues must still be addressed to ensure the proper functioning of these networks.
Amongst these issues, routing is this paper’s main concern. Thus, we propose
the use of multiple metrics with the proactive Optimized Link State Routing
(OLSR) protocol, in order to provide quality of service routing. Even though
it has already been proved that routing with multiple metrics is an NP-complete
problem, we show how the techniques of Analytic Hierarchy Process (AHP) and
Pruning may be combined to perform multiple-metric routing, offering the best
available routes based on the considered metrics. A study on the performance of
the metrics considered for the proposal is also carried out in the NS simulator.
1. Introduction
Over the years wireless mesh networks (WMNs) have shown their usefulness in differ-
ent scenarios, especially those where extending already existing networking services is
desired but cabling is not a feasible alternative.
As a result, these networks provide a more versatile and inexpensive solution if
compared to wired, and even some other wireless, technologies. They became quite pop-
ular mainly due to their extended coverage, robustness, self-configuration, easy mainte-
nance and low cost features [Lee et al. 2006].
Some examples of the great utility of WMNs include: to extend the coverage area
of enterprises and universities; to reach areas where cabling is somehow difficult due to
cost and/or physical obstacles; to provide communications in emergency situations such
as earthquakes, fire fighting, and other catastrophes; to provide public Internet access; to
operate intelligent transportation systems; and to help in military and rescue operations
[Bruno et al. 2005].
However, even though WMNs are considered to be very useful, they still lack stan-
dards, and this has resulted in the emergence of many different solutions, proprietary or
26° Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos
not, that are not interoperable among themselves. In fact, the IEEE 802.11 working group
is investigating proposals which will specify the WMN functionalities, to be incorporated
in the IEEE 802.11s standard.
Besides the standardization problem, the problem of WMN routing is also of great
interest, and must be carefully addressed to guarantee the proper functioning of WMNs.
Due to these WMN characteristics (dynamic topology, lack of resources as band-
width, security, and scalability), WMN routing protocols must display the features of
self-management, self-configuration, and self-healing [Bruno et al. 2005].
Many different routing protocols have already been proposed. However, these
protocols are unable to answer all the needs of this kind of network because each of them
was developed to deal with a specific application [Kowalik and Davis 2006].
A number of different approaches have been considered in order to develop WMN
routing protocols, including the use of heuristics, a single metric, a single compound
metric, a single mixed metric, a composite metric, multiple metrics, and multidimensional
metrics [Costa et al. 2002] [Badis et al. 2003] [Aslam et al. 2004] [Alkahtani et al. 2006]
[Faccin et al. 2006]. Multiple metrics are of interest to this paper.
This paper’s main goal is to use multiple metrics with the proactive Optimized
Link State Routing (OLSR) protocol, to guarantee the selection of routes which are com-
posed of good quality links. However, it is worth pointing out that the problem of working
with multiple additive/multiplicative metrics in any combination is non-trivial, and turns
out to be NP-complete [Wang and Crowcroft 1996] [Badis et al. 2003].
A solution for getting around the NP-complete problem when integrating multiple
metrics may be achieved by combining the two techniques known as Analytic Hierarchy
Process (AHP) and Pruning. This becomes our secondary goal which is applying these
two simple techniques normally used in wired scenarios to a WMN context.
The idea is to use the AHP multi-criteria technique, a methodology of decision
analysis developed by [Saaty 1980] to aid in the decision of choosing the best route be-
tween a given source and destination. [Alkahtani et al. 2006] proposed a solution which
made use of this technique for wired networks with good results. Yet, this solution suffers
from great complexity due to the number of matrix computations required to determine
the best route. [Alkahtani et al. 2006] suggest changes to the size of the matrices being
calculated, which would reduce the number of steps required to determine the best route
as well as to reduce this complexity.
There is no need to say that the complexity is even greater in a WMN context,
since all nodes might be able to ”sense” all, or most of, the other ones present in the
network. As a result, the size of the matrices increases, and that is what we would like to
So, we introduce a second technique, called Pruning, to be applied before the first
AHP step in order to improve AHP’s computations. This technique simply gets rid of
the paths that are not feasible, that is, those which have qualities exceeding the desired
threshold. Both techniques will be detailed in Section 4.
The remainder of this paper is organized as follows. Section 2 presents related
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work. Section 3 gives a general overview on WMNs, routing protocols, and link quality
metrics. Section 4 presents the AHP and Pruning techniques. A case study using simu-
lation is presented in Section 5. Finally, Section 6 presents the conclusions and current
2. Related Work
This section presents previously published work on matters related to this paper. The
following publications provide relevant information on WMNs, defining these networks,
showing their applicability, and pointing out important issues currently being investigated.
[Akyildiz et al. 2005] present a detailed study on advances and open research is-
sues related to all protocol layers in WMNs highlighting system architectures, applica-
tions, testbeds, commercial practices and related standards activities. Case studies, tech-
nical issues and solutions for developing WMNs, as well as an overview on standardiza-
tion of mesh technology, are presented by [Faccin et al. 2006]. [Held 2005] explores some
WMN applications and protocol operations, analyzing problems affecting these networks
as well as suggesting solutions for each of them.
An overview on mesh technology is provided by [Bruno et al. 2005] using exam-
ples of proprietary and commercial solutions, concepts on which WMNs must be based,
and challenges faced by WMN design. Another overview on mesh technology, pointing
out some standards which are applicable to the concept of multihop techniques in different
wireless networking technologies, is presented in [Lee et al. 2006].
[Nandiraju et al. 2007] discuss challenges slowing down the development of
WMNs, showing how each layer of the network could be improved to address such
challenges. Finally, [Zhang et al. 2007] point out problems and challenges in designing
WMNs, considering a number of important issues, and detailing techniques to improve
WMN performance.
Regarding routing, [Clausen and Jacquet 2003] provide important information on
the protocol considered in this paper, OLSR. Reasons for the existence of so many differ-
ent WMN routing protocols are presented in [Kowalik and Davis 2006].
A number of different approaches have been proposed for improving WMN rout-
ing, which may simply combine different metrics with OLSR, or create new routing pro-
tocols. [Costa et al. 2002] evaluate the use of a single mixed metric and heuristics, com-
pared with the multiple individual metric approach, to speed up routing computations,
with the former presenting outstanding results. [Badis et al. 2003] propose a single metric
solution to achieve QoS routing. The use of a composite metric for routing improvement
is explored in [Aslam et al. 2004]. A new protocol is proposed by [Alkahtani et al. 2006]
using a multiple metric approach, while [Faccin et al. 2006] discuss how multidimen-
sional metrics can be used for QoS routing.
The metrics we study in this paper for integration are Expected Trans-
mission Count, Minimum Loss, and Minimum Delay, and these are described
in [DeCouto et al. 2003], [Passos et al. 2006], and [Cordeiro et al. 2007], respectively.
However, the use of multiple metrics is non-trivial, and [Wang and Crowcroft 1996] prove
it turns out to be NP-complete problem. [Saaty 1980] presents one of the techniques con-
sidered in this paper to solve the NP-completeness problem, and [Alkahtani et al. 2006]
26° Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos
present a routing protocol based on this technique known as Analytic Hierarchy Process
A second technique, Pruning, can be used to improve routing computations, when
more than one additive/multiplicative metric is considered, and [Costa et al. 2002] de-
scribe its use with excellent outcomes.
3. Wireless Mesh Networks
WMNs have self-organizing, self-configuring, and self-healing features with easy de-
ployment/maintenance at a very reasonable cost providing high scalability and reliable
services as well as improving capacity, connectivity, and resiliency of the already exist-
ing network. Due to these characteristics, WMNs have been recognized as a promising
technology, which will play an important role in future generations of wireless networks.
These networks are an extension of wireless ad hoc networks [Bruno et al. 2005].
However, protocols and architectures developed for ad hoc networks have a weak per-
formance when applied to WMNs. This is explained by the differences between these
two kinds of networks, regarding their applicability, deployment goals and the resource
limitations to which they are subjected [Held 2005].
3.1. Routing metrics in WMNs
WMNs are a combination of mobile and fixed nodes which communicate through wireless
links forming a multi-hop network.
In most cases, WMN nodes are fixed and not battery operated. Thus WMN routing
protocols must focus on reliability and performance improvement rather than dealing with
mobility or minimizing energy consumption.
Giving the characteristics of the WMN scenario under consideration (fixed
nodes and small number of nodes), proactive protocols are more suitable for it
[Zhang et al. 2007]. Amongst the proactive protocols, Optimized Link State Routing
(OLSR) protocol [Clausen and Jacquet 2003] has been widely used in mesh solutions
[Passos et al. 2006].
However, the original OLSR is not quite suitable for WMNs since it does not take
into account the link quality while computing routing tables. Instead, it considers the min-
imum hop count to determine the best path to reach a given destination. This metric, hop
count, has been shown not to be at all useful in multi-hop networks [DeCouto et al. 2003].
As a result, researchers started to propose metrics based on what constitutes a good qual-
ity link. That is, these metrics reflect the quality of each link, and the routing protocol
considers this information when computing its routing tables.
Many proposals have been made to improve WMN routing. The use of heuristics,
a single metric, a single compound metric, a single mixed metric, a composite metric and
multiple metrics are some of the solutions which have been proposed to create new routing
protocols, or simply to be combined with OLSR in order to improve its performance
[Costa et al. 2002] [Badis et al. 2003] [Aslam et al. 2004] [Alkahtani et al. 2006].
This paper focuses mainly on the combination of two metrics with OLSR, and
evaluates the performance of the ones presented as follows.
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3.1.1. Expected transmission count (ETX) [DeCouto et al. 2003]
The goal here is to choose routes with the minimum expected number of transmissions
(including retransmissions) a packet will need to be delivered and have its receipt ac-
knowledged. Consequently, the selected routes have high throughput. The main advan-
tage is that probe packets are broadcast, which results in reduced probing overhead. The
main disadvantage resides in the fact that the probe packets are small and are sent at the
lowest data rate possible, and tend not to suffer the same loss rate as larger data packets
sent at higher data rates.
3.1.2. Minimum loss (ML) [Passos et al. 2006]
This is based on ETX, with the aim of selecting the path with the minimum loss proba-
bility. It uses the probability of successful transmissions, and not the inverse probability,
as in ETX. Another difference is related to a route composed of two or more links. The
route probability is given by the product of the link probabilities instead of the sum of
their inverse probabilities. It has the advantage of eliminating high loss rate routes, and
the disadvantage that some low quality links may still be taken into account in choosing
a given route, since the metric considers only the total probability product.
3.1.3. Minimum Delay (MD) [Cordeiro et al. 2007]
The routing table computation is based on the total minimum transmission delay. The
transmission delay measurements come from a variant of a link capacity estimation tech-
nique, known as Adhoc Probe. The use of the Adhoc Probe technique is a great advan-
tage, because it takes into account differences in clock synchronization, thus providing
a more reliable measurement. A disadvantage is that this metric considers routes which
have nodes sharing a collision domain with many others, and this tends to degrade the
communication on such routes.
It is worth pointing out that, for this proposal, we only considered metrics that
are frequently discussed on the available related researches such as ETX. Since we have
proposed another metric, MD, we decided to simulate it along with ETX and ML in order
to determine the two metrics to be considered for the proposal.
4. Techniques for Combining Multiple Metrics with OLSR
It has been proved that the selection of routes based on the combination of additive and/or
multiplicative metrics is NP-complete [Wang and Crowcroft 1996] [Badis et al. 2003].
However, there is a technique which can be used to get around the NP-
completeness of the use of multiple metrics, known as Analytic Hierarchy Process. Thus,
a secondary goal of this proposal is to combine another technique, called Pruning, to
AHP in order to reduce its complexity still offering routes based on the best link qualities
available at the moment.
This section is intended to present what these techniques are and how they work.
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4.1. Analytic Hierarchy Process (AHP) [Saaty 1980]
AHP is widely known in the field of decision making, when different qualitative and/or
quantitative criteria must be applied. A number of applications already make use of this
methodology, in fields such as telecommunications and the provision of health services.
By making small changes to the methodology, [Alkahtani et al. 2006] proposed a
routing protocol which takes different metrics into account, when deciding the best route
to a given destination. The goal was to provide support for multimedia applications which
are characterized by multiple Quality of Service (QoS) requirements.
To illustrate the approach proposed by [Alkahtani et al. 2006], we apply it to the
network in Figure 1 shown below. It is worth pointing out that this network is a small
WMN where every node may have a link to every other one unless they are too far apart.
Every link has two metrics: ETX and MD, for this example. Finally, we assume we wish
to set up a connection between nodes 1 and 4.
Figure 1. Example of a small network
Step 1: First, we need to find all possible routes between nodes 1 and 4. Ta-
ble 1 shows each possible path along with its respective overall values of ETX and
MD. Further information for these metrics can be found in [DeCouto et al. 2003] and
[Cordeiro et al. 2007], respectively.
Table 1. Possible paths
Paths A B C D
Links 124 134 1234 1324
ETX 2.19 2.25 3.23 3.45
MD 1.01 0.20 0.51 1.40
Step 2: The computation of the path-path pair-wise comparison matrix (ppcm)
for each metric is carried out to determine how well each path is scored for each metric
compared to the other paths. [Alkahtani et al. 2006] define three criteria: min - metrics
to be minimized (i.e. delay), max - metrics to be maximized (i.e. bandwidth), and bin -
binary nature metrics (i.e. link security - 1: secure, 0: insecure). Since ETX and MD are
quantitative metrics which need to be minimized, the matrix calculation is based on the
following equations. Here iand jare paths, and mjis the overall value of the metric for
ppcm(i, i)=1, when comparing the same path;
ppcm(j, i) = 1/ppcm(i, j), for reciprocal paths; and
ppcm(i, j) = mj/mi, for min criterion.
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As an example, the ppcm for ETX is given by:
ppcm(ET X ) =
1 1.027 1.475 1.575
0.973 1 1.436 1.533
0.678 0.697 1 1.068
0.635 0.652 0.936 1
Step 3: The normalized path-path pair-wise comparison matrix (nppcm) is calcu-
lated, based on the following equation with iand j= 1, .., P, where Pis the number of
paths (four in this example):
nppcm(i, j) = ppcm(i, j )/Σppcm column(j)
As a result:
nppcm(ET X ) =
0.3043 0.3043 0.3043 0.3043
0.2962 0.2962 0.2962 0.2962
0.2063 0.2063 0.2063 0.2063
0.1932 0.1932 0.1932 0.1932
Step 4: The average normalized path-path pair-wise comparison matrix (anppcm)
is calculated, based on the following equation:
anppcm(i) = Σnppcm row(i)/P
The anppcm matrix is [nxP] where nis the number of metrics and Pis the number
of paths. The anppcm for ETX is:
anppcm(ET X ) = h0.3043 0.2962 0.2063 0.1932 i
Steps 2 - 4 must be carried out for every metric. And as result, the complete
anppcm is showed below. It is worth mentioning that each line of this matrix refer to the
metrics ETX and MD, respectively.
anppcm ="0.3043 0.2962 0.2063 0.1932
0.1143 0.5770 0.2263 0.0824 #
Step 5: The average normalized priority pair-wise comparison matrix (anprpcm)
is calculated to determine the relative importance of each metric compared with the other
metrics. For the original AHP, an absolute number is given to each metric, based on the
decision maker’s feelings. Then Steps 2 - 4 are performed to find the anprpcm. An-
other modification proposed by [Alkahtani et al. 2006] is that these metrics are assigned
weights directly in the range [0, 1] where the sum of all weights is equal to one, as pre-
sented in the matrix below.
anprpcm =h0.5 0.5i
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Step 6: Select the required priority of metrics, if more than one priority is set. In
this example, the priority set is 0.5 for both ETX and MD, since priority is not considered
for this paper.
Step 7: Calculation of the total score for each path, Table 2, through the equation:
P athjscore =
(anprpcm[i]×anppcm[i, j]), j = 1, ..., P
Table 2. Total scores for each path
Paths A B C D
Total Score 0.2093 0.4366 0.2163 0.1378
Step 8: Select the path with the maximum total score to be used in the communi-
cation between nodes 1 and 4. As it can be seen, path B is the one that has the best link
quality overall.
To reduce the number of matrix computations, it would be enough to make ppcm
and nppcm be P x 1 matrices instead of P x P, since the columns of the P x P nppcm have
the same values. Thus, Step 5 would be eliminated.
This technique is a very interesting approach to get around the NP-completeness
problem of using multiple metrics for routing.
However, if the WMN is quite large, there may be a large number of possible
paths between a source and destination, due to the fact that each node may ”hear” a major
part of, if not all, the surrounding nodes. This situation will result in a large number of
calculations in order to obtain just ppcm and nppcm. To combat this, we adopt another
technique, Pruning.
4.2. Pruning
This technique has been applied to many different applications in order to improve their
performance [Costa et al. 2002].
It consists of eliminating links which have quality values greater than or equal to
a given threshold. To determine this threshold, we need to know both the network and
the functioning of the metrics used in this scenario. For this proposal, we calculate the
threshold through the median of ETX values of the links, discarding links with values
above this threshold since ETX is to be minimized.
In the previous example, path D in Table 1 would not even be determined since
one of its links has the highest values for the ETX and MD metrics. By doing this, the
number of possible paths calculated between the source and destination can be reduced,
improving even more the performance of the AHP technique.
5. Case Study
In this section we present the scenario used in carrying out simulations, and how the
routing metrics were chosen.
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5.1. Scenario
The simulations attempted to reproduce the behavior of the metrics to be used in the
routing protocol for a WMN backbone at the main campus of the Federal University of
a, in Bel´
em, Par´
a state, Brazil. This campus is located by the Guam´
a river within a
large wooded area, and and contains many buildings separated by parking areas. Figure 2
shows the WMN scenario under consideration.
Figure 2. Federal University of Par ´
a Campus
Since this scenario happens to be in a tropical region, deploying an outdoor wire-
less network is rather challenging due to sometimes heavy rain and the number of trees
present in the area.
5.2. Metrics used
To decide which metrics were to be used for routing, simulations were run to determine
the metrics’ performance in the aforementioned scenario. These simulations were carried
out on Network Simulator 2.31 [NS 2007] using different seeds for the random number
generator. A confidence interval of 95% was considered for the calculations according to
[Jain 1991]. Each simulation was run for 50 seconds and repeated 10 times.
The two metrics with the best overall performance would be considered for the
routing protocol. To show that the real scenario and equipments were closely represented
in the simulation, some variables were chosen, as shown in Table 3.
It is worth pointing out that the values of Path Loss Exponent and Shadowing
Deviation could have been obtained directly from the NS manual [NS 2007]. However,
the values used here were obtained from field measurements carried out at each of the
ten points as shown in Figure 2. Using a notebook computer running the NetStumbler1
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Table 3. Simulation Parameters
Parameters Values
IEEE Standard 802.11b
Propagation Model Shadowing
Antennas Omnidirectional, 18dB gain
Router’s Carrier Sense Threshold -76dBm [IEEE 1999]
Router’s Receiver Sensitivity -80dBm [IEEE 1999]
Router’s Transmit Power 17dBm (WRT54G)
Frequency 2.422GHz (Channel 3)
Path Loss Exponent 1.59
Shadowing Deviation 5.4dB
software with a GPS device attached to it, measurements took place at each point, as
illustrated in Figure 3 for the Capacit point and discussed below.
Figure 3. Paths taken for data gathering
At each point, data was collected in eight different ways starting close to the point
and moving away from it until a signal level of -85 dB was reached. The directions of
measurement took into account the position of the point in regards to other neighboring
points. Once the measurements had been carried out, a final value was attributed to each
variable by calculating the average based on the data collected at each point.
In the simulator, a total of six Voice over Internet Protocol (VoIP) calls and
three background Paretto traffic flows were simulated. These calls involved the fol-
lowing points: Capacit/Graduac¸˜
ao Profissional, Reitoria/Capacit, Reitoria/CT, DI/CT,
orio, and DI/Secom, and the points with background traffic were:
orios, Graduac¸˜
ao B´
asico/CT, e Secom/Graduac¸ ˜
ao Profissional. For each of
the metrics, jitter, delay, blocking probability and throughput were calculated, and are
shown in Figure 4. Since a VoIP call is bidirectional, each call is represented by two
flows. The same indicators were also calculated for the original OLSR, which uses hop
count as a metric. These points were selected so that the communication between them
happened through three hops at most and nodes really competed for the wireless medium.
For jitter, OLSR-ML had the highest variation amongst the metrics, as can be
seen in Figure 4a. OLSR-ETX and OLSR-MD had the best performance in regards to
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throughput as shown in Figure 4b.
In Figure 4c, OLSR-ML had the best performance amongst the metrics, but its
values still are not considered appropriate for VoIP calls. This high-delay behavior is
explained by the number of different flows attempting to use wireless medium in the sim-
ulations. It is important to mention that, during the calls, the protocol was still computing
its routing tables during the beginning of the VoIP calls. This was done on purpose, in
order to determine the performance of each metric in the worst-case scenario. As for the
blocking probability, Figure 4d, OLSR-ML also had the highest values.
(a) Jitter per VoIP flow (b) Throughput per VoIP flow
(c) Delay per VoIP flow (d) Block Probability per VoIP flow
Figure 4. Results obtained from the simulations
It is important to remember that the main goal here is to choose the metrics with
the best performances in the scenario under consideration to be used in the proposal.
Original OLSR was simulated only for comparison purposes. Even having performed
better for some flows than the other metrics, it was not considered for use in WMN rout-
ing, since it is widely known that it does not take into account the quality of a given
link. Instead, it uses the shortest path approach, that is, the minimum number of hops
between a given source and destination. And that is not useful in a mesh network context
[Faccin et al. 2006].
From the results, the metrics ETX and MD had the best overall performance for
the considered scenario, and thus they were chosen for use with OLSR to improve its
routing table computations.
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5.3. A Practical Example
For the following practical example, consider the scenario presented in Figure 2. As the
mesh network simulated high-gain antennas, every node is able to ”sense” all the other
nodes despite the distance between them. It is important to point out that this is not a
problem since every routing decision is made considering the link qualities, ETX and
Table 4 shows the routing table of each node in the network with the metrics’
values for every link towards all other nodes at a given time.
Table 4. Nodes and their respective routing tables
Firstly, Pruning is applied to get rid of links of unsatisfactory quality, and the
metric considered was ETX. To do this, the median is calculated and links with ETX
values equal to or greater than the median are pruned since this metric is to be minimized.
We could also consider MD for pruning threshold calculation since we are not prioritizing
any of these metrics as in [Saaty 1980]. In Table 4, the median is in bold digits and the
pruned links’ values are in italics.
As the first step of the AHP solution requires all possible routes to be found,
Pruning becomes very important. Dijkstra’s algorithm [Cormen et al. 2001] can be run to
find all these paths. Without Pruning, a total of 48.929 possible paths were found, whilst
with this technique the number of paths was reduced to 256. Thus, the goal of reducing
the computational complexity mentioned earlier is achieved.
Both metrics, ETX and MD, make use of Dijkstra’s algorithm to determine the
best route, that is, the one with the least cost among the possible routes found. For this
example, we wish to determine to best route between nodes 0 and 9. The best route,
through nodes 0 - 4 - 5 - 9, ended up to be the same for both ETX (7.0833) and MD
Since this proposal aims to select routes which combine the best quality values of
the considered metrics, after the application of AHP and Pruning the best selected route
should be the same as for ETX/MD or another one even better. It is important to point out
that even though ETX was considered for Pruning, priority of metrics was not taken into
26° Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos
account and anprpcm in Step 5 remained unchanged. So, applying the remaining steps
of the solution in [Alkahtani et al. 2006], the route obtained was also through nodes 0 -
4 - 5 - 9 with a maximum total score of 0.0066343. Hence, we also attain the goal of
combining multiple metrics with OLSR in order to provide selection of the best route.
6. Conclusions and Current Work
The main goal of this paper was to provide QoS routing for Wireless Mesh Networks
through the application two simple techniques, Analytic Hierarchy Process and Pruning,
normally used in wired scenarios, and that together may improve OLSR’s performance
through the usage of multiple metrics.
Although the solution presented by [Alkahtani et al. 2006] was proposed for a
wired scenario, it does have great potential for application in a wireless network context.
However, the complexity of this solution may be high, due to the many matrix computa-
tions which are a result of the number of possible paths between a source and destination.
In WMNs, this complexity may become even greater, since most, or even all, of the nodes
are able to ”sense” the other ones present in the network.
With that in mind, the Pruning technique comes into play to lessen the number
of matrix computations, and thus reducing even more the complexity of the solution pre-
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which really improved their results.
Unlike only having improvements either on throughput or transmission delay,
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26° Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos
... While SCOR can be used to model variety of QoS routing algorithms in SDN, the selected routing algorithms were modelled to illustrate the expressive power and completeness of SCOR. A small set of these models were selected to evaluate various aspects of SCOR in- Widest Path [10] Chapter 7 3 Bandwidth-Guaranteed [16] Chapter 6 4 Bandwidth-Constrained [10] Chapter 6 5 Minimum-Loss Path [17] Chapter 6 6 Minimum-Fixed Delay Path [17] Appendix-A2 7 ...
... While SCOR can be used to model variety of QoS routing algorithms in SDN, the selected routing algorithms were modelled to illustrate the expressive power and completeness of SCOR. A small set of these models were selected to evaluate various aspects of SCOR in- Widest Path [10] Chapter 7 3 Bandwidth-Guaranteed [16] Chapter 6 4 Bandwidth-Constrained [10] Chapter 6 5 Minimum-Loss Path [17] Chapter 6 6 Minimum-Fixed Delay Path [17] Appendix-A2 7 ...
... This SCOR model implements the least cost path routing (LCPR) algorithm [10]. Using different parameters as the cost metrics allows to use exactly the same model for modelling several different routing algorithms such as minimum (transmission) delay routing [17] , minimum loss routing [17] and shortest path routing. Shortest path routing is one of the most applied routing algorithms in networking which is used in common routing protocols such as OSPF, RIP and IGRP. ...
Full-text available
While Software Defined Networks (SDN) has been introduced to facilitate innovation in networking, and to simplify the creation of new applications, there are domains in which these SDN promises are far from being realised. One such area is Quality of Service (QoS) routing and Traffic Engineering (TE). Despite the vital importance of QoS and TE in today's networks, SDN currently does not provide sufficiently powerful abstractions and interfaces to facilitate the development of QoS and TE applications. This thesis addresses this gap by introducing a new northbound interface for SDN. A northbound interface provides the connection between network services and applications that use them. The northbound interface proposed here is based on constraint programming techniques to provide a robust, declarative interface for stating networking problems in SDN. It is called Software-defined Constrained Optimal Routing (SCOR) which is proposed with its corresponding routing framework in this thesis. This routing framework is based on SDN's architecture model and uses SCOR as its northbound interface. The main advantage of SCOR, hiding the complexity of solving the problem from the user, is inherited from its constraint programming roots. Accordingly, the user only states the constraints and utility functions of the routing problem and the solution is provided by a powerful generic solver. SCOR is implemented in the MiniZinc constraint modelling language consisting of nine fundamental constraint programming predicates, which cover different aspects of the routing problems. It is shown that this interface (set of predicates) is sufficiently expressive to handle all the known and relevant QoS routing problems. Furthermore, the practicality and scalability of the approach are demonstrated via a number of example scenarios, with varying network topologies, network sizes and number of rows. Real-world applications are also modelled by implementing the proposed routing framework in a carrier-grade SDN controller, ONOS, to demonstrate the practical feasibility and benefits.
... algorithm to support QoS routing and provide optimal path selection for varying smart meter traffic. The idea to use AHP technique for adaptively supporting AMI traffic in NAN is conceived from [5] and [6], which used it for conventional wireless and wired networks. This paper explore the possibility of supporting QoS using this technique on a grid topology NAN based WMN which involve transmission of variable AMI traffics to a data concentrator. ...
... Considering that the functionality of SG is dependent on the ability of different applications meeting certain performance requirements, proposing multiple metric implemented within the existing routing protocols can guarantee the QoS of the variety of traffic in SG AMI network. Though the selection of route based on a combination of multiplicative metric have been proved to be NP-complete [10], techniques such as the AHP and Pruning proposed in [5], have been used to get around the NP-completeness of multiple metric protocols. ...
... An application of the Analytical AHP algorithm for multiple prioritised metrics was proposed for connectionoriented point-to-point communications in [6]. The use of AHP for multiple metrics with OLSR to improve routing in wireless mesh network and deal with high QoS demands was also proposed in [5]. Considering the different applications with special QoS requirement in AMI; changing route priority to meet some special requirements for some traffic is a highly desirable attribute for routing protocols in NANs. ...
Conference Paper
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Routing in Neighbourhood Area Network (NAN) for Smart Grid's Advanced Metering Infrastructure (AMI) raises the need for Quality of Service (QoS)-Aware routing. This is due to the expanded list of applications that will result in the transmission of different types of traffic between NAN devices (i.e smart meters). In wireless mesh network (WMN) routing, a combination of multiple link metrics, though complex, has been identified as a possible solution for QoS routing. These complexities (i.e Np complete problem) can be resolved through the use of Analytical Hierarchy Process (AHP) algorithm and pruning techniques. With the assumption that smart meters transmit IP packets of different sizes at different interval to represent AMI traffic, a case study of the performance of three Optimised Link State Routing (OLSR) link metrics is carried out on a grid topology NAN based WMN in ns-2 network simulator. The best two performing metric were used to show the possibility of combining multiple metrics with OLSR through the AHP algorithm to fulfill the QoS routing requirements of targeted AMI application traffic in NANs.
... This decision is based upon the information provided by link metric. Therefore, primary emphasis has been given to propose new link metrics of different varieties; a single metric, a single mixed metric, a single compound metric, multiple metrics and a composite metric are few examples that have been designed and implemented with the existing protocols [78]. Thus, while designing a link metric for a routing protocol, following design requirements must be taken into account. ...
... We use the implementation of ETX, Minimum Delay (MD) [76], and ML [77] with OLSR [78] in NS2-2. 34. ...
This dissertation endeavors to contribute enhancements in goodputsof the IEEE 802.11-based Wireless Multi-hop Networks (WMhNs).By performing exhaustive simulations, for the deep analysis and detailed assessment of both reactive (AODV, DSR, DYMO) and proactive (DSDV, FSR, OLSR) protocols for varying mobilities, speeds, network loads and scalabilities, it is observed that a routing link metric is a significant component of a routing protocol. In addition to finding all available paths, the fastest end-to-end route is selected by a link metric for the routing protocol. This study aims the quality routing. In the class of quality link metrics, Expected Transmission Count (ETX) is extensively used. Thus, the most recently proposed ETX-based metrics have been analyzed. Though, newly developed metrics over perform ETX but still they can be improved. By profound analysis and particularized comparison of routing protocols depending upon their classes (reactive and proactive) and ETX-based metrics, we come to realize that users always demand proficient networks. In fact, WMhNs are facing several troubles which they expect to be resolved by the routing protocol operating them. Consequently, the protocol depends upon the link metric for providing quality paths. So, we identify and analyze the requirements to design a new routing link metric for WMhNs. Because, considering these requirements, when a link metric is proposed, then : firstly, both the design and implementation of the link metric with a routing protocol become easy. Secondly, the underlying network issues can easily be tackled. Thirdly, an appreciable performance of the network is guaranteed. Keeping in view the issues of WMhNs, increasing demands of users and capabilities of routing protocols, we propose and implement a new quality link metric, Interference and Bandwidth Adjusted ETX (IBETX). As, MAC layer affects the link performance and consequently the route quality, the metric therefore, tackles the issue by achieving twofold MAC-awareness. Firstly, interference is calculated using cross-layered approach by sending probes to MAC layer. Secondly, the nominal bit rate information is provided to all nodes in the same contention domain by considering the bandwidth sharing mechanism of 802.11. Like ETX, our metric also calculates link delivery ratios that directly affect throughput and selects those routes that bypass dense regions in the network. Simulation results by NS-2 show that IBETX gives 19% higher through put than ETX and 10% higher than Expected Throughput (ETP). Our metric also succeeds to reduce average end-to-end delay up to 16% less than Expected Link Performance (ELP) and 24% less than ETX
... In addition to the presence of losses, the other objective of d exp is to find high throughput paths. To compute f d (l) and r d (l), as in [10] [11]. The number of previously received probes are kept by each probe in window of size 10. ...
Conference Paper
In this work, we propose a novel quality link metric; Bandwidth adjusted Inverse ETX (BIETX) for Static Wireless Multi-hop Networks (SWMhNs). The proposed metric considers two path selection parameters into account i.e., packet delivery ratio and link capacity. For computing packet delivery ratios in BIETX, the mechanism of Expected Transmission Count (ETX) is adopted. On the other hand, we take two methods of computing link capacity in BIETX. These methods are based upon the size of pair probes; equal size and different size. We also enhance Optimized Link State Routing (OLSR) protocol while using BIETX. A comparative analysis of proposed metric with equal size and different size pair probe; BIETX-1 and BIETX-2, with two existing quality metrics (ETX and Expected Transmission Time (ETT)) in SWMhNs is also a part of this work. From simulation results, we conclude that BIETX-2 outperforms rest of the metrics because of low routing load in ad-hoc probes, and low routing latencies due to enhancements of routing update frequencies and window size in OLSR.
... Mostly WMN routing problem has been considered as a single objective problem, but it can have more than one objective . A number of assorted approaches have been proposed for improving WMN routing, which includes the utilization of heuristics , a single metric, a composite metric, multiple metrics and multidimensional metrics78934]. In a very few papers, it has been treated as a multiobjective problem. ...
Full-text available
In this paper, we introduce SCOR (Software-defined Constrained Optimal Routing), a new Software Defined Networking (SDN) Northbound Interface for QoS routing and traffic engineering. SCOR is based on constraint-programming techniques and is implemented in the MiniZinc modelling language. It provides a powerful, high-level abstraction layer, consisting of 10 basic constraint-programming predicates. A key feature of SCOR is that it is declarative, where only the constraints and utility function of the routing problem need to be expressed, and the complexity of solving the problem is hidden from the user, and handled by a powerful generic solver. We show that the interface (set of predicates) of SCOR is sufficiently expressive to handle all the known and relevant QoS routing problems. We further demonstrate the practicality and scalability of the approach via a number of example scenarios, with varying network topologies, network sizes and number of flows.
Conference Paper
In this paper, we introduce SCOR (Software-defined Constrained Optimal Routing), a new SDN Northbound Interface for QoS routing and traffic engineering. SCOR is based on constraint programming techniques and is implemented in the MiniZinc modelling language. It provides a powerful, high level abstraction, consisting of 9 basic constraint programming predicates. A key feature of SCOR is that it is declarative, where only the constraints and utility function of the routing problem need to be expressed, and the complexity of solving the problem is hidden from the user, and handled by a powerful generic solver. We show that the interface (set of predicates) of SCOR is sufficiently expressive to handle all the known and relevant QoS routing problems. We further demonstrate the practicality and scalability of the approach via a number of example scenarios, with varying network topologies, network sizes and number of flows.
The traditional routing protocols used in wireless mesh networks like AODV are not very efficient since the number of hops to a destination is mainly considered as the routing metric. This may lead to shorter paths; however, the throughput can decrease when traffic is routed through those paths. Various contributions have proposed different metrics or completely different routing algorithms. Nevertheless, for many of these metrics, real-time network performance monitoring is required, increasing their overhead, while the implementation of many of the proposed routing protocols is not feasible in practice because of their complexity. In this paper, we aim to optimize link metrics together with routing. We preserve the shortest path routing principle but with optimizing the link metrics; thus, combining the shortest path algorithm's low overhead with an optimized link metrics scheme. We present a two-phase scheme for the considered problem. During the first phase, we seek for the optimal link scheduling for minimizing the required time slots and then, in the second phase, we present a mixed integer programming model for metric-driven routing design. For comparison, we also present the optimization models for global optimized routing and shortest-hop routing, providing numerical results.
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This document describes the Optimized Link State Routing (OLSR) protocol for mobile ad hoc networks. The protocol is an optimization of the classical link state algorithm tailored to the requirements of a mobile wireless LAN. The key concept used in the protocol is that of multipoint relays (MPRs). MPRs are selected nodes which forward broadcast messages during the flooding process. This technique substantially reduces the message overhead as compared to a classical flooding mechanism, where every node retransmits each message when it receives the first copy of the message. In OLSR, link state information is generated only by nodes elected as MPRs. Thus, a second optimization is achieved by minimizing the number of control messages flooded in the network. As a third optimization, an MPR node may chose to report only links between itself and its MPR selectors. Hence, as contrary to the classic link state algorithm, partial link state information is distributed in the network. This information is then used for route calculation. OLSR provides optimal routes (in terms of number of hops). The protocol is particularly suitable for large and dense networks as the technique of MPRs works well in this context.
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Professor Jain has written a text on the performance analysis of computer systems which can serve as a reference for both specialists and nonspecialists alike. His text is divided into six parts, each of which consists of a half-dozen or so chapters, and covers diverse topics ranging from Measurement Tools to Experimental Design. Each part of this reference text presumes a minimum of exposure to the field and little or no facility with mathematical technique. The author’s style is light and even entertaining, although it is clear that significant practical experience has informed the overall design of the text and the specific material selected. As the author correctly states in his introduction: “There are many books on computer systems performance. These books discuss only one or two aspects of performance analysis, with a majority of the books being queueing theoretic. Queueing theory is admittedly a helpful tool, but knowledge of simulation, measurement techniques, data analysis and experimental design is invaluable.” His aim was to fill a void by writing a book that integrates these rather diverse aspects of performance analysis, and I believe that he has largely succeeded. Part I of his text, “An Overview of Performance Analysis,” discusses performance techniques and metrics, but only after presenting common mistakes which can be made (consciously and otherwise) in presenting performance data and reaching conclusions. This part of the text sets the style: short chapters with witty headings, each of which emphasizes central ideas and encapsulates significant results in a bold face “box.” Each chapter ends with a list of exercises and each part ends with a list of references for further reading. Part II studies measurement techniques and tools, beginning with a discussion of workload selection and their characterization. Software and hardware monitors, capacity planning, and the art of data presentation is surveyed and this part ends with a discussion of “ratio games.” The witty and particularly relevant heading for this last topic is: “If you can’t convince them, confuse them.” Part III is entitled “Probability Theory and Statistics”, with the emphasis not surprisingly on the latter. Confidence interval estimation, a brief mention of hypothesis testing, and a discussion of regression models completes this part. Although this part is an attempt to make the text self-contained, one obviously cannot do justice to these concepts in a quick survey, and the author’s attempt is no exception. Part IV is a serious attempt to survey experimental design and analysis techniques. Factorial designs with and without replication, fractional factorial designs, and one- and two-factor experiments are considered in succession. These topics are often ignored by the performance analysis community, and they are a welcome addition to a text of this kind. Part V is an introduction to simulation techniques, and Part VI surveys simple and widely used queuing models. The author explains the major pitfalls of a simulation clearly and with emphasis – beginning Part V with sage advice: “The best advice to those about to embark on a very large simulation is often the same as Punch’s famous advice to those about to marry: Don’t!” Part IV is a brief introduction to queueing theory which only brushes the surface of this important performance analysis tool. Nevertheless, the standard models (from the M/M/1 single-server model through product form queueing networks) are explained briefly and their essential formulas are recorded. This last part of the text has the form of a “cook book,” and the better part of wisdom to this reviewer would have been to forgo the more complex models (queueing networks certainly), and emphasize the more widely used and more easily digested single-server models. Professor Jain has drawn on his considerable practical experience at the Digital Equipment Corporation in writing this book, and some of the material has been used by him in a graduate seminar on computer systems at the Massachusetts Institute of Technology. Overall, this text draws together much of the material required by the practicing performance analyst in an enjoyable and easo-to-read form.
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This work is based on measurements of the ReMesh wireless mesh network deployed over the city of Niterói, Brazil. It uses a modified version of the OLSR ad hoc routing protocol. OLSR has the goal of maximizing throughput by minimizing the number of transmissions over the wireless shared medium selecting routes based on the sum of the expected transmission count (ETX) of each link from a source node towards a destination node. Because of routing instabilities and the high packet loss rates (PLR) observed with the original OLSR algorithm, this work uses an algorithm for selecting multi-hop paths based on minimum loss probability along the entire path. Test results show that the mesh network performance has been improved, leading to more stable routes, lower packet loss rates, shorter delays and in many cases a small increase in network throughput.
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A link state routing approach makes available de-tailed information about the connectivity and the condition found in the network. OLSR protocol is an optimization over the classical link state protocol, tailored for mobile ad hoc networks. In this article, we design a QoS routing scheme over OLSR protocol, called QOLSR. In our proposal, we introduce more appropriate metrics than the hop distance used in OLSR. In order to improve quality requirements in routing information, delay and bandwidth measurements are applied. The implications of routing metrics on path computation are examined and the relational behind the selection of bandwidth and delay metrics are discussed. We first consider algorithms for single-metric approach, and then present a distributed algorithm for multiple metrics approach. We also present a scalable simulation model close to real operations in Ad Hoc Networks. The performance of our protocol are extensively investigated by simulation. Our results indicate that the attained gain by our proposal represent an important improvement in such mobile wireless networks.
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Wireless Mesh Networks (WMNs) are a type of radio-based net-work systems which require minimal configuration and infrastructure. They can be build using relatively low cost radios and inexpensive computing platforms, and consequently appear to be a compelling option for rolling out networks with a low deployment cost. One of the factors which influences the performance of WMNs is the routing protocol used. There are many routing protocols for WMNs, we estimate that there are more than a hundred of them. In this paper we attempt to answer the question why there are so many and if there is a need for such an abundance. Moreover, we elaborate on the possible development of a single routing protocol for WMNs.
Conference Paper
This paper presents the expected transmission count metric (ETX), which finds high-throughput paths on multi-hop wireless networks. ETX minimizes the expected total number of packet transmissions (including retransmissions) required to successfully deliver a packet to the ultimate destination. The ETX metric incorporates the effects of link loss ratios, asymmetry in the loss ratios between the two directions of each link, and interference among the successive links of a path. In contrast, the minimum hop-count metric chooses arbitrarily among the different paths of the same minimum length, regardless of the often large differences in throughput among those paths, and ignoring the possibility that a longer path might offer higher throughput.
Quality of service (QoS) based routing provides QoS guarantees to multimedia applications and an efficient utilization of the network resources. Nevertheless, the QoS-routing algorithm must be simple because a costly procedure does not scale with the size of the network. This paper proposes and analyzes the performance of the single mixed metric (SMM) routing protocol in two versions: one based on distance-vectors and the other on link-states. SMM takes into account three metrics: propagation delay, available bandwidth, and loss probability. A heuristic based on the residual loss probability and metric-combination is used to turn the algorithm scalable and solvable in polynomial time. The simulation results show that SMM outperforms other solutions that implement QoS routing based on three metrics.
Wireless mesh networks (WMNs) consist of mesh routers and mesh clients, where mesh routers have minimal mobility and form the backbone of WMNs. They provide network access for both mesh and conventional clients. The integration of WMNs with other networks such as the Internet, cellular, IEEE 802.11, IEEE 802.15, IEEE 802.16, sensor networks, etc., can be accomplished through the gateway and bridging functions in the mesh routers. Mesh clients can be either stationary or mobile, and can form a client mesh network among themselves and with mesh routers. WMNs are anticipated to resolve the limitations and to significantly improve the performance of ad hoc networks, wireless local area networks (WLANs), wireless personal area networks (WPANs), and wireless metropolitan area networks (WMANs). They are undergoing rapid progress and inspiring numerous deployments. WMNs will deliver wireless services for a large variety of applications in personal, local, campus, and metropolitan areas. Despite recent advances in wireless mesh networking, many research challenges remain in all protocol layers. This paper presents a detailed study on recent advances and open research issues in WMNs. System architectures and applications of WMNs are described, followed by discussing the critical factors influencing protocol design. Theoretical network capacity and the state-of-the-art protocols for WMNs are explored with an objective to point out a number of open research issues. Finally, testbeds, industrial practice, and current standard activities related to WMNs are highlighted.