SNR/RP Aware Routing Algorithm: Cross-Layer Design for MANETS

International Journal of Wireless & Mobile Networks (IJWMN), Vol 1, No 2, November 2009
127
SNR/RP AWARE ROUTING ALGORITHM:
CROSS-LAYER DESIGN FOR MANETS
Fuad Alnajjar1
and Yahao Chen2
Department of Electrical Engineering,
City College and Graduate Center of City University of New York
New York, USA
{1
fuad@ccny.cuny.edu ,2
ychen00@ccny.cuny.edu}
ABSTRACT
Routing in MANET is complex due to the fact that the network graph is episodically connected and nodes
get only intermittently connected because of nodes mobility, terrain, weather, and jamming that change
topology rapidly. In this paper, we propose cross-layer design to achieve a reliable data transmission in
MANET. A key challenge is to create a mechanism that can provide good delivery performance and high
quality of service in intermittent networks. The key components of our approach include a cross-layer
design (CLD) to improve information sharing between different protocol layers. In order to improve the
end-to-end performance of MANET, we present mechanism that allows the network layer to adjust its
routing protocol dynamically based on SNR and Received Power along the end-to-end routing path for
each transmission link. We evaluate our approach using one of common MANET routing protocols, DSR,
to illustrate that our CLD improved the performance of DSR.
KEYWORDS
Cross Layer Design, Mobile Ad-Hoc Networks, Routing Protocols, QoS, SNR & OPNET.
1. INTRODUCTION
A Mobile Ad hoc Network (MANET) is a dynamic wireless network with or without fixed
infrastructure. Nodes may move freely and arrange themselves randomly. The contacts between
nodes in the network do not occur very frequently. As a result, the network graph is rarely, if
ever, connected and message delivery required a mechanism to deal with this environment [1]
Routing in MANET using the shortest-path metric is not a sufficient condition to construct
high-quality paths, because minimum hop count routing often chooses routes that have
significantly less capacity than the best paths that exist in the network. [2]
Most of the existing MANET protocols optimize hop count as building a route selection.
Examples of MANET protocols are Ad hoc On Demand Distance Vector (AODV) [3],
Dynamic Source Routing (DSR) [4], and Destination Sequenced Distance Vector (DSDV) [5].
However, the routes selected based on hop count alone may be of bad quality since the routing
protocols do not ignore weak quality links which are typically used to connect to remote nodes.
These links usually have poor signal-to-noise ratio (SNR), hence higher frame error rates and
lower throughput. [6], [7].
The wireless channel quality among mobile nodes is time varying due to fading, Doppler Effect
and pathloss. Known that the shortest-path metric does not take into account the physical
channel variations of the wireless medium, it is desirable to choose the route with minimum cost
based on some other metrics which are aware of the wireless nature of the underlying physical
channel. In MANET, there are many other metrics to be considered: Power, SNR, Packet Loss,

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Maximum available bandwidth etc. These metrics should come from a cross-layer approach in
order to make the routing layer aware of the local issues of the underling layers. [8].
The ability of MANET to provide acceptable quality of service (QoS) is restricted by the ability
of the underlying routing protocol to provide consistent behavior despite the inherent dynamics
of a mobile computing environment. [9] [10].
Cross-Layer Design has enormous potential in wireless communication systems. By using Cross
Layer Design (CLD) we try to offer dedicated QoS for dedicated applications.
Our objective is to design a mechanism to provide an efficient QoS routing protocol to enhance
the performance of existing routing protocols in Mobile ad hoc network environment.
In this paper we select DSR as one of the common MANET protocols to demonstrate our two
models, Signal to noise Ratio (SNR) and Received Power (RP), to enhance the quality of
service of the DSR. We evaluate how the protocol differ in the methods it uses to select paths,
detect broken links, and buffer messages during periods of link outage. Our new approach is
called Signal to Noise Ratio/Received Power Aware Routing Algorithm (SNR/RP). We
computed differences in terms of packet delivery ratio, throughput, end-to-end latency, and
mechanism overhead. We show that the performance of DSR protocol improved by using the
proposed model.
The rest of this paper is organized as follows: Sec. 2 discusses related work. Sec. 3 gives
background about DSR. Sec. 4 presents the proposed cross layer design and model
optimization. Sec. 5 discusses simulation environment setup. Sec. 6 discusses simulation results
and finally Sec. 7 concludes the paper and Sec. 8 presents our future work.
2. RELATED WORK
Many proposals and models addressed quality of service (QoS) among mobile nodes of the
wireless networks and considered the link quality in their designs and architectures.
Wisitpongphan and et al. [11] proposed a bit error rate (BER)-based routing design, where the
chosen route is the one which guarantees the lowest BER at the ending node. They considered
providing QoS in terms of BER at the destination node.
[12] presented a mechanism to improve both the routing and data forwarding performance of
DSR, with lesser power consumption. This mechanism involves intelligent use of the route
discovery and route maintenance process thereby providing faster routing and reduced traffic as
compared to the basic DSR. This mechanism enables faster data forwarding and reduced
collisions with lesser power consumption.
In [8] authors modified DSR to work as three-state Markov model of the wireless channel
instead of two-state Markov model (Gilbert-Elliot model) by applying a higher order of Markov
chains. They applied their model to the Dynamic Source Routing protocol (DSR). In their
proposed modified DSR, both the route discovery and route selection are based on physical
layer parameter and the link monitoring function located at each node.
Authors in [13] proposed a simple extension of DSR. They presented a model to reduce routing
overhead in request process and the anycast group management protocol is discussed.
3. BACKGROUND
DSR stands as one of the common representatives of reactive routing protocols like all On-
Demand routing algorithms, Ad Hoc On-Demand Distance Vector (AODV), Dynamic MANET
On-demand (DYMO). DSR applies source routing rather than hop-by-hop routing, in which
each packet to be routed carrying in its header the full ordered list of nodes through which the
packet should pass. The key benefits of source routing is that intermediate nodes do not need to
maintain up-to-date routing information in order to route the packets they forward, since the

129
packets themselves already contain all the routing decisions. This fact, coupled with the on-
demand nature of the protocol, eliminates the need for the periodic route advertisement and
neighbor detection packets present in other protocols. [14]
In DSR source node generates a route request packet when it has a new route to a destination.
The route request is flooded through the network until it reaches some nodes with a route to that
destination. See figures 1 and 2.
Figure 1. S sends Route Request to D Figure 2. D sends Route Reply to S
Each route request packet holds the information of the route it has propagated. When the route
request packet arrives at the destination or an intermediate node with a route to the destination, a
route reply packet will be generated. This reply packet is then sent back to the source node
following the reverse route contained in the route request packet. While transmitting the data
traffic, the complete path is added to each data packet according to the routing table of the
source node. The intermediate nodes forward packets according to the path provided in the
packet. See figure (1.b).
More clearly, in DSR routing protocol to send route reply packet, when current route breaks,
destination seeks a new route. In this paper we try to change route selection mechanism. We
also define a signal to noise Ratio and received power parameters as new metrics in which those
values are added to the route reply packet. Given those features, source node can select the best
and more stable route out of various available routes based on Signal to Noise Ratio (SNR) or
Received Power (RP). Therefore we can improve the Quality of service (QoS) and the
performance of the routing protocols in MANET environment.
4. SNR/RP AWARE ROUTING ALGORITHM
(BEST OF WORSE END-TO-END ROUTING PATH)
Routing in MANET is difficult as a result of the dynamic nature of network topology and the
resource constraints. The issue of Link reliability in mobile ad hoc networks is a main problem
to transmit messages through the wireless channels. Routing in multi-hop wireless networks
using the shortest-path metric is not an adequate condition to build good quality paths, because
minimum hop count routing often selects paths that have significantly less capacity than the best
paths that exist in the network. [2]
Physical-layer limits of wireless channel because of: time-varying fading, multipath, co-channel
interference, hostile jamming, mobility, dynamic network topology.
In technicality, information from the transmission links, such as Signal to Noise Ratio (SNR)
and Received Power (RP), can furnish valuable information to the source node about the
transmission paths as far as routing is concerned. Each wireless node can communicate with any
other node within its transmission range, which depends on SNR and RP at the receiver node.
We modified the route reply packet format and added two extra fields in the packet format to
store the worst value of power strength (received power strength) and worst value of SNR
(signal-to-noise ratio) along the route from destination to source. See figure 3.
S
D
Route
Reply
Route
Request
S
D

130
Figure 3: Modified Route Reply packet format of DSR including metrics of SNR and RP.
Section 3 illustrated how original DSR works. We modified also the mechanism of DSR process
to include our SNR/RP model. The new mechanism will works as follows: when the route
request packet arrives at the destination or an intermediate node with a route to the destination, a
route reply packet will be generated. This reply packet is then sent back to the source node
following the reverse route contained in the route request packet. Each intermediate node will
update the SNR and RP values if its link values of SNR and RP lower than the existing recorded
values in the route reply packet. If SNR/RP values of its link are greater than recorded value, the
node will not update the value. The process will continue until the route reply packet reach the
source node. Now, at the source node there are many of available routes with different values of
SNR and RP. The Source node will select the route based on the value of best of worse
available values of SNR or RP. Figure 4 demonstrates the flow chart of how modified DSR
routing protocol works after implementing the SNR/RP model. Dotted-line areas in the figure
represents new process.
Figure 4. Flow chart shows how SNR/RP model works with DSR.
Figure 5 illustrates the mechanism of our new approach, SNR/RP aware routing algorithm when
it applies to DSR routing protocol. The values on links represent the values of Signal to Noise
Ratio of the link or values of received power of the link. When node S needs to send a packet to
node R. Node S sends 2 route request packets along path 1 and path 2. Node R generates 2 route
reply packets to node S along the reverse routes of paths 1 and 2. Now, at node S there 2
available routes to destination R, path 1 with 5 hops but the lowest value of SNR or RP found in
the end-to-end path is 3, and path 2 with 4 hops but the lowest value of SNR or RP found in the
end-to-end path is 2. Source node S will sort the two routes and select path 1 based on our new
mechanism since the best worse value of path 1 is 3 is grater than the worse value of the other
path which is 2. Traditional DSR protocol will select Path 2 that has minimum number of hops
eventhough the path has low-quality of service.

131
Figure 5: Scenario shows that modified DSR with SNR/RP will select path 1 (High QoS) rather
than path 2 (minimum number of hops).
Wireless channels have high channel bit error rate and limited bandwidth. The high bit error rate
degrades the quality of transmission and the network performance. A routing protocol that can
not quickly recover from link breakage caused by mobility renders a QoS model incapable of
meeting delivery requirements. [9]. Implementing our model will guarantee the Quality of
service in the environment of MANET where is QoS is low. Any routing protocol should be
smart enough to pick a stable and good quality communication route in order to avoid any
unnecessary packet loss.
Routing in MANET is challenging due to the dynamic nature of network topology and the
resource constraints. In our model, we create a mechanism that can provide good delivery
performance and high quality of service in MANET environment that characterized with
intermittent network and episodically connected and nodes get intermittently connected because
of nodes mobility, terrain, weather, and jamming to reach a reliable data transmission.
5. SIMULATION ENVIRONMENT
The cross-layer algorithm described above was implemented and evaluated in OPNET v 14.5
simulator [15]. Table 1 shows the parameters used in our simulation.
The fading modules contributed in [16] are included into account. The modulation, BPSK,
compute the BER under fading condition from the loop-up tables. We calculate the Doppler
shift velocity according to the ground speed, pitch, and yaw of the transmitting node and the
receiving node. Look up the fading amplitude according to the Rician K=5 factor. [17]. We
considered in our network topology to include fading, Doppler effect, various speed mobility.
A
7
2
5
4
5
4
6
7
3
9
Path 2
Path 1
B
D E
S R
W X Y Z
SNR/RP of link
C
5

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Table 1: simulation setup
Parameters Value
Network Size 3 x 3 Km
Modulation Scheme BPSK
Traffic rate 11 Mbps
Transmit Power 35 mW
Packet Reception-Power Threshold -75 dBm
Mobility model Random-Waypoint
Propagation–Path loss Free space
Propagation fading model Rayleigh, Rician
Rician K Factor 5
MAC protocol 802.11
Packet size 1024 bits
Routing protocol DSR
Carrier frequency 2.4 GHz
Nodes number 80
Transmission Range 300 - 400 m
Speed of nodes 3, 6, 9, 12 m/s
6. RESULTS
Simulation results show that according to the channel quality, the delay, received data and
throughput show significant improvement in performance when compared to traditional DSR.
Our results indicate that the cross-layer design using the model of Signal to Noise Ratio SNR
aware routing algorithm provides a better improvement in the Quality of Service when
compared to the traditional DSR routing protocol and the Received Power (RP) aware routing
algorithm improved the performance of traditional DSR.
It is immediately evident from the results given in figures 6-11 that our SNR/DSR model
improved the performance of traditional DSR.
Throughput (bits/sec)
0
2000
4000
6000
8000
10000
12000
14000
16000
18000
1 72 143 214 285 356 427 498 569 640 711 782 853 924 995 1066
Time (sec)
SNR DSR Power Received
Figure 6. SNR & RP models improve the throughput

133
Delay (Sec)
0
5
10
15
20
25
30
35
40
45
50
1 66 131 196 261 326 391 456 521 586 651 716 781 846 911 976
Time (Sec)
SNR DSR Power Recei ved
Figure 7. RP model reduces the delay
Traffic Received (Packets/sec)
0
10
20
30
40
50
60
70
80
90
100
1 68 135 202 269 336 403 470 537 604 671 738 805 872 939
Time (sec)
Figure 8. RP & SNR models improve the delivery rate
Total Acknowledgements Sent
0
1000
2000
3000
4000
5000
6000
1 69 137 205 273 341 409 477 545 613 681 749 817 885 953
Time (Sec)
Figure 9. RP & SNR models increase number of ACKs sent

134
Total Replies Sent from Destination
0
2
4
6
8
10
12
14
16
18
1 66 131 196 261 326 391 456 521 586 651 716 781 846 911 976
Time (Sec)
SNR DSR P ower Recei ved
Figure 10. SNR & RP models improve numbers of destination’s repliers
Total route errors sent
0
2000
4000
6000
8000
10000
12000
1 69 137 205 273 341 409 477 545 613 681 749 817 885 953
Time (sec)
SNR DSR P ower Recei ved
Figure 11. SNR & RP models reduced number of errors sent
7. DISCUSSION AND CONCLUSIONS
In this work, we modified the DSR protocol to choose routes according to the Signal to Noise
Ratio (SNR) or a Received Power (RP) criterion which is characterized with the best value of
SNR or RP of the weakest link along the route from destination to source to eliminate the routes
with bad links that has very low SNR and to improve QoS. We have presented our recent results
of the SNR/RP aware routing design to achieve reliable communication in networks associated
with intermittent connectivity. The challenge was to find a routing design that can deal with
dynamic environment causing networks to split and merge, considering nodes mobility, fading,
and Doppler Effect. Simulation results show that our model achieved better performance than
traditional DSR protocol in terms of delivery rate, delay, throughput over intermittent network.
8. FUTURE WORK
We intend to continue on developing the proposed model and provide a detailed analytical as
well as simulation-based study. Our future work will complete the research to implement
SNR/RP aware routing design on AODV, GRP, TORA and OLSR. Also, we will study and
analyze the impact of the physical layer parameters on the performance of the Delay Tolerant
Network (DTN)-based probabilistic routing protocols. We will design a cross-layer frame
assists information exchanges between different network layers, expedites upper layers’

135
response to quick changes of physical links and outside environment, and helps to optimize link
selections in MANET using DTN routing protocols. Our future work will complete the research
by implement DTN based routing algorithms in Aerial/terrestrial Airborne Network
environment.
ACKNOWLEDGEMENTS
This work is based on research sponsored by the Air Force Research Laboratory under agreement
FA8750-09-1-0158. The US Government is authorized to reproduce and distribute reprints for
Governmental purposes notwithstanding any copyright notation thereon.
DISCLAIMER
The views and conclusions contained herein are those of the authors and should not be interpreted as
necessarily representing the official policies or endorsement, either expressed or implied, of the Air Force
Research Laboratory or the US Government.
REFERENCES
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Networking System for Mobile Ad Hoc Networks”, in: PIMRC 2002, vol. 4, September 2002,
pp. 1952-1956
[3] C. E. Perkins and E. M. Royer, “Ad-hoc on-demand distance vector routing,” in Proc. IEEE
Workshop on Mobile Comp. Sys.and Apps., Feb. 1999, pp. 90-100.
[4] D. B. Johnson and D. A. Maltz, “Dynamic source routing in ad hoc wireless networks,” in
Mobile Computing, 1996, pp. 153-181.
[5] C. E. Perkins and P. Bhagwat, “Highly dynamic destinationsequenced distance-vector routing
(DSDV) for mobile computers“, Computer Communications Review, pp. 234-244, Oct.1994.
[6] H.M. Tsai, N. Wisitpongphan, and O.K. Tonguz, “Link-Quality Aware AODV Protocol,” in
Proc. IEEE International Symposium on Wireless Pervasive Computing (ISWPC) 2006, Phuket,
Thailand, January 2006
[7] E. Royer and C.-K. Toh, "A Review of Current Routing Protocols for Ad Hoc Mobile Wireless
Networks," IEEE Personal Communications Magazine, vol. 6, No. 2, April 1999.
[8] Merlinda Drini & Tarek Saadawi .”Modeling Wireless Channel for Ad-Hoc Network Routing
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Communications, 2005. Volume 3, 22-24 Aug.2005, Pages: 205-212
[10] Frank Aune “Cross-Layer Tutorial” NTNU 2004
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provisioning using BER-based routing for ad hoc wireless networks", IEEE Vehicular Tech.
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[14] Josh Broch, David A. Maltz, David B. Johnson, Yih-Chun Hu, Jorjeta Jetcheva, “A Performance
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[15] The OPNET simulator www.opnet.com
[16] R. J. Punnoose, P. V. Nikitin, and D. D. Stancil. “Efficient simulation of ricean fading within a
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Authors
Fuad Alnajjar received his BS degree from Sana’a University, Yemen
in 19994 and MS degree from the City College of City University of
New York (CUNY) in 2004. He is currently a Ph.D. candidate at the
Gradate Center of City
University of NY. His research interests include wireless mobile ad hoc
networks, Cross Layer Design, and Delay-Tolerant Networks.
Yahao Chen received his BS degree from City College of City University of
New York (CUNY) in 2009. He is currently a M.E. student at City College of
City University of NY. His research interests include wireless mobile ad hoc
networks, and Cross Layer Design.

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