Routing performance in the presence of unidirectional links in multihop wireless networks.
We examine two aspects concerning the influence of unidirectional links on routing performance in multihop wireless networks. In the first part of the paper we evaluate the benefit from utilizing unidirectional links for routing as opposed to using only bidirectional links. Our evaluations are based on three transmit power assignment models that reflect some realistic network scenarios with unidirectional links. Our results indicate that the marginal benefit of using a high-overhead routing protocol to utilize unidirectional links is questionable.Most common routing protocols however simply assume that all network links are bidirectional and thus may need additional protocol actions to remove unidirectional links from route computations. In the second part of the paper we investigate this issue using a well known on-demand routing protocol Ad hoc On-demand Distance Vector (AODV) as a case study. We study the performance of three techniques for AODV for efficient operation in presence of unidirectional links viz. BlackListing Hello and ReversePathSearch. While BlackListing and Hello techniques explicitly eliminate unidirectional links the ReversePathSearch technique exploits the greater network connectivity offered by the existence of multiple paths between nodes. Performance results using ns-2 simulations under varying number of unidirectional links and node speeds show that all three techniques improve performance by avoiding unidirectional links the ReversePathSearch technique being the most effective.
INTRODUCTION
A unidirectional link arises between a pair of nodes in a network
when only one of the two nodes can directly communicate with
the other node. In multihop wireless networks (also known as ad
hoc networks), unidirectional links originate because of several rea-
sons. These include difference in radio transceiver capabilities of
nodes, the use of transmission range control, difference in wireless
channel interference experienced by different nodes. Depending on
such conditions, unidirectional links can be quite common.
This paper addresses routing in the presence of unidirectional
links. Most of the previous work on this problem concentrated on
developing routing protocols [1, 10, 39, 31, 33, 2], or techniques
such as tunneling [23] to allow the use of unidirectional links. But
the resulting performance advantages and tradeoffs are not well un-
derstood. Our approach in this work is to empirically study the
influence of unidirectional links on routing performance.
Utilizing unidirectional links along with bidirectional links for
routing has two conceivable advantages over using only bidirectional
links. First, they can improve the network connectivity. For
example, removal of unidirectional links in Figure 1 partitions the
network. Second, they can provide better, i.e., shorter, paths. In

Figure

node B can communicate to node C directly in one hop
by using the unidirectional link as the alternate
bidirectional path B E C requires two hops.
But routing using unidirectional links is complex and entails high
overheads. Main difficulty comes from the asymmetric knowledge
about a unidirectional link at its end nodes. A node downstream of a
unidirectional link (for example, node F in Figure 1) immediately
knows about the incoming unidirectional link (link
hearing a transmission from the upstream node (node E); but the
upstream node may not know about its outgoing unidirectional link
until the downstream node explicitly informs it over a multihop
reverse path (say, F A Learning about the
unidirectional link thus incurs higher overhead than when the link
is bidirectional.
There is evidence in the literature that routing protocols finding
unidirectional paths (paths with one or more unidirectional links)
are subject to higher overheads than those finding only bidirectional
paths. For distance-vector protocols, Gerla et al. [10] and
Prakash [33] independently make this observation. In the realm of
on-demand protocols for ad hoc networks also, similar observation
can be made. DSR [15] requires two route discoveries to discover
unidirectional paths - one from the source and the other from the
destination, as opposed to a single route discovery to find bidirectional
paths. Although pure link-state protocols such as OSPF
[21] may be able to support unidirectional links with least additional
overhead, they already have very high overheads compared
A
F

Figure

1: A network with unidirectional links.
to other competing protocols for ad hoc networks [6]. Exactly for
this reason, efficient variants of link-state protocols (e.g., TBRPF
[24], OLSR [5]) have been developed. But these protocols work
only with bidirectional links.
Besides, the use of unidirectional links poses problems to existing
link-layer protocols. Many common link-layer protocols for
medium access and address resolution not only assume bidirectional
links, but also very much depend on two-way handshakes
and acknowledgments for their operation. For example, the well-known
IEEE 802.11 DCF MAC protocol [14] depends on the exchange
of RTS-CTS control packets between the sender and the
receiver to prevent hidden terminal collisions, and also expects acknowledgment
from the receiver to judge correct packet reception
of unicast transmissions.
Thus it is important to evaluate the potential benefit of unidirectional
links to know whether employing a seemingly high overhead
unidirectional link routing protocol is justified. We evaluate this
benefit in the first part of the paper. We compare two routing ap-
proaches: (i) using both unidirectional and bidirectional links; (ii)
using only bidirectional links. We look at the idealized routing performance
obtained from these two approaches - independent of
specific routing protocols or associated overheads - to find out
any performance advantages of utilizing unidirectional links. To
accomplish this goal, we simulate a large number of random multihop
network topologies with unidirectional links. We study the
connectivity and path cost metrics of these topologies when uni-directional
links are used, and when they are ignored. In order to
create unidirectional links, we use three models that assign variable
transmission ranges to nodes. These models reflect some realistic
wireless network scenarios having unidirectional links. Our results
show that the connectivity advantage using unidirectional links is
almost non-existent, but shortest path costs show some improvement
with unidirectional links. However, these improvements too
go away when hop-by-hop acknowledgment costs are accounted.
Utilizing unidirectional links for routing purposes may not be ef-
ficient, and most routing protocols indeed work with only bidirectional
links. But these protocols must still need additional mechanisms
to "eliminate" unidirectional links from route computations
when they are present. We investigate the importance of such mechanisms
using a well-known on-demand routing protocol called Ad
hoc On-demand Distance Vector (AODV) [29, 28]. The basic AODV
protocol works only with bidirectional links. We propose a new
technique called ReversePathSearch to handle unidirectional links
in AODV. This technique takes advantage of multiple paths between
nodes to overcome unidirectional links. We also consider
two other techniques - BlackListing and Hello - that explicitly
eliminate unidirectional links in AODV. Using ns-2 simulations, we
evaluate the performance of these three techniques relative to basic
AODV.
The rest of the paper is organized as follows. Section 2 evaluates
the idealized performance advantage of routing using unidirectional
links. Section 3 investigates the issue of avoiding unidirectional
links from route computations in the context of AODV.
Here we present and evaluate three techniques to improve basic
AODV performance in networks with unidirectional links. Section
4 reviews related work. Finally, we present our conclusions in Section
5.
2. BENEFITOFUNIDIRECTIONALLINKS
2.1 Unidirectional Link Scenarios
Generally speaking, there are two principal reasons behind the
presence of unidirectional links in multihop wireless networks. First,
difference in radio transmission power level (or receiver sensitiv-
ity) of the nodes give rise to unidirectional links. When two nodes
(say A and B) have widely different radio transmission ranges 1 so
that node A can transmit to node B but not the other way, a uni-directional
link forms from node A to node B. Nodes may naturally
have different transmission ranges in a heterogenous network
where there is an inherent difference in radio capabilities. Alter-
natively, they may have different transmission ranges when power
control algorithms are used for energy savings or topology control.
Second, difference in interference (or noise) at different nodes
cause asymmetric links. Asymmetric links occur between a pair of
nodes if the link quality is different in each direction. An extreme
case of link asymmetry leads to unidirectional links. Nodes may
experience different interference levels because of wireless channel
imperfections such as multipath fading and shadowing. Hidden
terminals can be another cause of wide variation in interference
levels (as also mentioned in [33]).
To study the benefit of unidirectional links for routing, we only
consider unidirectional links arising from difference in transmission
ranges. Note that for unidirectional links to be effective for
routing, they should exist long enough for the routing protocol to
compute routes through them and to later use such routes to forward
some data. Unidirectional links caused by variation in interference
levels presumably happen on much smaller time-scales
than would be needed for routing. So here we limit ourselves to
unidirectional links from variable transmission ranges. However,
later in the paper, we do take into account the issue of interference
to some extent, specifically from hidden terminals, when studying
the negative influence of unidirectional links on routing.
Among the power control algorithms, only a particular class is
relevant here. Some power control algorithms prescribe a common
power level for all nodes in the network (e.g., [22]). These
algorithms do not create any unidirectional links. Other algorithms
that do allow variable power levels either assign power levels on
a per-transmission basis (e.g., [41, 20]), or assign power levels independent
of any single transmission, but may be used for several
successive transmissions (e.g., [13, 37, 34, 40]). Since the former
set of algorithms may result in short-term unidirectional links, we
limit our attention to the latter class only.
We will sometimes use transmission range instead of transmission
power to simplify description. Note that it is usually straightforward
to compute the "nominal" transmission range of a node given
the transmission power, large-scale path loss model, and the radio
parameters.
2.2 Models for Variable Transmit Power As-
signment
Based on the above discussion, we use the following models in
our evaluations to create networks with unidirectional links.
TwoPower In this model, the transmission range of a node can
take one of two possible values with equal probability. A
node can have either a short or a long range corresponding
to low and high transmission power levels, respectively. The
fraction of low power nodes is the variable parameter. A
similar model was used in [38, 26]. This model represents a
heterogenous network with two widely different radio capa-
bilities. For example, transmission power levels of vehicular
and man-pack radios in a battlefield scenario can differ by as
much as 10dB.
RandomPower With this model, each node is assigned a random
transmission range that is uniformly distributed between minimum
and maximum range values. This model is representative
of two practical scenarios where unidirectional links
might occur: (i) a generalization of TwoPower level model
described above, i.e., a network of nodes with multiple different
power levels; (ii) a snapshot of a network in which
each node adjusts its transmit power based on the available
energy supply to conserve its battery power.
Rodoplu and Meng (R&M) This model is based on the distributed
topology control algorithm proposed by Rodoplu and Meng
[37]. Topology control algorithms (e.g., [13, 37, 34, 40])
adjust node transmit powers in order to obtain a topology
that optimizes a certain objective such as network capacity,
network reliability or network lifetime. Almost all topology
control algorithms in the literature try to guarantee some
form of network connectivity while optimizing one or all of
the above criteria. We have chosen the R&M algorithm because
it is the only algorithm in our knowledge that considers
unidirectional links and ensures strong connectivity possibly
using some unidirectional links. This feature of the algorithm
provides a favorable case for the use of unidirectional
links for routing to potentially provide better network con-
nectivity. All other algorithms guarantee connectivity using
bidirectional links alone and thus are not good candidates for
our evaluation.
Here we briefly review the R&M algorithm for the benefit
of the readers. The algorithm aims at achieving energy
efficiency through transmit power adjustment. Because of
the nature of wireless communication, it is sometimes energy
efficient for a node to use a lower transmit power and
communicate with a farther node using intermediate relaying
nodes than to use higher power and communicate directly.
The algorithm uses this observation to advantage. Central to
the algorithm is the notion of an enclosure. Enclosure of a
node represents its immediate locality. As long as each node
maintains links with nodes in its enclosure, strong connectivity
is guaranteed. So each node reduces its transmit power
from the maximum value to a level where it can reach only
nodes in its enclosure. The algorithm assumes that each node
knows its position. Every node computes its enclosure set
by exchanging position information with all reachable nodes
(using maximum power).
2.3 Evaluation Methodology
Our goal here is to assess the benefit attainable from using uni-directional
links for routing in multihop wireless networks. To accomplish
this goal, we evaluate the idealized routing performance
of two approaches: (i) utilizing unidirectional as well as bidirectional
links; (ii) utilizing only bidirectional links. Our evaluation
process involves static simulation of large number (over a thousand
for each data point) of random multihop network topologies containing
unidirectional links, and comparing the average connectivity
and path cost metrics with and without unidirectional links. The
three models for transmit power assignment described in the previous
subsection are used to generate networks with unidirectional
links.
To measure connectivity, we compute the average number of
strongly connected components and largest strongly connected component
over all random graph samples. For comparing the path
quality, we consider the average shortest path cost, per-hop acknowledgment
cost and the total communication cost. Note that
all path costs are in number of hops and are averaged over all node
pairs having a bidirectional path between them, for each random
graph sample - averaged over all such samples. The per-hop acknowledgment
cost is computed as the average cost of traversing
a shortest path between a pair of nodes hop-by-hop in the reverse
direction. The total communication cost is simply the sum of the
shortest path and acknowledgment costs.
We experiment with a wide variety of node densities and radio
ranges. All our experiments are for 100 node networks. Each
random network topology consists of nodes randomly placed in a
square field. To vary node density (measured as nodes/sq. km), the
dimensions of the field are varied. In all three range assignment
models, a fixed maximum transmission range of 250 m is used. In
the TwoPower model, the fraction of low power nodes is varied to
get different range assignments. The long range is same as the maximum
range, while the short range is always set to 125 m. Note that
we experimented with different short range values, but the results
are not very sensitive to these values. In the RandomPower model,
the minimum range is changed for variation in ranges. In the R&M
model, the radio range of a node is controlled by the algorithm, and
cannot be artificially varied.
2.4 Simulation Results
2.4.1 Variation in Node Density
Here we study the effect of node density on connectivity and path
cost metrics in all three range assignment models. The fraction of
low power nodes in the TwoPower model is set to 0.5 as this value
results in the most number of unidirectional links. In the Random-
Power model, the minimum range value is kept constant at 125 m
which is chosen somewhat arbitrarily. We did experiments with
other values of minimum range, but the results did not vary much.
Node density is varied so that all network configurations are covered
starting from very sparse and disconnected networks to highly
dense and connected networks. Note that number of unidirectional
and bidirectional links (data not shown) increase with increase in
density in all three models. However, the relative number of these
links and their rate of increase with density is very much dependent
on the specific model used. Also, we noticed that the mean radio
range in the R&M model shrank as nodes become denser. This is
expected, however, given the nature of the underlying algorithm.
The first set of plots (Figure 2) study the network connectivity
properties with and without using unidirectional links. The number
of strongly connected components and the size of the largest components
are very similar regardless of whether or not unidirectional
links are used. Note that unidirectional links do not improve connectivity
in the R&M model even though they are explicitly taken
into account by the algorithm. Furthermore, we found that connec-
0Strongly
connected
components
Density (nodes/sq. km)
With unidirectional links
unidirectional links
(a) TwoPower5152535450 50 100 150 200 250 300 350 400 450 500
Strongly
connected
components
Density (nodes/sq. km)
With unidirectional links
unidirectional links
(b) RandomPower26101418
Strongly
connected
components
Density (nodes/sq. km)
With unidirectional links
unidirectional links
(c) R&M20406080100
Largest
strongly
connected
component
Density (nodes/sq. km)
With unidirectional links
unidirectional links
(d) TwoPower20406080100
Largest
strongly
connected
component
Density (nodes/sq. km)
With unidirectional links
unidirectional links
Largest
strongly
connected
component
Density (nodes/sq. km)
With unidirectional links
unidirectional links

Figure

2: Connectivity metrics in all three models with varying density.
tivity metrics in this model are exactly identical to the case where
all nodes use the maximum range. Both these observations suggest
that it may be somewhat unlikely in random topologies for two sub-components
to be connected by two unidirectional links (between
different node pairs).
The second set of plots (Figure 3 (a, b, c)) shows the average cost
of the shortest path. The initial hump in the plots is because of the
sharp transition from disconnected to connected networks within a
small range of densities. Observe that ignoring unidirectional links
only marginally increases the shortest path cost in TwoPower and
RandomPower models (Figure 3 (a, b)) except when the density is
between 50-100 nodes/sq. km, where the increase is more signifi-
cant. In the R&M model (Figure 3 (c)), the increase is marginal for
lower density, but increases with increasing density.
However, note that the shortest path cost is only a part of the
overall picture. Many ad hoc network protocols use some sort of
per-hop acknowledgment either in the network or the link layer to
guarantee reliable transmission and also to detect link breaks. Use
of unidirectional links will cause such acknowledgments to traverse
multiple hops - possibly in the network layer (see [23] for an idea
based on tunneling). This will increase the overall communication
cost. As expected, the hop-by-hop acknowledgement costs are
more in all three models when unidirectional links are used (Figure
3 (d, e, f)). The overall communication cost in TwoPower and Ran-
domPower models (Figure 3 (g, h)) is approximately the same with
or without unidirectional links. In the R&M model (Figure 3 (i)),
they are still similar for lower density, but the use of unidirectional
links brings down the cost a bit (up to 10%) when the node density
is very high.
2.4.2 Variation in Radio Range
Till now, in TwoPower and RandomPower models, the variability
in range has been fixed and node density has been varied. Here
we study the effect of variation in ranges for a fixed density. We set
the node density to 100 nodes/sq. km which yields a connected net-work
when all nodes use the maximum range. Using this density
value allows us to meaningfully evaluate the connectivity advantage
from unidirectional links. A higher value of density will produce
more number of bidirectional links and thus benefits the case
without unidirectional links. On the other hand, a lower density
value will not allow us to explore the whole range of connectivi-
ties, as network will not get connected for any range assignment.

Figure

4 shows all metrics with varying fraction of low power
nodes in the TwoPower model. Note that connectivity (Figure 4
improves only slightly (less than a few percents) by using
unidirectional links. On the other hand, the average total communication
cost (Figure 4 (e)) improves (up to about 7%, but mostly
lower) when a large fraction of nodes is low power; the costs are
similar when a small fraction of nodes is low power.
The effect of variability in node ranges in the RandomPower
model is shown in Figure 5 for different values of the minimum
range. There is some noticeable improvement (about 15%) in the
largest components (Figure 5 (b)) with unidirectional links when
minimum range is very small. However, for higher values of minimum
range, the improvements start to drop. This is somewhat
expected because the variability in node ranges decreases with increase
in the minimum range. Similar observation applies for communication
cost (Figure 5 (e)) as well; there is up to 10% improvement
with unidirectional links when the minimum range is small.
The general observation from the foregoing evaluations is that
unidirectional links provide only incremental benefit. They do not
improve connectivity in most cases. They do improve shortest path
cost in general. But with per-hop acknowledgments, the overall
benefit is small and is restricted to only certain densities and radio
ranges.
3. ELIMINATION OF UNIDIRECTIONAL
Majority of the protocols developed for multihop wireless networks
assume bidirectional links (e.g., [17], DSDV [27], AODV [28],
6
Avg.
shortest
path
cost
Density (nodes/sq. km)
With unidirectional links
unidirectional links
(a) TwoPower357
Avg.
shortest
path
cost
Density (nodes/sq. km)
With unidirectional links
unidirectional links
(b) RandomPower579
Avg.
shortest
path
cost
Density (nodes/sq. km)
With unidirectional links
unidirectional links
(c) R&M23456
Avg.
hop-by-hop
ack
cost
Density (nodes/sq. km)
With unidirectional links
unidirectional links
(d) TwoPower357
Avg.
hop-by-hop
ack
cost
Density (nodes/sq. km)
With unidirectional links
unidirectional links
Avg.
hop-by-hop
ack
cost
Density (nodes/sq. km)
With unidirectional links
unidirectional links
Avg.
communication
cost
Density (nodes/sq. km)
With unidirectional links
unidirectional links
Avg.
communication
cost
Density (nodes/sq. km)
With unidirectional links
unidirectional links
Avg.
communication
cost
Density (nodes/sq. km)
With unidirectional links
unidirectional links

Figure

3: Path cost metrics in all three models with varying density.
TBRPF [24], OLSR [5]). But for correct operation in the presence
of unidirectional links, they require additional mechanisms to eliminate
unidirectional links from route computations. Our goal in this
section is to understand the importance of such mechanisms and
their effect on the overall performance of the routing protocol. We
investigate this issue using AODV as a case study. While general
comments are difficult to make, we do believe that other protocols
will also benefit from the mechanisms we develop and our observations
from the performance evaluation.
3.1
AODV is an on-demand routing protocol. It is loosely based on
the distance-vector concept. In on-demand protocols, nodes obtain
routes on an as needed basis via a route discovery procedure. Route
discovery works as follows. Whenever a traffic source needs a route
to a destination, it initiates a route discovery by flooding a route request
(RREQ) for the destination in the network and then waits for
a route reply (RREP). When an intermediate node receives the first
copy of a RREQ packet, it sets up a reverse path to the source using
the previous hop of the RREQ as the next hop on the reverse
path. In addition, if there is a valid route available for the desti-
nation, it unicasts a RREP back to the source via the reverse path;
otherwise, it re-broadcasts the RREQ packet. Duplicate copies of
the RREQ are immediately discarded upon reception at every node.
The destination on receiving the first copy of a RREQ packet forms
a reverse path in the same way as the intermediate nodes; it also
unicasts a RREP back to the source along the reverse path. As the
RREP proceeds towards the source, it establishes a forward path to
the destination at each hop. AODV also includes mechanisms for
erasing broken routes following a link failure, and for expiring old
and unused routes. We do not discuss them, as they are not relevant
here.
The above route discovery procedure requires bidirectional links
for correct operation. Only then RREP can traverse back to the
source along a reverse path and form a forward path to the destination
at the source. Many common MAC protocols check link
bidirectionality only for unicast transmissions. For example, IEEE
802.11 DCF MAC [14] protocol uses an RTS-CTS-Data-ACK exchange
for unicast transmissions; receipt of CTS following an RTS
or ACK following the data transmission on a link ensures that it is
bidirectional. Broadcast transmissions, however, cannot detect the
presence of unidirectional links. Since AODV RREQ packets typically
use link-layer broadcast transmissions, some unidirectional
links can go undetected and as a result reverse paths may contain
unidirectional links (directed away from the source). RREP transmissions
along such reverse paths will fail, as they are unicast.
Route discovery fails when none of the RREPs reach the source.
Strongly
connected
components
Fraction of low power nodes
With unidirectional links
unidirectional links
Largest
strongly
connected
component
Fraction of low power nodes
With unidirectional links
unidirectional links
(b)34567
Avg.
shortest
path
cost
Fraction of low power nodes
With unidirectional links
unidirectional links
(c)34567
Avg.
hop-by-hop
ack
cost
Fraction of low power nodes
With unidirectional links
unidirectional links
Avg.
communication
cost
Fraction of low power nodes
With unidirectional links
unidirectional links

Figure

4: TwoPower model: connectivity and path cost metrics with varying fraction of low power nodes.261014180 50 100 150 200 250
Strongly
connected
components
Minimum transmission range (m)
With unidirectional links
unidirectional links
(a)657585950 50 100 150 200 250
Largest
strongly
connected
component
Minimum transmission range (m)
With unidirectional links
unidirectional links
(b)34560 50 100 150 200 250
Avg.
shortest
path
cost
Minimum transmission range (m)
With unidirectional links
unidirectional links
Avg.
hop-by-hop
ack
cost
Minimum transmission range (m)
With unidirectional links
unidirectional links
Avg.
communication
cost
Minimum transmission range (m)
With unidirectional links
unidirectional links

Figure

5: RandomPower model: connectivity and path cost metrics with varying values of minimum range.

Figure

All links are bidirectional except the one with an ar-
row. A receives first copy of RREQ from S for D via S A
path, and forms a reverse path A S; subsequent RREP transmission
from A to S will fail. This scenario will repeat for later
route discovery attempts from S. The alternate, longer path
will never be discovered.
It can fail even when there is a bidirectional path between the source
and the destination. This is because only the first copy of a RREQ
packet - which may arrive via a unidirectional path from the source
- is considered by intermediate nodes and the destination to form
reverse paths and send back RREPs; later copies are simply discarded
even if they take bidirectional paths. See Figure 6 for an
In the worst case, this scenario will result in repeated route discovery
failures. Thus additional mechanisms are needed to avoid
the above problem in networks with unidirectional links.
3.2 Techniques for Handling Unidirectional
Links in AODV
In the following we describe three techniques to alleviate this
problem. The first two techniques - "BlackListing" and "Hello"
are known techniques. The third technique, "ReversePathSearch"
is our contribution in this paper.
BlackListing This technique reactively eliminates unidirectional
links. It is included in the latest AODV specification [29].
Here, whenever a node detects a RREP transmission failure,
it inserts the next hop of the failed RREP into a "blacklist"
set. The blacklist set at a node indicates the set of nodes
from which it has unidirectional links. For example, in Figure
6 node A will blacklist node S. Later when a node receives
a RREQ from one of the nodes in its blacklist set,
it discards the RREQ to avoid forming a reverse path with
unidirectional link. This gives a chance for RREQ from an
alternate path (e.g., via C in Figure 6) to provide a different
reverse path. BLACKLIST TIMEOUT specifies the period
for which a node remains in the blacklist set. By default, this
period is set to the upper bound of the time it takes to perform
the maximum allowed number of route discovery attempts by
a source.
This technique is simple and has little overhead when there
are few unidirectional links. However, when there are many
unidirectional links, this approach is inefficient because these
links are blacklisted iteratively one at a time. Several route
discoveries may be needed before a bidirectional path, if ex-
ists, is found. Another difficulty with this technique is in setting
an appropriate value for the BLACKLIST TIMEOUT.
Setting it to a small value may reduce the effectiveness of the
technique. On the other hand, setting it to a very large value
affects connectivity when there are many short-term unidirectional
links.
Hello In the contrast to the BlackListing technique, this technique
proactively eliminates unidirectional links by using periodic
one-hop Hello packets. A similar idea has also been used in
OLSR [5] to record only bidirectional links. In each Hello
packet, a node includes all nodes from which it can hear Hellos
(i.e, its set of neighbors). If a node does not find itself in
the Hello packet from another node, it marks the link from
that node as unidirectional. Just as in the BlackListing tech-
nique, every node ignores RREQ packets that come via such
unidirectional links. Note that this hello packets are identical
to the AODV hello packets [29] except for the additional
neighborhood information.
The advantage of this technique is that it automatically detects
unidirectional links by exchanging Hello packets. But
the periodic, large Hello packets can be a significant over-
head. Although the size of the Hello packets may be reduced
by using "differential" Hellos [24], the periodic packet overhead
is still a concern. However, in situations when Hellos
must be used for maintaining local neighborhood and to detect
link failures (e.g., when the link layer cannot provide
any feedback about link failures), incremental overhead for
unidirectional link detection may not be very much.
ReversePathSearch Unlike the above two techniques, this technique
does not explicitly remove unidirectional links. In-
stead, it takes a completely different approach. Each unidirectional
link is viewed as a "fault" in the network and multiple
paths between the nodes are discovered to perform fault-tolerant
routing. The basic idea is as follows. During the
RREQ flood, multiple loop-free reverse paths to the source
are formed at intermediate nodes and the destination. Using
a distributed search procedure, multiple RREPs explore
this multipath routing structure in an attempt to find one or
more bidirectional paths between the source and the destina-
tion. This search procedure is somewhat similar to the well-known
depth first search algorithm. When RREP fails at a
node, the corresponding reverse path is erased and the RREP
is retried along an alternate reverse path, if one is available;
when all reverse paths fail at a node during this process, the
search backtracks to upstream nodes 2 of that node with respect
to the source and they too follow the same procedure.
This continues until either one or more bidirectional paths
are found at the source, or all reverse paths are explored.
This technique is described in more detail in the following
subsection.
3.3 Reverse Path Search Technique
In a prior work [19], we have investigated a multipath extension
to AODV, called AOMDV, where route update rules to maintain
multiple loop-free paths are described. We use the same AOMDV
route update rules here in the ReversePathSearch technique to maintain
multiple loop-free paths to a destination at every node.
In the ReversePathSearch algorithm, all RREQ copies including
duplicates are examined at intermediate nodes and the destination
for possible alternate reverse paths to the source. However, reverse
2 A node X is upstream of a node Y with respect to a node D if Y
appears on a path from X to D. Conversely, Y is a downstream node
of X for D.
F
G

Figure

7: Demonstration of reverse path search. Multiple reverse
paths to the source S formed during the RREQ flood
are shown; some of the reverse paths contain unidirectional
links such as C A S. Consider the RREP propagation
via C A S. The transmission from A to S fails causing
a BRREP transmission at A. C erases the reverse path via A
and transmits a RREP to B in order to explore the reverse path
This also fails, causing C to transmit BRREP. E
then erases the reverse path via C and transmits RREP to F
in order to explore path E F G H S. This will be
successful.
paths are formed only from those copies that satisfy route update
rules and provide loop-free paths [19]. Other copies are simply
discarded. Note that this is different from basic AODV where only
the first copy is looked at.
When a RREQ copy at an intermediate node creates or updates
a reverse path, and the intermediate node has no valid path to the
destination, the RREQ copy is re-broadcasted provided it is the first
copy that yields a reverse path; this is somewhat similar to basic
AODV where only first copies of RREQ are forwarded to prevent
looping during the flood. On the contrary, if the intermediate node
does have a valid path to the destination, it checks whether or not a
RREP has already been sent for this route discovery. If not, it sends
back a RREP along the newly formed reverse path and remembers
the next hop used for this RREP; otherwise, the RREQ copy is
dropped.
When the destination receives copies of RREQs, it also forms
reverse paths in the same way as intermediate nodes. However, unlike
intermediate nodes, the destination sends back a RREP along
each new reverse path. Multiple replies from destination allow exploration
of multiple reverse paths concurrently - thus speeding
up the search for a bidirectional path. In contrast, allowing multiple
destination replies in basic AODV has little benefit unless those
replies take non-overlapping paths to the source. This is because intermediate
nodes have at most one reverse path back to the source.
When an intermediate node receives a RREP, it follows route
update rules in [19] to form a loop-free forward path to the desti-
nation, if possible; else, the RREP is dropped. Supposing that the
intermediate node forms the forward path and has one or more valid
reverse paths to the source, it checks if any of those reverse paths
was previously used to send a RREP for this route discovery. If not,
it chooses one of those reverse paths to forward the current RREP,
and also remembers the next hop for that reverse path; otherwise,
the RREP is simply dropped.
RREP transmission failure (as a result of transmission over a
unidirectional link, for example) at an intermediate node results in
that node erasing the corresponding reverse path, and retrying an
alternate reverse path. If no such alternate path is available, the intermediate
node transmits (broadcast transmission) a new message
called the "backtrack route reply" (BRREP) to inform its upstream
nodes (with respect to the source) to try other reverse paths at those
nodes. A BRREP is also generated by an intermediate node, if that
node does not have any reverse path upon a RREP reception. On
receiving a BRREP, an intermediate node upstream of the BRREP
source (meaning it has last sent a RREP to the BRREP source for
this route discovery) takes a similar action as on a RREP failure;
nodes that are not upstream of the BRREP source simply discard
the packet on reception. When the destination encounters a RREP
failure, or receives a BRREP, it only erases corresponding reverse
paths. See Figure 7 for an illustration.
Note that the above procedure is guaranteed to terminate. To
see this, observe that every RREP failure erases the corresponding
reverse path. So reverse paths cannot be explored indefinitely since
there are only finite number of them. On the other hand, alternate
reverse paths are not explored at the intermediate nodes as long
as RREPs successfully go through. Also note that in the above
description, some details have been omitted for the sake of brevity.
For instance, algorithms actions to cope with BRREP loss are not
mentioned.
Multiple loop-free reverse paths used by the above algorithm are
in general a subset of all possible reverse paths. Thus, sometimes it
is possible that the multiple reverse paths explored by the algorithm
do not include a bidirectional path between source and destination
although such a path exists. But in dense networks that we con-
sider, often there is more than one bidirectional path and the above
possibility is rare.
Finally, multiple replies from the destination in the algorithm
yield multiple forward paths at intermediate nodes and the source.
This ability to compute multiple bidirectional paths in a single route
discovery is highly beneficial in mobile networks for efficient recovery
from route breaks.
3.4 Performance Evaluation
In this section we evaluate the performance of the three techniques
described in the previous subsection relative to basic AODV
under varying number of unidirectional links and node speeds. Two
primary goals from this evaluation are: (i) to understand the impact
of unidirectional links on basic AODV performance; and (ii)
to evaluate the effectiveness of the three techniques in handling uni-directional
links.
3.4.1 Simulation Environment
We use a detailed simulation model based on ns-2 [8]. The
Monarch research group in CMU developed support for simulating
multi-hop wireless networks complete with physical, data link
and MAC layer models [4] on ns-2. The distributed coordination
function (DCF) of IEEE 802.11 [14] for wireless LANs is used
as the MAC layer. The radio model uses characteristics similar to
a commercial radio interface, Lucent's WaveLAN. WaveLAN is a
shared-media radio with a nominal bit-rate of 2 Mb/s and a nominal
radio range of 250 meters. More details about the simulator
can be found in [4, 8]. This simulator has been used for evaluating
performance of earlier versions of the AODV protocol (e.g., [4,
30]).
The AODV model in our simulations is based on the latest protocol
specification [29], except that the expanding ring search is
disabled for all protocol variations. Note that the expanding ring
search introduces an additional reason for route discovery failures,
i.e., when a smaller ring size (TTL value) is used for the search.
This makes analysis somewhat difficult. So in our AODV model,
a source does network-wide route discoveries appropriately spaced
in time until either a route is obtained or a maximum retry limit
(3) is reached; when the limit is exceeded, source reports to the application
that the destination is unreachable and drops all buffered
packets for the destination - we term this event as "route search
failure" in our evaluations. Besides, link layer feedback is used
to detect link failures in all protocol variations. The 802.11 MAC
layer reports a link failure when it fails to receive CTS after several
RTS attempts, or to receive ACK after several retransmissions of
DATA. Note that in the Hello technique, link failures are detected
using hello messages as well as the feedback, whichever detects the
link breakage first.
TwoPower model is used to create unidirectional links, primarily
because it does not perform power control. Use of power control
makes the analysis here difficult as the number of unidirectional
links then will become heavily dependent on the choice of the actual
power control algorithm and the frequency at which the algorithm
is invoked. Note that the frequency of invocation did not play
any role in our earlier evaluations as we used only static topolo-
gies. We modified the ns-2 simulator to allow variable transmission
ranges for nodes. In all our experiments, short and long ranges
in the TwoPower model are set to 125 m and 250 m, respectively.
We vary the fraction of low power nodes to vary the number of
unidirectional links.
We consider 100 node networks with nodes initially placed at
random in a rectangular field of dimensions 575 m x 575 m. The
field size is chosen to guarantee a connected network across the parameter
space. We use random waypoint model [4] to model node
movements. Pause time is always set to zero and the maximum
speed of the nodes is changed to change mobility.
Traffic pattern in our experiments consists of fixed number of
CBR connections (20) between randomly chosen source-destination
pairs and each connection starts at a random time at the beginning
of the simulation and stays until the end. Each CBR source sends
packets (each of size 512 bytes) at a fixed rate of 4 packets/s.
All our experiments use 500 second simulation times. In the
case of static networks, each data point in the plots is an average
of at least 50 runs with different randomly generated initial node
positions and range assignments in each run. In the mobility exper-
iments, we average over 25 randomly generated mobility scenarios
and range assignments. Identical scenarios are used across all protocol
variations.
3.4.2 Performance Metrics
We evaluate four key performance metrics: (i) Packet delivery
fraction - ratio of the data packets delivered to the destination
to those generated by the CBR sources; (ii) Average end-to-end
delay of data packets - this includes all possible delays caused
by buffering during route discovery, queuing delay at the interface,
retransmission delays at the MAC, propagation and transfer times;
(iii) Route search failures - total number of route search failure
events (see previous subsection) at sources; (iv) Normalized routing
load - the number of routing packets "transmitted" per data packet
"delivered" at the destination. Each hop-wise transmission of a
routing packet is counted as one transmission.
3.4.3 Simulation Results
We present two sets of experiments. In the first set, the network
is static and the number of unidirectional links is varied. In the
second set, node mobility is considered. Figure 8 shows the packet
delivery fraction, average delay, and the route search failures as
a function of the number of unidirectional links. We change the
fraction of low power nodes from 0 to 0.5 to increase the number
of unidirectional links. With increase in unidirectional links, basic
AODV drops the highest number of packets (as many as 20%) and
also experiences most number of route search failures (Figure 8 (a,
c)). This is because the basic AODV protocol does not take notice
of the unidirectional links and repeatedly performs route discoveries
without any benefit. Note that after every route search failure,
all packets buffered for the destination at the source are dropped.
The drop in packet delivery is less drastic for BlackListing compared
to basic AODV. But it still drops as many as 14% of the packets
because of its slowness in eliminating unidirectional links one
by one. It still has a large number of route search failures; but performs
somewhat better than basic AODV. The delay performance
of AODV and BlackListing (Figure 8 (b)) is similar as route discovery
latency dominates the delay in both cases.
Both Hello and ReversePathSearch deliver almost all packets always

Figure

8 (a)), as both are able to successfully find routes
always (Figure 8 (c)). However, their delay performance (Figure 8
(b)) is quite different. Delay for the Hello technique is similar to basic
AODV and BlackListing, while ReversePathSearch has significantly
lower delay than others. This shows that ReversePathSearch
can effectively overcome unidirectional links by exploring multiple
reverse paths. However, the delay performance of the Hello technique
is counter-intuitive. One would normally expect the performance
of Hello to be independent of unidirectional links because it
proactively eliminates unidirectional links in the background without
burdening AODV route discovery mechanism. Below we will
analyze the reason behind this unexpected behavior.
By additional instrumentation, we found that the sharp increase
in route discovery attempts with increase in unidirectional links

Figure

9 (a)) explains the delay performance of the Hello tech-
nique. What is more interesting is the reason behind the rise in
route discoveries itself. This we found was because of an undesirable
interaction of this protocol with the 802.11 MAC layer. We
noticed that in general MAC collisions increased with increase in
the number of unidirectional links. This is because of the hidden
terminal interference via unidirectional links, and the insufficiency
of the RTS-CTS handshake in 802.11 MAC to avoid such hidden
terminals (See [32] for a similar observation). For the Hello tech-
nique, however, the increase in collisions is quite dramatic (Figure
9 (c)) because of large and periodic (every second) broadcast hello
packets. Consequently, the efficiency of the MAC layer is negatively
affected resulting in more number of unsuccessful transmissions
and triggering of link failure signals to the routing protocol.
Such link failure signals cause route breaks (Figure 9 (b)). Note
that in the basic AODV protocol, every route break will result in a
new route discovery attempt. Since the Hello technique is identical
to basic AODV except for the additional hello exchanges, it does
more number of route discovery attempts as unidirectional links
grow in number. Note that basic AODV and BlackListing are not
affected very much by the above phenomenon, as they spend most
of their effort finding a route. Even though ReversePathSearch is
subject to this problem to some extent, the availability of redundant
forward paths prevents a big drop in its performance.

Figure

shows the routing load comparison for the four proto-
cols. Overall, ReversePathSearch has the lowest overhead followed
by BlackListing, basic AODV and Hello. The high overhead of the
Hello technique is expected because of the periodic hello messages.
Also, low routing overhead in ReversePathSearch indicates that the
higher per route discovery costs in ReversePathSearch due to more
route replies is very well offset by the significant reduction
in route discoveries (Figure 9(a)). Relative performance in
terms of the byte overhead (not shown) is same as above. In sum-
mary, the ReversePathSearch technique allows for a much more effective
elimination of unidirectional links from route computations
Packet
delivery
fraction
Unidirectional links
Basic AODV
BlackListing
Hello
ReversePathSearch
(a) Packet delivery fraction20601000 100 200 300 400 500 600 700
Avg.
delay
(ms)
Unidirectional links
Basic AODV
BlackListing
Hello
ReversePathSearch
(b) Average delay10305070900 100 200 300 400 500 600 700
Route
search
failures
Unidirectional links
Basic AODV
BlackListing
Hello
ReversePathSearch
(c) Route search failures

Figure

8: Performance with varying number of unidirectional links.501502503500 100 200 300 400 500 600 700
Route
discovery
attempts
Unidirectional links
Hello
ReversePathSearch
(a) Route discoveries50150250350
Route
breaks
Unidirectional links
Hello
(b) Route breaks500015000250000 100 200 300 400 500 600 700
MAC
collisions
Unidirectional links
Hello
(c) MAC collisions

Figure

9: Route discoveries, route breaks and MAC collisions for the Hello technique with varying number of unidirectional links.0.51.52.50 100 200 300 400 500 600 700
Normalized
routing
load
Unidirectional links
Basic AODV
BlackListing
Hello
ReversePathSearch
(a) Routing load

Figure

10: Routing load with varying number of unidirectional
links.
compared to BlackListing, however with much lower overhead cost
compared to Hello.
The effect of node mobility on all metrics is shown in Figure 11.
Here we vary the maximum node speed between 0 and 20 m/s. To
stress the protocols, we set the fraction of low power nodes to 0.5
which results in the most number of unidirectional links in static
networks. Mobility also affects the number and duration of unidirectional
links. But these are somewhat hard to quantify in mobile
networks. As expected, performance in terms of packet delivery,
delay and overhead degrades for all protocols with increase in mobility
observations about the relative
performance of the four protocols pretty much remain same as in
the static network case. Note that the difference in routing load
between basic AODV, BlackListing, and Hello shrinks as mobility
starts to play a dominant role. ReversePathSearch, however, continues
to perform significantly better than the rest. With the built-in
redundancy in the route discovery process, it not only eliminates
unidirectional links from the route computations by exploring alternate
reverse paths, but also, in a similar vain, avoids broken reverse
paths due to mobility (Figure 11 (c)). In addition, by computing
multiple forward paths at the source and intermediate nodes, it obviates
the need for frequent route discovery attempts in response to
route breaks caused by node mobility.
4. RELATED WORK
Although many common routing protocols assume bidirectional
links, there is still considerable amount of literature available on
routing using unidirectional links (e.g., [1, 10, 39, 31, 2]). These
protocols are mainly targeted towards two network environments,
namely, mixed satellite and terrestrial networks, and multihop wireless
networks, where unidirectional links commonly occur. Of the
several unicast routing proposals for multihop wireless networks
within the IETF MANET working group [18], only DSR [15] and
FSR [9] can fully support unidirectional links, while ZRP [12, 11]
and TORA [25] can partially support unidirectional links. There
have also been attempts to extend existing protocols to support uni-directional
links [33, 38, 16]. But none of the above efforts contain
any simulation or experimental evaluation of the impact of unidirectional
links on routing performance in realistic scenarios.
Support for unidirectional links below the network layer also received
some attention. Link-layer tunneling approach has been explored
in [7, 23]. The main motivation behind this approach is
to hide the unidirectional nature of a link from higher layer protocols
so that they can operate over unidirectional links without
any modifications. This is basically achieved by forming a reverse
tunnel (possibly via a multihop path) for each unidirectional link
using information gathered by the routing protocol. In [36], an
alternative approach to tunneling, but with a similar goal is pro-
posed. The idea here is to introduce a sub-layer beneath the net-work
layer to find and maintain multihop reverse routes for each
unidirectional link. There is also some work on using multihop
acknowledgements to discover unidirectional links [26], and GPS-based
approaches for enabling link-level acknowledgements [16]
over unidirectional links.
Work on channel access protocols for multihop wireless networks
with unidirectional links is starting to get attention [35, 3].
Ramanathan [35] makes an important observation that many uni-directional
links hurt channel access protocol performance. This
is somewhat related to our observation that utilizing unidirectional
links does not provide any significant additional benefit.
5. CONCLUSIONS
Unidirectional links commonly occur in wireless ad hoc networks
because of the differences in node transceiver capabilities
or perceived interference levels. Unidirectional links can presumably
benefit routing by providing improved network connectivity
and shorter paths. But prior work indicates that routing over uni-directional
links usually causes high overheads. With this in mind,
we evaluated performance advantages, in terms of connectivity and
path costs, of routing using unidirectional links under ideal con-
ditions. Our evaluations were done with respect to three variable
transmission range assignment models that reflect some realistic
network scenarios with unidirectional links. Main conclusion from
this study is that unidirectional links provide only incremental ben-
efit. Thus, protocols that avoid unidirectional links demand a closer
look.
Many common routing protocols, however, simply assume that
links are bidirectional. They will require some additional protocol
operations to detect and eliminate unidirectional links from
route computations. To assess the difficulty of doing this, we have
presented a case study with the AODV protocol where three such
techniques are presented and evaluated. It is observed that the Re-
versePathSearch technique performs the best because of its ability
to explore multiple paths. It exhibits a dual advantage, both in terms
of immunity from unidirectional links and from mobility-induced
link failures. While this case study has been performed only for
AODV, we expect that other protocols that share certain characteristics
with AODV, such as the on-demand nature or the distance
vector framework, will also benefit from these ideas.
Besides, our performance study also revealed that 802.11 MAC
performance degrades in the presence of unidirectional links. A
similar observation was also made in [32]. These observations suggest
the need for more efficient MAC protocols to handle unidirectional
links, as such links may be inevitable in certain ad hoc
network scenarios (for example, a network of nodes with heterogenous
powers).

Acknowledgments

This work is partially supported by NSF CAREER grant ACI-00961-
86 and NSF networking research grant ANI-0096264. Mahesh
Marina is supported by an OBR computing research award in the
ECECS department, University of Cincinnati.
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routing;asymmetric links;multihop wireless networks;ad hoc networks;on-demand routing;unidirectional links;multipath routing