Mobil Ad Hoc Networks Protocol Design Part 5 ppt

Mobile Ad-Hoc Networks: Protocol Design

192
sequence h
1
, h
2
, …, h
k
, x represents the current partial path. Each l
i
contains a total of b
time slots that are found to be available for h
i
to transmit to h
i+1
, with the exception that
h
k
's intending receiver is host x.
• NH: a list next-hop hosts of the format ((h
1
', l
1
'), (h
2
', l
2
'), …). Each host h
i

' has potential
to serve as the next hop of host x to extend the current partial path (so the new path will
be h
1
, h
2
, …, h
k
, x, h
i
'). However, this will depend on whether h
i
' has sufficient time slots
or not (this will become clear in the protocol). The corresponding parameter l
i
' contains
b time slots that can be used by x to transmit to h
i
' without collision.
When a route is found, we need to initiate from the destination D a packet QREP(S, D, id,
PATH) to the source S. This packet will travel on the reverse direction of PATH and reserve
time slots, as discovered, on the path. These parameters carry the same meanings as above.
3.3 Protocol details
Now suppose a host y receiving a broadcasting packet QREQ(S, D, id, b, x, PATH, NH)
initiated by a neighboring host x. If the same route request (uniquely identified by (S, D, id))
has not be heard by y before, it will perform the following steps:

A1. if (y is not a host listed in NH) then
exit this procedure.
else

Let (h
i
', l
i
') be the entry in NH such that h
i
' = y.
Construct a list PATH_temp = PATH|(x, l
i
'), where | means list concatenation.
end if.

A2. Construct two temporary tables, ST_temp[1 n, 1 s] and RT_temp[1 n, 1 s], as follows.
i. Copy all entries in ST
y
[1 n, 1 s] into ST_temp[1 n, 1 s], and similarly copy all entries in
RT
y
[1 n, 1 s] into RT_temp[1 n, 1 s].
ii. Let PATH = ((h
1
, l
1
), (h
2
, l
2
), …, (h
k
, l

k
)). For each i = 1 k-1, assign ST_temp[h
i
, t] = 1 and
assign RT_temp[h
i+1
, t] = 1 for every time slot t in the list l
i
. Assign ST_temp[h
k
, t] = 1 and
assign RT_temp[x, t] = 1 for every time slot t in the list l
k
.
iii. Recall l
i
' (the slots for x to send to y). Let ST_temp[x, t] = 1 and RT_temp[y, t] = 1 for
every time slot t in the list l
i
'.
These temporary tables, ST_temp and RT_temp, are obtained from ST, RT, PATH, and NH. This
is because we are in the probing stage, but ST and RT only contain slot status already
confirmed. The information in PATH and NH has to be introduced into these temporary tables.

A3. Let NH_temp=
φ
(i.e., an empty list).
for each 1-hop neighbor z of y do
L= select_slot(y, z, b, ST_temp, RT_temp)
if L ≠

φ
then
NH_temp = NH_temp | (z, L)
end if
end for

The above step calls for a procedure select_slot(), which will return, if possible, b available
slots that can be used by y to send to z (the details will be shown later). If the above loop can
find at least one host to extend the current path, the QREQ will be rebroadcast, as shown
below.
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193
A4. if NH_temp ≠
φ
then
broadcast QREQ(S, D, id, b, y, PATH_temp, NH_temp)
end if

The source host S will initiate the QREQ. It can be regarded as a special case of intermediate
hosts, and can perform similarly to the above steps by replacing host y with S. We only
summarize the modifications required for S. First, S has not PATH and NH. So in S1, the
checking of NH is unnecessary. We can simply set PATH_temp =
φ
. Also, step A2 can be
simplified to only executing step i. The other steps remain the same.
When the destination D receives packet QREQ(S, D, id, b, x, PATH, NH), a satisfactory path
has been formed. D can accept the first QREQ received, or choose based on other policy.
Then following steps will be executed.

B1. Let (h
i
'

, l
i
') be the entry in NH such that h
i
' = D.
B2. PATH_temp = PATH | (x, l
i
').
B3. Send QREP(S, D, id, PATH_temp) to S.

Note that the QREP packet will travel in the reverse direction of PATH through unicast.
Each intermediate host should relay this packet. In addition, proper sending and receiving
activities should be recorded in their sending and receiving tables. Specifically, let the whole
path be PATH = ((h
1
, l
1
), (h
2
, l
2
), …, (h
k
, l
k
)). For each intermediate host x = h

i
, the following
steps should be conducted.

C1. for j = i - 2 to i + 2 do
Let ST
x
[h
j
, t]=1 for each time slot t in l
j
.
end for

C2. for j = i – 2 to i + 2 do
Let RT
x
[h
j
, t]=1 for each time slot t in l
j-1
.
end for
3.4 Time slot selection
The procedure select_slot(y, z, b, ST_temp, RT_temp) is for host y to choose b free time slots to
send to z. It mainly relies on Lemma 1 to do the selection. Specifically, for each time slot i,
1 / i / s, we check the following conditions D1, D2, and D3. If all conditions hold, slot i is a
free slot that can be used by y to send to z.

D1. (ST_temp[y, i]=0) ∧ (RT_temp[y, i]=0) ∧ (ST_temp[z, i]=0) ∧ (RT_temp[z, i]=0).

D2. ∀w : (H
y
[y, w] = 1) ⇒ RT_temp[w, i]=0.
D3. ∀w : (H
y
[z, w] = 1) ⇒ ST_temp[w, i]=0.

To respond the procedure call in A3, if there are at least b time slots satisfying the above
conditions, we should return a list of b free slots to the caller; otherwise, an empty list
φ

should be returned. When there are more than b time slots available, we can further choose
slots based on some priority. The basic idea is to increase channel reuse (which is generally
favorable in almost all kinds of wireless communications). Those slots which have
the exposed-terminal problem can be chosen with higher priority. To reflect this, we can
give a legal time slot i a higher priority such that ST_temp[w, i]=1 for some neighbor w of x.
Mobile Ad-Hoc Networks: Protocol Design

194

Fig. 6. An example of QREQ propagation in our protocal.
3.5 Example
Following the example in Fig. 5, we show in Fig. 6 how B searches for a route of bandwidth
2 slots to G. Since B is the source, the ST_temp and RT_temp are equal to ST
B
and RT
B
,
respectively. Each of hosts A, C, and F can serve as the next hop by using slots {7, 8}, {9, 10},
and {7, 8}, respectively, as reflected in the packet content. We also show F's ST_temp and

RT_temp when searching for the next host. Hosts that can serve as the next hop of F are A,
C, and G. The QREQ packets sent by other hosts are not shown for clarity. Finally, when G
receives F's QREQ, it may reply a QREP(B, G, 1, (B, {7, 8}), (F, {9, 10})) to B.
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4. Experimental results
We have developed a simulator to evaluate the performance of the proposed bandwidth
reservation scheme. A MANET in a 1000m × 1000m area with 20 ~ 70 mobile hosts was
simulated. Each mobile host had the same transmission range of 300 meters. Hosts might
roam around continuously for 5 seconds, and then have a pose time from 0 ~ 8 seconds. The
roaming speed is 0 ~ 20 m/s, with a roaming direction which was randomly chosen in every
second. A data transmission rate of 11 Mbit/s was used. Each time frame had 16 ~ 32 time
slots, with 5 ms for each time slot. Traffic was generated from randomly chosen source-
destination pairs with bandwidth requirement of 1, 2, or 4 slots (denoted as QoS1, QoS2, and
QoS4, respectively). New calls arrived with an exponential distribution of mean rate
1/12000 ~ 1/500 per ms. Each call had duration of 180 sec. Since our goal was to observe
multi-hop communication, we impose a condition that each source-destination pair must be
distanced by at least two hops. The total simulation time was 1000 sec.
We make observations from several aspects.
A) Network throughput: When calculating throughput, we only count packets that
successfully arrive at their destinations. In Fig. 7, we show the network throughput under
various loads, where load is defined to be the bandwidth requirement (which are 1, 2, and 4
for QoS1, QoS2, and QoS4, respectively) times the corresponding call arrival rate. Among
the simulated ranges, the throughputs all increase linearly with respect to loads for all QoS
types. This indicates that QoS routing can be supported quite well by MANET based on our
protocol. As comparing different bandwidth requirements, QoS4 performs slightly worse
than QoS1 and QoS2. The reason will be elaborated below.
To understand the above scenarios, we further investigate the call success rate (the
probability to accept a new call) under the same inputs. The results are in Fig. 8 .When the

traffic load increases, the success rates decrease for all QoS types. The success rate of QoS1 is
the largest, which is followed by QoS2, and then QoS4. This is reasonable because larger
bandwidth requirements are more difficult to satisfy.
Next, we investigate the average number of hops for all source-destination pairs under
different bandwidth requirements. The result is in Fig. 9. We see that QoS4 routes are the
shortest in all ranges. One interesting thing is that when the traffic load is higher than
1/1000, the lengths of QoS1 routes will start to increase, while on the contrary those of QoS4
routes will drop significantly. The reason is that it is less likely to find satisfactory, but long
QoS4 routes under heavy load. But for QoS1 routes, the chances are actually higher. This is
why QoS1 gives the best network throughput.
B) Effect of host density: In this experiment, we vary the total number of hosts. Since the
physical area is fixed, this actually reflects the host density (or crowdedness of the
environment). The result is in Fig. 10. First, we observe that the network throughput will
improve as the network is denser under all QoS types. This is perhaps due to richer choices
of routing paths. Second, there will be larger performance gaps between low QoS routes
(such as 1 and 2) and high QoS routes (such as 4). So higher host density is more beneficial
to low-bandwidth routes.
C) Effect of host mobility: In Fig. 11, we show the throughput under various host mobility. We
see that throughput is very sensitive to mobility in all QoS types. In our simulation,
whenever a route is broken, an error message will be sent to the source host. Before the
source host knows this fact, all packets already sent will still consume time slots without
contributing to the real throughput. Furthermore, before a new route is discovered, some
time slots will be idle. This is why we see significant drop on throughput as mobility
increases, which also indicates a challenging problem deserving further research.
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D) Effect of frame length: In Fig. 12, we show the network throughput when a time frame has
16, 24, and 32 time slots. Longer frame length will be more beneficial to requests with higher
QoS requirements. This is reasonable because requests with larger QoS requirements get

rejected with higher probability as the frame length is shorter.

Fig. 7. Network throughput vs. traffic load (= QoS requirement times call arrival rate),
where number of hosts=30, number of time slots=16, pose time=0, and mobility=4m/s.

Fig. 8. Call success rate vs. traffic load, where number of hosts=30, number of time slots=16,
pose time=0, and mobility=4m/s.
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Fig. 9. The average route length v.s. traffic load, where number of hosts=30, number of time
slots=16, pose time=0, and mobility=4m/s.



Fig. 10. Network throughput v.s. host density, where traffic load=1/500, number of time
slots=16, pose time=0, and mobility=4m/s.
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Fig. 11. Network throughput v.s. mobility, where number of hosts=30, number of time
slots=16, pose time=0, and traffic load=1/500.

Fig. 12. Network throughput v.s. frame length, where number of hosts=30, pose time=0,
mobility=4m/s, and traffic load=1/1000.
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199

Fig. 13. Network throughput v.s. pose time, where number of hosts=30, number of time
slots=16, mobility=8m/s, and traffic load=1/1000.
E) Effect of pose time: Recall that we adopt a roaming model that a host will continue move
for 5 seconds, and then pose for 0 to 8 seconds. In Fig. 13, we show the network throughput
under various pose times. Longer pose time is beneficial for all types of QoS routes, which is
reasonable because the probability of route broken will drop.
5. Conclusions
In this paper, we have proposed a TDMA-based bandwidth reservation protocol for QoS
routing in a MANET. Most existing MANET routing protocols do not guarantee bandwidth
when searching for routes. Few works have considered the same QoS routing problem, but
are under a stronger multi-antenna model or a less stronger CDMA-over-TDMA channel
model. Our protocol assumes a simpler (and perhaps more practical) TDMA-based channel
model. One single common channel is assumed to be shared by all hosts in the MANET.
Hence the result may be applied immediately to current wireless LAN cards. One
interesting point is that our protocol can take into account the difficult hidden-terminal and
exposed-terminal problems when establishing a route. So more accurate route bandwidth
can be calculated and the precious wireless bandwidth can be better utilized. We are
currently trying to further optimize the bandwidth utilization from a global view.
6. References
Haas, Z. J. & Pearlman, M. R. (1998). The Zone Routing Protocol (ZRP) for Ad-Hoc
Networks, Internet draft, August, 1998.
Johnson, D. B.; Maltz, D. A.; Hu, Y C. & Jetcheva, J. G. (2001). The Dynamic Source Routing
Protocol for Mobile Ad Hoc Networks, Internet draft, November, 2001.

Liao, W H.; Tseng, Y C. & Sheu, J P. (2001). GRID: A Fully Location-Aware Routing
Protocol for Mobile Ad Hoc Networks, Telecommunication Systems, Vol. 18, No. 1-3,
pp. 37-60, 2001.
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Perkins, C. & Bhagwat, P. (1994). Highly Dynamic Destination-Sequenced Distance-Vector
(DSDV) Routing for Mobile Computers, ACM SIGCOMM Symposium on
Communications, Architectures and Protocols, 1994.
Perkins, C.; Royer, E. M. & Das, S. R. (2002). Ad Hoc On Demand Distance Vector (AODV)
Routing, Internet draft, January, 2002.
Royer, E. M. & Toh, C K. (1999). A Review of Current Routing Protocols for Ad Hoc Mobile
Wireless Networks, IEEE Personal Communications, Vol. 6, No. 2, pp. 46-55, April,
1999.
Wu, J. & Li, H. (2001). A Dominating-Set-Based Routing Scheme in Ad Hoc Wireless
Networks, Telecommunication Systems, Vol. 18, No. 1, pp. 13-36, 2001.
Chen, S. & Nahrstedt, K. (1999). Distributed Quality-of-Service Routing in Ad Hoc
Networks, IEEE Journal on Selected Areas in Communications, Vol. 17, No. 8, pp. 1488-
1505, August, 1999.
Liao, W H.; Tseng, Y C.; Wang, S L. & Sheu, J P. (2002). A Multi-Path QoS Routing
Protocol in a Wireless Mobile Ad Hoc Network, Telecommunication Systems, Vol. 19,
No. 3, pp. 329-347, 2002.
Lin, C R. (2001). On-Demand QoS Routing in Multihop Mobile Networks, IEEE INFOCOM,
2001.
Lin, C R. & Liu, J.–S. (1999). QoS Routing in Ad Hoc Wireless Networks, IEEE Journal on
Selected Areas in Communications, Vol. 17, No. 8, pp. 1426-1438, August, 1999.
Stojmenovic, I.; Russell, M. & Vukojevic, B. (2000). Depth First Search and Location Based
Localized Routing and QoS Routing in Wireless Networks, International Conference
on Parallel Processing, 2000.
Chalmers, D. & Sloman, M. (1999). A Survey of Quality of Service in Mobile Computing

Environments, IEEE Communications Surveys, Vol. 2, No. 2, pp. 2-10, April, 1999.
Wang, Z. & Crowcroft, J. (1996). Quality-of-Service Routing for Supporting Multimedia
Applications, IEEE Journal on Selected Areas in Communications, Vol. 14, No. 7, pp.
1228-1234, September,1996.
Sobrinho, J. L. & Krishnakumar A. S. (1999). Quality-of-Service in Ad Hoc Carrier Sense
Multiple Access Wireless Networks, IEEE Journal on Selected Areas in
Communications, Vol. 17, No. 8, pp. 1353-1368, August, 1999.
Ni, S Y.; Tseng, Y C.; Chen, Y S. & Sheu, J P. (1999). The Broadcast Storm Problem in a
Mobile Ad Hoc Network, ACM/IEEE International Conference on Mobile Computing
and Networking (MobiCom'99), 1999.
Bertossi, A. & Bonuccelli, M. (1995). Code Assignment for Hidden Terminal Interference
Avoidance in Multihop Radio Networks, IEEE/ACM Transation on Networks, Vol. 3,
No. 4, pp. 441-449, August, 1995.
Garcia-Luna-Aceves, J. J. & Raju, J. (1997). Distributed Assignment of Codes for Multihop
Packet-Radio Networks, IEEE MILCOM '97, 1997.
Ju, J H. & Li, V. O. K. (1999). TDMA Scheduling Dedsign of Multihop Packet Radio
Networks Based on Latin Squares, IEEE Journal on Selected Areas in Communications,
Vol. 17, No. 8, pp. 1345-1352, August, 1999.
IEEE Std 802.11–1997：Wireless LAN Medium Access Control (MAC) and Physical Layer
(PHY) Specifications, Institute of Electrical and Electronics Engineers, Inc., 1997.
Marina, M. K. & Das, S. R. (2001). Performance of Route Caching Strategies in Dynamic
Source Routing, IEEE Wireless Networking and Mobile Computing (WNMC)
, 2001.
11
Link Quality Aware Robust Routing for
Mobile Multihop Ad Hoc Networks
Sangman Moh, Moonsoo Kang, and Ilyong Chung
Chosun University
South Korea
1. Introduction

A mobile ad hoc network (MANET) (Perkins, 2001; Siva Ram Murthy & Manoj, 2004; IETF,
2009) is a collection of mobile nodes without any fixed infrastructure or any form of
centralized administration. In other words, it is a temporary network of mobile nodes
without existing communication infrastructure such as access points or base stations. In
such a network, each node plays a router for multihop routing as well. MANETs can be
effectively applied to military battlefields, emergency disaster relief, and other application-
specific areas including wireless sensor networks and vehicular ad hoc networks.
In mobile ad hoc networks, interference and noise are two major obstacles in realizing their
full potential capability in delivering signals. In wireless links, the signal propagation is
affected by path loss, shadowing and multi-path fading, and dynamic interferences generate
additional noise from time to time degrading link quality. In this study, as an effective and
practical metric of link quality, signal-to-interference plus noise ratio (SINR) is used because it
takes interference and noise as well as signal strength into account. Note that SINR is
measurable with no additional support at the receiver (Krco & Dupcinov, 2003; Zhao et al.,
2005). Furthermore, as nodes are fast moving, poor links are unpredictably increased.
Actually, it is shown that the communication quality of mobile ad hoc networks is low and
users can experience strong fluctuation in link quality in practical operation environments
(Gaertner & Cahill, 2004). In particular, sending real-time multimedia over mobile ad hoc
networks is more challenging because it is very sensitive for packet loss and the networks
are error prone due to node mobility and weak links (Karlsson et al., 2005). Accordingly, it is
very important to include as many high-quality links as possible in a routing path. Also, the
dynamic behavior of link quality should be taken into consideration in protocol design.
In the IEEE 802.11 MAC (IEEE, 1999), broadcast packets are transmitted at the base data rate of 1
Mbps. It is mainly due to the potential demand that a broadcast packet should cover as large
area as possible in the wireless LAN environment. Note here that, given radio hardware and
transmit power, the transmission range is affected by the transmit rate. In mobile ad hoc
networks, the route request (RREQ) packet in routing protocols is a broadcast packet. Therefore,
if a distant node receiving an RREQ rebroadcasts the RREQ, a long weak link with low data
rate can be included in the discovered route. Intuitively, this helps the routing protocols to find
out the minimum hop-count route from source to destination. Note here that the minimum hop-

count route is a routing path with the minimum number of hops from source to destination
and sometimes called the shortest path in the viewpoint of graph algorithm. However, such
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202
long links are relatively weak and unreliable and increase the possibility that they are broken.
That is, the minimum hop-count route does not mean the best route as measured in (De Couto
et. al., 2002; De Couto et. al., 2003). Furthermore, as an effort, SINR-based design of optimized
link state routing was introduced for scenarios where VoIP (Voice over IP) traffic is carried
over a static multihop networks (Kortebi et al., 2007). In our study, in order to find out a robust
route for high delivery efficiency and network performance in MANETs, strong links are
selected by examining link quality (or SINR) instead of the number of hops.
This paper proposes a link quality aware routing protocol for MANETs resulting in robust
delivery and high throughput by finding out a robust route with strong links. During route
discovery, the strong links are effectively exploited by forwarding the RREQ packet with the
highest SINR among the multiple RREQ packets received. In case there are RREQ packets
within
δ
dB (
δ
= 1 in this study) from the highest SINR, the first-arrived one among them is
chosen to cope with the dynamic behavior of SINR. Any node that has received an RREQ
receives successive RREQ packets until the predetermined RREQ waiting time expires;
afterwards, RREQ packets for the route discovery are ignored. Compared to the
conventional protocols such as AODV, in which only the first-arrived RREQ is forwarded
and the others are ignored, the proposed scheme may not have the minimum hop-count
route but the one with more number of hops (links). However, the found route is a reliable
path with high data rate because it consists of strong links, resulting in high performance as
well as robust routing. For performance study, in this paper, the link quality aware AODV
(LA-AODV) is implemented in ns-2 (NS-2, 2008; CMU, 2008). For practical system

simulation, we introduce a realistic reception model that takes BER and frame error rate (FER)
into account instead of the deterministic reception model in the ns-2 network simulator.
Note that the deterministic reception model in ns-2 is based on three fixed thresholds such
as carrier sense, receive and capture thresholds (NS-2, 2008; CMU, 2008). According to our
performance study, it is shown that packet delivery ratio is improved by up to 70% and per-
route goodput is dramatically increased by a factor of up to 12. It is also shown that the
acceptable value of the RREQ waiting time (T
w
) is 1 msec in the simulated environment,
which is enough to achieve fairly good performance.
The rest of the paper is organized as follows: As preliminaries for this study, the basic
AODV routing protocol and the rate adaptation mechanisms are summarized in the
following section. Section 3 presents the proposed link quality aware routing; i.e., the RREQ
forwarding algorithm and the robust routing protocol LA-AODV are described, and then
the impact of link quality is analyzed. Performance study including reception model,
simulation environment, and evaluation results is discussed in Section 4. Finally,
conclusions are given in Section 5.
2. Preliminaries
In this section, the ad hoc on-demand distance vector (AODV) routing protocol (Perkins et
al., 2003; Belding-Royer & Perkins, 2003), which is a representative routing protocol for
MANETs, is briefly overviewed. Then, the rate adaptation mechanisms to exploit as high
transmission rate as possible are summarized.
2.1 AODV routing
The AODV routing protocol (Perkins et al., 2003; Belding-Royer & Perkins, 2003) is an on-
demand routing protocol based on the DSDV protocol (Perkins & Watson, 1994). The main
Link Quality Aware Robust Routing for Mobile Multihop Ad Hoc Networks

203
characteristics of AODV are to use the periodic beaconing for neighbor sensing and
sequence numbering procedure of DSDV and a flooding-based route discovery procedure.

In AODV, route discovery works as follows: Whenever a source needs a route to a
destination, it first checks whether it has a route in its route cache (routing table). If it does
not have a route, it initiates a route discovery by flooding a route request (RREQ) packet for
the destination in the network and, then, waits for a route reply (RREP) packet. When an
intermediate node receives the first copy of an RREQ, it sets up a reverse path to the source
using the previous hop of RREQ as the next hop on the reverse path. In addition, if there is a
valid route available for the destination, it unicasts an RREP back to the source via the
reverse path; otherwise, it rebroadcasts RREQ. Duplicate copies of RREQ are immediately
discarded upon reception at every node. The destination on receiving the first copy of an
RREQ forms a reverse path in the same way as intermediate nodes, and it also unicasts an
RREP back to the source along the reverse path. As RREP proceeds towards the source, it
establishes a forward path to the destination at each hop. Note here that the destination
generates RREPs only when its destination sequence number is grater than or equal to the
destination sequence number of the RREQ received.
Route maintenance is done by means of route error (RERR) packets. When an intermediate
node detects a link failure (e.g., via a link-layer feedback), it generates an RERR. RERR
propagates towards all sources having a route via the failed link, and erases all broken
routes on the way. A source upon receiving RERR initiates a new route discovery if it still
needs the route. Apart from this route maintenance mechanism, AODV also has a timer-
based mechanism to purge stale routes.
2.2 Rate adaptation
As a wireless channel is time-varying and location-dependent due to path loss, shadowing
and small-scale fading as well as interference, rate adaptation is a powerful way to
overcome channel variations (Zhai et al., 2006). For example, IEEE 802.11b standard
incorporates physical-layer multi-rate capability, the feasible data rate set of which is 1, 2,
5.5 and 11 Mbps. However, the IEEE 802.11 standards do not specify how to choose the data
rate based on varying channel conditions and thus some schemes to select the rate
adaptively have been proposed.
The auto rate fallback (ARF) protocol (Kamerman & Monteban, 1997) is the first commercial
MAC that utilizes rate adaptation. Each sender attempts to use higher transmission rate

after consecutive transmission successes at a given rate and revert to a lower rate after 1 or 2
consecutive failures. A timer is reset and started each time the rate is changed. When either
the timer expires or the number of successfully received acknowledgements reaches the
threshold of 10, the rate is increased. The first transmission after the rate increase must
succeed or the rate is immediately decreased. When two consecutive transmissions fail in a
row, the current rate is decreased. However, if the channel conditions change very quickly
due to fast multipath fading, ARF cannot adapt effectively. The adaptive ARF (AARF)
protocol (Lacage et al., 2004) continuously changes the threshold at runtime to better reflect
the channel conditions. When the transmission of the probing frame fails, the data rate is
switched back immediately and the threshold is doubled. The threshold is reset to its initial
value of 10 when the rate is decreased due to two consecutive failed transmissions.
However, AARF still cannot take the frame loss due to collisions over the wireless link into
consideration. The loss-differentiating ARF (LD-ARF) protocol (Pang, 2005) effectively
adapts to collision losses as well as link error losses. The data rate is reduced only when a
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204
loss of data frame is caused by link errors, not by collisions. Note that it is assumed that if
the CTS frame is not received, most likely a collision has occurred because RTS and CTS are
short and usually transmitted at a base rate of 1 Mbps.
In the receiver based auto rate (RBAR) protocol (Holland et al., 2001), each receiver measures
the channel quality (SINR) of the received RTS frame and, then, selects the transmission rate to
be used by the upcoming CTS, data, and acknowledgement frames according to the highest
achievable value based on the SINR. The rate to use is then sent back to the sender in the CTS
frame. Note that the sender chooses a data rate for RTS based on some heuristic or sets it at a
base rate of 1 Mbps. To allow all the nodes within the transmission range to correctly update
their network allocation vector (NAV), the RTS, CTS, and data frames have to contain
information on the size and rate of the data transmission. If a node that heard the RTS frame
hears the data frame, it should recalculate the reservation duration and update its NAV
correctly. Since the channel quality is evaluated just before data packet transmission, RBAR

yields significant throughput gain compared to ARF. In RBAR, only one packet is allowed to
transmit each time, which is not efficient especially when the channel condition is good for a
long time. To better exploit the duration of high-quality channel condition, the opportunistic
auto rate (OSR) protocol (Sadeghi et al., 2002) opportunistically sends multiple back-to-back
data packets whenever the channel quality is good. It achieves significant throughput gains
compared to RBAR. In the opportunistic packet scheduling and auto rate (OSAR) protocol
(Wang et al., 2004), a sender multicasts RTS to a group of candidate receivers simultaneously
and, then, a receiver with channel quality better than a certain level replies CTS. If there are
more than one candidate receivers with good channel condition, a coordinating rule is applied
in a distributed fashion to avoid collision.
As in (Zhao et al., 2005), we implement a SINR-based rate adaptation scheme in ns-2 (NS-2,
2008; CMU, 2008). The scheme is based on RBAR (Holland et al., 2001), and the data rate of
RTS is set at a base rate of 1 Mbps to safely cope with dynamically changing link quality in
MANETs. Such a rate adaptation is effectively utilized in our link quality aware routing
protocol which will be presented in Section 3.
3. Link quality aware routing
The proposed link quality aware routing protocol, which finds out a robust route with
strong links during route discovery, is presented and discussed in this section. The key idea
of finding out a robust route is to forward the RREQ packet with the highest SINR among
multiple RREQ packets received. In case there are multiple RREQ packets within
δ
dB from
the highest SINR, the first-arrived one among them is chosen to cope with the dynamic
behavior of SINR. The RREQ forwarding algorithm is presented first and then the link
quality aware AODV (LA-AODV) is followed. The route reliability and throughput are
analyzed in terms of link quality or SINR.
3.1 RREQ forwarding algorithm
In the conventional routing protocols such as AODV, the intermediate nodes forward only
the first-arrived RREQ during route discovery in order to find out the minimum hop-count
route even though the route does not mean the best route as measured in (De Couto et. al.,

2002; De Couto et. al., 2003). This results in a fragile route with long, weak and unreliable
links. In this subsection, a new RREQ forwarding algorithm is presented to find out a robust
and high-performance route.
Link Quality Aware Robust Routing for Mobile Multihop Ad Hoc Networks

205
Max range of node s
sd
a
b
RREQ
(1 Mbps)
RREQ
(1 Mbps)
RREQ
(1 Mbps)
RREQ
(1 Mbps)
(ignored)

Max range of node s
sd
a
b
DATA
(2 Mbps)
DATA
(1 Mbps)

(a) Minimum hop-count RREQ forwarding (b) Low-rate delivery after route discovery

sd
a
b
DATA
(1 Mbps)
(failed)
Node b moves.

Noise and interference are increased.
sd
a
b
DATA
(2 Mbps)
DATA
(1 Mbps)
(failed)

(c) Delivery failure after node b moves (d) Delivery failure when noise increases
Fig. 1. Minimum hop-count RREQ forwarding and its possible problems.
Fig. 1 shows the minimum hop-count RREQ forwarding and its possible problems in the
conventional routing protocols such as AODV. Since the first-arrived RREQ is forwarded
and the others are ignored, node b receives the RREQ packet directly come from s and
forwards it, resulting in a routing path <s, b, d> with two hops as shown in Fig. 1(a). The
RREQ packet come from node a is ignored at node b because it arrives later. Once a route is
discovered, subsequent data delivery is done through the route as shown in Fig. 1(b), but
the throughput is 1 Mbps because the weak link <s, b> in the route limits the data rate to the
base rate of 1 Mbps. On the other hand, if node b moves and exists out of the maximum
range of node s as shown in Fig. 1(c), it does not receive data packets from node s any more,

resulting in delivery failure and initiating a new route discovery. The effect of mobility
changes the received signal power, which is exponentially decreased as the communication
distance increases, and thus affects SINR. Fig. 1(d) shows another example of delivery
failure. If interference and noise on the link <s, b> are increased due to unstable and
dynamic network environment, SINR of the packet transmitted from node s becomes less
than the threshold (e.g., 10 dB) and, thus, node b does not receive the packet successfully
even though it does not move. The interference and noise are influenced by unstable and
dynamic network environment and unexpectedly changes from time to time, and thus
affects SINR. As explained earlier, the weak point of the conventional routing protocols,
which is got over in this paper, is the RREQ forwarding algorithm in which the intermediate
nodes forward the first-arrived RREQ to find out the minimum hop-count route even
though the route does not mean the best route as measured in (De Couto et. al., 2002; De
Couto et. al., 2003).
In the proposed LA-AODV protocol, the route discovery and maintenance are necessary as
in the basic AODV. The main difference between AODV and LA-AODV is RREQ
forwarding during route discovery. Fig. 2 represents the proposed RREQ forwarding
algorithm. The new RREQ forwarding algorithm helps find out a reliable route with strong
links. When a node has a packet to send, it needs a route to the destination. If it has no route
in its route cache or routing table, it issues route discovery by broadcasting an RREQ packet

Mobile Ad-Hoc Networks: Protocol Design

206
// RREQ forwarding procedure at every node
/* This algorithm is carried out during route discovery at every node that receives an RREQ packet:
i.e., if a node receives an RREQ packet, this routine is immediately called and run by the node.
*/
1: S = {R
1
}; // keep track of received RREQs (including link quality or SINR).

2: // subscript i in set element R
i
represents the order of receipt
3: set the timer as T
w
; // initialize the timer to
4: while the timer does not reach 0, do { // repeat lines 4~7 until the timer reaches 0
5: // receives successive RREQs until the predetermined RREQ waiting time expires
6: if any successive RREQ arrives, append it into S;
7: }
8: k = |S|; // number of elements in S
9: if k = 1, forward R
1
;
10: else{ // if there are two or more RREQs received
11: sort S in decreasing (non-increasing) order of SINR;
12: if there are one or more RREQs within
δ
dB from the highest SINR in S { //
δ
=1 in this study
13: // for coping with the dynamic behavior of SINR
14: select the first-arrived one among them;
15: forward the selected one;
16: }
17: else forward the RREQ with the highest SINR;
18: }
19: return; // afterwards, RREQ packets are ignored
T
w

Fig. 2. Proposed RREQ forwarding algorithm.
for the destination. Intermediate nodes forward the RREQ packet with the highest SINR
among multiple RREQ packets received for the predetermined RREQ waiting time (T
w
) after
the first RREQ is received. In case there are multiple RREQ packets within
δ
dB (
δ
= 1 in this
study) from the highest SINR, the first-arrived one among them is chosen to cope with the
dynamic behavior of SINR. The other RREQ packets arrived later are ignored if any.
Similarly, the destination takes the RREQ packet with the highest SINR for route reply.
3.2 Link quality aware end-to-end routing
Based on the RREQ forwarding algorithm, the link quality aware AODV (LA-AODV) routing
protocol is presented and discussed in this subsection. Since the RREQ forwarding
algorithm finds out a robust route with strong links, the proposed LA-AODV results in
robust delivery and high performance. Note that the route discovery operation of LA-
AODV differs from that of AODV but there is no noticeable difference in the route
maintenance. Accordingly, LA-AODV can be easily implemented.
Fig. 3 shows the proposed link quality aware RREQ forwarding and its resulting effects for
the same example as in Fig. 1. During route discovery, node b forwards the RREQ packet
come from node a rather than that come from node s as shown in Fig. 3(a) because the
former has the better link quality (i.e., higher SINR) than the latter. Notice that, in the

Link Quality Aware Robust Routing for Mobile Multihop Ad Hoc Networks

207
Max range of node s

sd
a
b
RREQ
(1 Mbps)
RREQ
(1 Mbps)
RREQ
(1 Mbps)
RREQ
(1 Mbps)
(ignored)

Max range of node s
sd
a
b
DATA
(2 Mbps)
DATA
(2 Mbps)
DATA
(2 Mbps)

(a) Link quality aware RREQ forwarding (b) High-rate delivery after route discovery

sd
a
b
DATA

(2 Mbps)
DATA
(2Mbps)
DATA
(2 Mbps)
Node bmo ve s.

sd
a
b
DATA
(2 Mbps)
DATA
(2 Mbps)
DATA
(1 Mbps)
Noise and interference are increased.

(c) Data delivery after node b moves (d) Data delivery when noise increases
Fig. 3. Link quality aware RREQ forwarding and its resulting effects for the same example as
in Fig. 1.
proposed RREQ forwarding algorithm, the intermediate nodes forward the RREQ packet with
the highest SINR among multiple RREQ packets received for the predetermined RREQ
waiting time after the first RREQ is received. In case there are RREQ packets within
δ
dB
(
δ
= 1 in this study) from the highest SINR, the first-arrived one among them is chosen to
cope with the dynamic behavior of SINR. Fig. 3(b) shows data delivery after route

discovery, in which data is delivered at 2 Mbps along with 3 hops. That is, the throughput of
the route is 2 Mbps, which is double of 1 Mbps in the conventional protocols as shown in
Fig. 1(b), because strong links <s, a> and <a, b> instead of the weak link <s, b> are exploited
in the proposed RREQ forwarding algorithm. Even when node b moves as in Fig. 3(c), the
data delivery is successful with the same throughput of 2 Mbps without performance
degradation. If node b moves further away from node a or node d, the throughput might be
reduced but still the route may be alive. Fig. 3(d) shows another example of data delivery in
case of unstable and dynamic network environment. If interference and noise are increased
resulting in link quality fluctuation, SINR of the packet transmitted from node a is reduced
but the link <a, b> is strong enough to receive the packet without error and, thus, node b can
still receive the packet successfully at lower data rate (e.g., 1 Mbps). Note here that the
transmission data rate is decreased (i.e., from 2 Mbps to 1 Mbps in the figure) because SINR
is reduced due to the increased interference and noise on the link <a, b>. Conclusively, the
proposed approach achieves high throughput as well as robust delivery by exploiting strong
links during route discovery.
In the conventional protocols such as AODV, only the first-arrived RREQ is forwarded and
the others are ignored. The rationale for such design is that it finds out the shortest path (i.e.,
the minimum hop-count route) because the first arrival means the smaller number of hops
from the source. That is, to discover the minimum hop-count route is the primary goal of the
conventional protocols as in the most wired networks. As described in Introduction,
however, the minimum hop-count route does not mean the best route as measured in (De
Couto et. al., 2002; De Couto et. al., 2003). On the other hand, the proposed approach might
Mobile Ad-Hoc Networks: Protocol Design

208
not have the minimum hop-count route but the one with more number of hops (links).
However, the found route in the proposed LA-AODV is a reliable path with high data rate
because it consists of strong links, resulting in high throughput as well as robust routing.
Obviously, a routing path with strong links is more reliable and has higher quality
compared to that with weak links. It significantly extends the lifetime of a routing path,

reducing route discovery frequency. Moreover, a high-quality link transmits packets at high
data rate. Therefore, the proposed LA-AODV results in higher packet delivery ratio and
higher throughput as well as more robust routing compared to AODV. In the proposed
protocols, the RREQ waiting time is a critical design factor because it directly determines the
amount of overhead affecting the route discovery time. Even though the overhead of the
RREQ waiting time is a minor factor compared to the positive effects of finding out a robust
routing path, it should be optimized to eliminate unnecessary operations. In Section 4, some
different RREQ waiting time is applied to performance simulation in order to investigate the
performance impact of the RREQ waiting time.
Note that LA-AODV is the same as AODV except for that the new RREQ forwarding
algorithm presented earlier is used instead of the first-arrived RREQ forwarding used in
AODV and DSR during route discovery. Therefore, LA-AODV protocol can be easily
implemented by redesigning only the RREQ forwarding module in AODV and tuning some
related modules appropriately. Note that the proposed RREQ forwarding algorithm is
feasible since SINR is measurable with no additional support at the receiver (Krco &
Dupcinov, 2003; Zhao et al., 2005). In this paper, the link quality-aware AODV (LA-AODV)
routing protocol, which is the modified version of AODV (Perkins et al., 2003; Belding-
Royer & Perkins, 2003), is implemented in ns-2 (NS-2, 2008; CMU, 2008) and its performance
is evaluated and compared with the conventional routing protocols of AODV in Section 4.
3.3 Analysis on impact of link quality
For a multi-hop route, the impact of link quality is analyzed in this subsection. The route
reliability and throughput are discussed in terms of link quality or SINR. In general, the link
quality can be represented by signal strength, signal-to-noise ratio (SNR), or SINR. In our
study, SINR is used as the metric of link quality because it takes all the signal strength,
interference and noise into account. Note that SINR directly affects bit error rate (BER)
which determines the probability that a packet is successfully transferred. Given a
modulation method, BER is inversely proportional to SINR. How to calculate SINR and a
typical example of SINR-BER curve will be given in Section 4.1.
Given a k-hop route R from source to destination in a mobile ad hoc network, the probability
P

R
that a packet is successfully delivered along with R can be represented by

1
k
Ri
i
Pp
=
=
∏
(1)
where p
i
is the probability that a packet is successfully transferred via the i-th link in R. Note
here that the data rate is fixed and the same for all the k links in R. When p
i
is relatively low,
P
R
is quickly decreased as the number of hops in a route increases. Therefore, p
i
needs to be
as high as possible to provide scalability. In other words, a route with strong links is highly
required to obtain a reliable route of high P
R
. Note that P
R
and p
i

are reliability of R and the i-
th link in R, respectively. P
R
is often called packet delivery ratio.
Link Quality Aware Robust Routing for Mobile Multihop Ad Hoc Networks

209
On the other hand, the end-to-end throughput
λ
R
of a k-hop route R is calculated by using
geometric mean. Note that geometric mean is used if the product of the observations is a
quantity of interest. Therefore,
λ
R
can be simply given by

1
1
()
k
k
Ri
i
λ
λ
=
=
∏
(2)

where
λ
i
is the throughput or data rate of the i-th link in R. Note here that the data rate (
λ
i
) is
directly correlated to the link quality (p
i
). To attain high end-to-end throughput, every link
of a route has to transmit frames at high data rate. To achieve high data rate for a link, the
link need to be as strong as possible.
In summary, the reliability and throughput can be significantly improved by exploiting
strong links during route discovery. The more strong links are taken, the better reliability
and throughput are attained. In this paper, per-route goodput is evaluated via extensive
simulation instead of throughput in the next section because goodput is more practical and
application oriented than throughput.
4. Performance evaluation
In this section, the performance of the proposed link quality aware AODV (LA-AODV) is
evaluated in comparison to the normal AODV using the ns-2 network simulator (NS-2, 2008;
CMU, 2008). Section 4.1 introduces the realistic reception model we have used in this study
and Section 4.2 explains the simulation environment including parameters. Simulation
results are discussed in Section 4.3.
4.1 Reception model
The reception model implemented in the ns-2 network simulator (NS-2, 2008; CMU, 2008) is
based on three fixed thresholds, i.e., carrier sense threshold (CSThresh), receive threshold
(RxThresh) and capture threshold (CPThresh). When a frame is received, each node in the
proximity calculates the received signal power based on radio propagation model and
compares it against CSThresh and RxThresh. If it is smaller than CSThresh, the receiver
ignores the signal. If it is in between the two thresholds, the receiver considers the medium

busy but do not attempt to decode the signal. If it is higher than RXThresh, the receiver
attempts to receive the frame. However, when the node receives another signal during
receiving the first signal, their ratio is compared against CPThresh. If one of them is much
stronger (e.g., 10 dB higher), it captures the other; otherwise, both frames fail. However, real
wireless links are characterized with random and probabilistic behavior.
Even though the abovementioned deterministic reception model is not realistic, it has been
used in most simulation studies for simple comparison. For the realistic evaluation of
wireless links with probabilistic behavior, however, it is important to simulate a realistic
reception model. Our evaluation takes bit error rate (BER) into consideration in the context of
ns-2 because BER is a function of SINR and modulation method (Pavon & Choi, 2003). In
other words, given a modulation method, BER is inversely proportional to SINR.
Here, we describe how SINR is calculated in ns-2 (NS-2, 2008; CMU, 2008). While the
receiver receives one signal, other signals may arrive at the receiver resulting in interference.
As a result, SINR of the receiving signal, γ, is calculated by
Mobile Ad-Hoc Networks: Protocol Design

210

r
i
ir
P
PN
γ
≠
=
+
∑
(3)
where P

r
is the received power (signal strength) of the signal, P
i
denotes the individual
received power of other signals received by the receiver simultaneously, and N is the
effective noise at the receiver. There are two components in the above equation – received
power and interference plus noise.
First, the received power at the receiver (P
r
) is calculated according to the radio propagation
model at the receiver in ns-2. In our study, Ricean fading model (Punnoose et al., 2000; NS-2,
2009) is used as a radio propagation model. The Ricean fading is a radio propagation
anomaly caused by partial cancellation of a radio signal by itself; i.e., the signal arrives at the
receiver by two or more different paths and at least one of the paths is changing. It occurs
when one of the paths, typically a line of sight signal, is much stronger than others. The
Ricean fading model is effectively applied to the environment that, in addition to scattering,
there is a strongly dominant signal seen at the receiver usually caused by a line of sight.
Second, noise contains the noise generated by the receiver and the one come from
environment. The effective noise level generated by the receiver can be obtained by adding
up the noise figure of a network interface card (NIC) onto the thermal noise (IEEE, 1994).
We first compute the thermal noise level within the channel bandwidth of 22 MHz in the
IEEE 802.11 standard (IEEE, 1999). This bandwidth is 73 dB above -174 dBm/Hz, or -101
dBm. Assuming a system noise figure of 6 dB as in (IEEE, 1994), the effective noise level
generated by the receiver is -95 dBm. The environment noise or channel noise is the additive
white Gaussian noise (AWGN) that is modeled as a Gaussian random variable. It is assumed
that the environment noise is fixed throughout the whole medium access of a
communication. For realistic simulation of noisy and unstable environments, the
environment noise can be varied for different medium accesses. On the other hand,
interference is the received signal power calculated as described above for other frames
received by the receiver simultaneously.

Based on the aforementioned discussions and the product specification of the Intersil
HFA3861B radio chip (Intersil, 2007a), we are able to calculate the BER as shown in Fig. 4(a),
which models the QPSK modulation with 2 Mbps. Note that the BER-E
b
/N
0
curve given in
(Intersil, 2007a) is simply converted into the BER-SINR curve since SINR = E
b
/N
0
× R/B
T
,
where E
b
is energy required per bit of information, N
0
is interference plus noise in 1 Hz of
bandwidth, R is system data rate, and B
T
is system bandwidth that is given by B
T
= R for
QPSK in the Intersil chipset (Intersil, 2007b). In an IEEE 802.11 frame, physical layer
convergence protocol (PLCP) preamble, PLCP header and payload (data) may be
transmitted at different rate with different modulation method. Hence, BER should be
calculated separately for the three parts of a frame.
Once BER is obtained, frame error rate (FER) can be calculated, which determines the
percentage that a frame is received correctly. For example, given

α
-bit preamble,
β
-bit PLCP
header and
γ
-bit payload with BER of p
a
, p
b
and p
c
, respectively, FER is obtained by 1 – (1 –
p
a
)
α
(1 – p
b
)
β
(1 – p
c
)
γ
. For comparison, Fig. 4(b) also shows the FER curve used in unmodified
ns-2. As discussed earlier in this section, if SINR is larger than CPThresh, e.g., 10 dB as in
Fig. 4(b), the frame succeeds (FER = 0.0). Otherwise, it fails (FER = 1.0). Our performance
evaluation study modifies ns-2 so that FER is not deterministically but probabilistically
determined based on SINR, making our evaluation more realistic and convincing.

Link Quality Aware Robust Routing for Mobile Multihop Ad Hoc Networks

211
1.E-09
1.E-08
1.E-07
1.E-06
1.E-05
1.E-04
1.E-03
1.E-02
1.E-01
5 6 7 8 9 10111213141516
SINR (dB)
Bit e rro r ra te
'
1.E -06
1.E -05
1.E -04
1.E -03
1.E -02
1.E -01
1.E +00
5 6 7 8 9 10111213141516
SINR (dB)
F ra m e e rro r ra te
'
Determinstic model
implemented in ns-2

(a) BER versus SINR (b) FER versus SINR
Fig. 4. BER and FER for QPSK with 2 Mbps in the Intersil HFA3861B radio chip. (The PHY
frame size for calculating FER is assumed to be 864 bits, i.e., 144-bit preamble, 48-bit PLCP
header and 84-byte payload.)
4.2 Simulation environment
In our simulation study, it is assumed that 50 mobile nodes move over a square area of 300m
× 1,500m. The propagation channel of Ricean fading model is assumed with a data rate of 2
Mbps. As mentioned in Section 2.2, the SINR-based rate adaptation scheme based on RBAR
(Holland et al., 2001) is modeled and used in ns-2 (NS-2, 2008; CMU, 2008), where the data
rate of RTS is set at a base rate of 1 Mbps to safely cope with dynamically changing link
quality in MANETs. The constant bit rate (CBR) source of 2 packets per second is assumed
with UDP-based traffic and the data payload of the packets is 512 bytes long. Mobile nodes
are assumed to move randomly according to the random waypoint model (Broch et al., 1998),
where two parameters of maximum node speed and pause time determine the mobility
pattern of the mobile nodes. Each node starts its journey from a randomly selected location
to a target location, which is also selected randomly in the simulation area, at a randomly
chosen speed (uniformly distributed between 0 and maximum speed). The maximum speed
is set as 5 m/sec throughout the simulation. When a node reaches the target location, it stays
there during the pause time and then repeats the mobility behavior.
As for performance metrics, we evaluate the followings: Packet delivery ratio is the ratio of the
number of data packets successfully delivered to the destination over the number of data
packets sent by the source. Per-route goodput is the application level throughput excluding
protocol overhead and retransmitted data packets, which is sometimes given by the inverse
of the averaged end-to-end data packet delay. Normalized control overhead is the ratio of the
total number of control packets transmitted for medium access and routing over the number
of data packets successfully delivered to the destination, where each hop-wise transmission
of a control packet is counted as one transmission.
For measuring the performance metrics, the simulation factors of the environment noise
level, the number of sessions, and the pause time are varied in a meaningful range; i.e., the
environment noise level of -90 ~ -80 dBm (i.e., -90, -88, -86, -84, -82, and -80dBm) modeled as

a Gaussian random variable with the standard deviation of 1 dB, the number of sessions
Mobile Ad-Hoc Networks: Protocol Design

212
from 2 to 18 (i.e., 2, 6, 10, 14, and 18), and the pause time of 100 ~ 900 sec (i.e., 0, 20, 50, 100,
200, 300, 600, and 900 sec) are applied. While one simulation factor is varied during a
simulation, the others are fixed as follows: the environment noise level of -84 dBm (which
represents a relatively harsh environment), the number of sessions of 4, and the pause time
of 100 sec. Note that the number of sessions is the number of connections. Source-destination
pairs are randomly selected. Each run has been executed for 900 sec of simulation time.
4.3 Simulation results and discussion
4.3.1 Packet delivery ratio.
Fig. 5 shows the packet delivery ratio for varying the environment noise and the number of
sessions. It is shown that the proposed LA-AODV outperforms the basic AODV by up to 70
% and 34% for the environment noise and the number of sessions, respectively. Note here
that LA-AODV shows almost the same performance for the two different values of RREQ
waiting time (T
w
) of 1 msec and 10 msec. The two cases with T
w
of 1 msec and 10 msec
outperform LA-AODV with T
w
of 0.1 msec. Therefore, it can be easily inferred that T
w
of 1
msec is long enough to achieve the most robust delivery in the given environment. As the
environment noise increases, PDR is decreased as expected. It is slightly decreased with the
increased number of sessions.
4.3.2 Per-route goodput.

Fig. 6 shows the per-route goodput for varying the environment noise and the number of
sessions. It is shown that the proposed LA-AODV outperforms the basic AODV by a factor
of up to 12 and 8 for the environment noise and the number of sessions, respectively. As in
Fig. 5, LA-AODV shows almost the same performance for the two different values of RREQ
waiting time (T
w
) of 1 msec and 10 msec, and the two cases with T
w
of 1 msec and 10 msec
outperform LA-AODV with T
w
of 0.1 msec. Hence, T
w
of 1 msec is long enough to achieve the
highest performance in the given environment. As the environment noise increases, the per-
route goodput of LA-AODV is rapidly decreased compared with the basic AODV. It is also
decreased with the increased number of sessions.

0.2
0.4
0.6
0.8
1.0
-90 -88 -86 -84 -82 -80
Environm ent noise (dBm )
Packet delivery ratio
LA -AO D V (Tw = 10 m sec)
LA -AO D V (Tw = 1 m sec)
LA -AO D V (Tw = 0.1 m sec)
Basic AODV

0.2
0.4
0.6
0.8
1.0
2 6 10 14 18
Num ber of sessions
Packet delivery ratio
LA-AO DV (Tw = 10 m sec)
LA-AO DV (Tw = 1 m sec)
LA-AO DV (Tw = 0.1 m sec)
Basic AO D V

(a) Varying environment noise (b) Varying the number of sessions
Fig. 5. Packet delivery ratio.
Link Quality Aware Robust Routing for Mobile Multihop Ad Hoc Networks

213
0
3
6
9
12
15
18
-90 -88 -86 -84 -82 -80
Environm ent noise (dBm )
Per-route goodput (packets/sec)
LA -AO D V (Tw = 10 m sec)
LA -AO D V (Tw = 1 m sec)

LA-A O DV (Tw = 0.1 m sec)
Basic A O D V
0
3
6
9
12
15
18
26101418
Num ber of sessions
Per-route goodput (packets/sec)
LA -A O D V (Tw = 10 m sec)
LA -A O D V (Tw = 1 m sec)
LA -A O D V (Tw = 0.1 m sec)
Basic A O D V

(a) Varying environment noise (b) Varying the number of sessions
Fig. 6. Per-route goodput.
4.3.3 Normalized control overhead.
Fig. 7 shows the normalized control overhead for varying the environment noise and the
number of sessions. As can be expected, LA-AODV incurs more control overhead compared
to the basic AODV for both the environment noise and the number of sessions. This is a kind
of side effect paid to achieve robust delivery and high performance. As the environment
noise increases, the normalized overhead is increased as expected. It is almost constant with
the increased number of sessions. This mainly due to the fact that, as the number of sessions
increases, the number of delivered data packets is also increased while the number of
control packets is increased.

0

5
10
15
20
25
30
-90 -88 -86 -84 -82 -80
Environm ent noise (dBm )
Norm alized control overhead
LA -A O D V (Tw = 10 m sec)
LA -A O D V (Tw = 1 m sec)
LA -A O D V (Tw = 0.1 m sec)
Basic AO D V
0
5
10
15
20
25
30
2 6 10 14 18
Num ber of sessions
Norm alized control overhead
LA -A O D V (Tw = 10 m sec)
LA -A O D V (Tw = 1 m sec)
LA -A O D V (Tw = 0.1 m sec)
B asic A O D V

(a) Varying environment noise (b) Varying the number of sessions
Fig. 7. Normalized control overhead.

4.3.4 Impact on node mobility in the harsh environment.
In general, the network performance is highly affected by node mobility in the normal
operation environment and it is degraded with increased mobility. Fig. 8 shows the impact
on node mobility in the harsh environment with the noise level of -84 dBm. LA-AODV
outperforms the basic AODV in terms of packet delivery ratio and per-route goodput for
different pause time. However, the packet delivery ratio and per-route goodput are almost
Mobile Ad-Hoc Networks: Protocol Design

214
constant with increased pause time except for very high mobility. In other words, it is
inferred from the results that the node mobility is not a major factor affecting performance
in the harsh operation environment.

0.4
0.6
0.8
1.0
0 300 600 900
Pause tim e (sec)
Packet delivery ratio
LA -AO D V (Tw = 10 m sec)
LA -AO D V (Tw = 1 m sec)
LA -AO D V (Tw = 0.1 m sec)
B asic AODV
0
3
6
9
0 300 600 900
Pause tim e (sec)

Per-route goodput (packets/sec)
LA -AO D V (Tw = 10 m sec)
LA -AO D V (Tw = 1 m sec)
LA -AO D V (Tw = 0.1 m sec)
B asic A O D V

(a) Packet delivery ratio (b) Per-route goodput
Fig. 8. Effect of varying pause time in the harsh environment.
5. Conclusions
In this paper, the link quality aware AODV (LA-AODV) has been presented by devising the
RREQ forwarding algorithm, resulting in robust packet delivery and high network
performance. The RREQ forwarding algorithm finds out a reliable path with strong links.
During route discovery, the strong links are effectively exploited by forwarding the route
request (RREQ) packet with the highest link quality or signal to interference plus noise ratio
(SINR) among the multiple RREQ packets received. Some tolerance is applied to the link
quality in choosing an RREQ to be forwarded in order for coping with the dynamic behavior
of SINR. Compared to the basic AODV, the proposed scheme may not have the minimum
hop-count route but the one with more number of hops. However, the discovered route is a
reliable path with high data rate because it consists of strong links, resulting in high
performance as well as robust routing. The performance study shows that packet delivery
ratio is improved by up to 70% and per-route goodput is dramatically increased by a factor of
up to 12. It is also shown that the acceptable value of the RREQ waiting time (T
w
) is 1 msec in
the simulated environment, which is enough to achieve fairly good performance.
The proposed mechanism can be easily applied to other routing protocols using broadcast-
based route discovery. To extend the LA-AODV principle to hierarchical routing protocols and
multicast protocols is another future work. Our future work includes the exploration of a
new link quality aware routing protocol for MANETs with asymmetric links as well, which
should be a very challenging work.

6. Acknowledgement
This research was supported in part by the MKE (The Ministry of Knowledge Economy),
Korea, under the ITRC (Information Technology Research Center) support program
supervised by the NIPA (National IT Industry Promotion Agency) (NIPA-2010-C1090-1021-
Link Quality Aware Robust Routing for Mobile Multihop Ad Hoc Networks

215
0013). A preliminary version of this work was presented at the 11th IEEE International
Conference on High Performance Computing and Communications, June 25-27, 2009 (Moh,
2009).
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