Location-Aided Routing (LAR) in Mobile Ad Hoc Networks
Young-Bae Ko and Nitin H. Vaidya
Department of Computer Science
Texas A&M University
College Station, TX 77843-3112
f
youngbae,vaidya
g
@cs.tamu.edu
Abstract
A mobile ad hoc network consists of wireless hosts that may move
often. Movement of hosts results in a change in routes, requiring
some mechanism for determining new routes. Several routing pro-
tocols have already been proposedfor ad hoc networks. This paper
suggests an approach to utilize location information (for instance,
obtained using the global positioning system) to improve perfor-
mance of routing protocols for ad hoc networks.
By using location information, the proposed Location-Aided
Routing (LAR) protocols limit the searchfor anew route to a smaller
“request zone” of the ad hoc network. This results in a significant
reduction in the number of routing messages. We present two al-
gorithms to determine the request zone, and also suggest potential
optimizations to our algorithms.
1 Introduction
Mobile ad hoc networks consist of wireless mobile hosts that com-
municate with each other, in the absence of a fixed infrastructure.
1
Routesbetweentwo hostsin a Mobile Ad hoc NETwork (MANET)
may consist of hops through other hosts in the network [7]. Host
mobility can causefrequent unpredictabletopologychanges. There-
fore, the task of finding and maintaining routes in MANET is non-
trivial. Many protocols have been proposed for mobile ad hoc net-
works, with the goal of achieving efficient routing [6, 9, 11, 12, 14,
16, 17, 18, 21, 23, 24, 28]. These algorithms differ in the approach
used for searching a new route and/or modifying a known route,
when hosts move.
In this paper, we suggest an approach to decrease overhead of
route discovery by utilizing location information for mobile hosts.
Such location information may be obtained using the global posi-
tioning system (GPS) [10, 22]. We demonstrate how location in-
formation may be used by means of two Location-Aided Routing
(LAR) protocols for route discovery. The LAR protocols use loca-
tion information (which may be out of date, by the time it is used)
to reduce the search space for a desired route. Limiting the search
space results in fewer route discovery messages.
Research reported is supported in part by Texas Advanced Technology Program
grants010115-248and 009741-052-C.
1
We will use the terms host and node interchangeably.
2 Related Work
Design of routing protocols is a crucial problem in mobile ad hoc
networks [7, 25], and several routing algorithms have been devel-
oped (e.g., [6, 9, 11, 12, 14, 16, 17, 18, 21, 23, 24, 28]). One desir-
able qualitative property of a routing protocol is that it shouldadapt
to the traffic patterns [8]. Johnsonand Maltz [15, 16] point out that
conventionalrouting protocols are insufficient for ad hoc networks,
since the amount of routing related traffic may waste a large por-
tion of the wireless bandwidth, especially for protocols that use
periodic updates of routing tables. They proposed using Dynamic
Source Routing (DSR), which is based on on-demand route dis-
covery. A number of protocol optimizations are also proposed
to reduce the route discovery overhead. Perkins and Royer [23]
present the AODV (Ad hoc On Demand Distance vector routing)
protocol that also uses a demand-driven route establishment pro-
cedure. More recent TORA (Temporally-Ordered Routing Algo-
rithm) [21] is designedto minimize reaction to topologicalchanges
by localizing routing-related messages to a small set of nodes near
the change. Hass and Pearlman [12] attempt to combine proactive
and reactive approaches in the Zone Routing Protocol (ZRP), by
initiating route discovery phase on-demand, but limits the scope
of the proactive procedure only to the initiator’s local neighbor-
hood. Also, ZRP limits topology update propagation to the neigh-
borhood of the change. There is a recent approach for compara-
tive performance evaluation of several routing protocols proposed
in MANET [26].
The existing MANET routing algorithms do not take into ac-
count the physical location of a destination node. In this paper, we
propose two algorithms to reduce route discovery overhead using
location information. Similar ideas have been applied to develop
selective paging for cellular PCS (Personal Communication Ser-
vice) networks [4]. In selective paging, the systempages a selected
subset of cells close to the last reported location of a mobile host.
This allows the location tracking cost to be decreased. We propose
and evaluate an analogous approach for routing in MANET. Met-
ricom is a packet radio system using location information for the
routing purpose [19]. The Metricom network infrastructure con-
sists of fixed base stations whose precise location is determined
using a GPS receiver at the time of installation. Metricom uses
a geographically based routing scheme to deliver packets between
base stations. Thus, a packet is forwarded one hop closer to its final
destination by comparing the location of packet’s destination with
the location of the node currently holding the packet. In a survey
of potential applications of GPS, Dommety and Jain [10] briefly
suggest use of location information in ad hoc networks, though
they do not elaborate on how the information may be used. Other
researchers have also suggested that location information should
be used to improve (qualitatively or quantitatively) performance of
a mobile computing system [27, 29]. A routing and addressing
method to integrate the concept of physical location (geographic
coordinates), into the current design of the Internet, has been inves-
tigated in [13, 20].
3 Location-Aided Routing(LAR) Proto cols
3.1 Route Discovery Using Floo ding
In this paper, we explore the possibility of using location infor-
mation to improve performance of routing protocols for MANET.
As illustration, we show how a route discovery protocol based on
flooding can be improved. The route discovery algorithm using
flooding is described next (this algorithm is similar to Dynamic
Source Routing [15, 16]). When a node S needs to find a route
to node D, node S broadcasts a route request message to all its
neighbors
2
– hereafter, node S will be referred to as the sender and
node D as the destination. A node, say X, on receiving a route re-
quest message,compares the desired destination with its own iden-
tifier. If there is a match, it means that the request is for a route
to itself (i.e., node X). Otherwise, nodeX broadcasts the request to
its neighbors – to avoid redundant transmissions of route requests,
a node X only broadcasts a particular route request once (repeated
reception of a route request is detected using sequence numbers).
Figure 1 illustrates this algorithm. In this figure, node S needs to
determine a route to node D. Therefore, node S broadcasts a route
request to its neighbors. When nodes B and C receive the route re-
quest, they forward it to all their neighbors. When node X receives
the route request from B, it forwards the request to its neighbors.
However, when node X receives the same route request from C,
node X simply discards the route request.
C
B
S
A
X
D
E
route request
Figure 1: Illustration of flooding
As the route requestis propagatedtovariousnodes,the pathfol-
lowed by the request is included in the route request packet. Using
the above flooding algorithm, provided that the intended destina-
tion is reachable from the sender, the destination should eventually
receive a route request message. On receiving the route request,
the destination responds by sending a route reply message to the
sender – the route reply message follows a path that is obtained by
reversing the path followed by the route request received by D (the
route request message includes the path traversed by the request).
It is possiblethat the destination will not receive a route request
message (for instance, when it is unreachable from the sender, or
route requests are lost due to transmission errors). In such cases,
the senderneeds to be able to re-initiate route discovery. Therefore,
when a sender initiates route discovery, it sets a timeout. If during
the timeout interval, a route reply is not received, then a new route
discovery is initiated (the route request messages for this route dis-
covery will usea different sequencenumberthanthe previous route
discovery – recall that sequence numbers are useful to detect mul-
tiple receptions of the same route request). Timeout may occur if
the destinationdoes not receive a route request, or if the route reply
message from the destination is lost.
2
Two nodes are said to be neighborsif they can communicatewith each other over
a wireless link.
Route discovery is initiated either when the sender S detects
that a previously determined route to node D is broken,or if S does
not know a route to the destination. In our implementation, we
assume that node S can know that the route is broken only if it at-
tempts to use the route. When node S sends a data packet along a
particular route, a node along that path returns a route error mes-
sage, if the next hop on the route is broken. When node S receives
the route error message, it initiates route discovery for destination
D.
When using the above algorithm, observe that the route request
would reach every node that is reachable from node S (potentially,
all nodes in the ad hoc network). Using location information, we
attempt to reduce the number of nodes to whom route request is
propagated.
Dynamic source routing (DSR) [15, 16] and ad hoc on-demand
distance vectorrouting (AODV) [23]protocolsproposedpreviously
are both based on variations of flooding. DSR and AODV also use
some optimizations - several of these optimizations as well as other
optimizations suggested in this paper can be used in conjunction
with the proposed algorithms. However, for simplicity, we limit
our discussion to the basic flooding algorithm, and location-aided
route discovery based on “limited” flooding.
3.2 Preliminaries
Location Information
The proposed approach is termed Location-Aided Routing (LAR),
as it makes use of location information to reducerouting overhead.
Location information usedin the LAR protocol may be provided by
the Global Positioning System (GPS) [2, 3, 10, 22]. With the avail-
ability of GPS, it is possible for a mobile host to know its phys-
ical location
3
. In reality, position information provided by GPS
includes some amount of error, which is the difference between
GPS-calculated coordinates and the real coordinates. For instance,
NAVSTAR Global Positioning System has positional accuracy of
about 50-100 meters and Differential GPS offers accuracies of a
few meters [2, 3]. In our initial discussion, we assume that each
host knows its current location precisely (i.e., no error). However,
the ideas suggested here can also be applied when the location is
known only approximately – the Performance Evaluation section
considers this possibility.
In this paper, we assume that the mobile nodes are moving in a
two-dimensional plane.
Expected Zone and Request Zone
Expected Zone:
Consider a node S that needs to find a route
to node D. Assume that node S knows that node D was at location
L at time
t
0
, and that the current time is
t
1
. Then, the “expected
zone” of node D, from the viewpoint of node S at time
t
1
,isthe
region that node S expects to contain node D at time
t
1
. Node S
can determine the expected zone based on the knowledge that node
D was at location L at time
t
0
. For instance, if node S knows that
node D travels with average speed
v
, then S may assume that the
expected zone is the circular region of radius
v
(
t
1
,
t
0
)
, centered
at location L (see Figure 2(a)). If actual speed happens to be larger
than the average, then the destination may actually be outside the
expected zone at time
t
1
. Thus, expected zone is only an estimate
made by node S to determine a region that potentially contains D
at time
t
1
.
If node S does not know a previous location of node D, then
node S cannot reasonably determine the expected zone – in this
case, the entire region that may potentially be occupied by the ad
3
Current GPS provides accurate three-dimensional position (latitude, longi-
tude, and altitude), velocity, and precise time traceable to Coordinated Universal
Time(UTC) [1]
hoc network is assumed to be the expected zone. In this case, our
algorithm reduces to the basic flooding algorithm. In general, hav-
ing more information regarding mobility of a destination node, can
result in a smaller expected zone. For instance, if S knows that
destination D is moving north, then the circular expected zone in
Figure 2(a) can be reduced to a semi-circle, as in Figure 2(b).
(b)
L
L
v (t1 - t0)
(a)
Figure 2: Examples of expected zone
Request Zone:
Again, consider node S that needs to determine
a route to node D. The proposed LAR algorithms use floodingwith
one modification. Node S defines(implicitly or explicitly) a request
zone for the route request. A node forwards a route request only
if it belongs to the request zone (unlike the flooding algorithm in
Section 3.1). To increase the probability that the route request will
reach node D, the request zone should include the expected zone
(described above). Additionally, the request zone may also include
other regions around the request zone. There are two reasons for
this:
Whenthe expected zone does not include hostS, a path from
host S to host D must include hosts outside the expected
zone. Therefore, additional region must be included in the
requestzone, so that S and D both belong to the request zone
(for instance, as shown in Figure 3(a)).
The request zone in Figure 3(a) includes the expected zone
from Figure 2(a). Is this an adequate requestzone? In theex-
ample in Figure 3(b), all paths from S to D include hosts that
are outside the request zone. Thus, there is no guarantee that
a path can be found consisting only of the hosts in a chosen
request zone. Therefore, if a route is not discovered within
a suitable timeout period, our protocol allows S to initiate a
new route discovery with an expanded request zone – in our
simulations, the expanded zone includes the entire network
space. In this event, however, the latency in determining the
route to D will be longer (as more than one round of route
request propagation will be needed).
Note that the probability of finding a path (in the first at-
tempt) can be increased by increasing the size of the initial
request zone (for instance, see Figure 3(c)). However, route
discovery overheadalso increases with the size of the request
zone. Thus, there exists a trade-off between latency of route
determination and the message overhead.
3.3 Determining Membership of Request Zones
As noted above, our LAR algorithms are essentially identical to
flooding, with the modification that a nodethat is not in the request
zone does not forward a route request to its neighbors.
4
Thus, im-
4
Recall that, in the flooding algorithm,a node forwardsa route request if it has not
received the request before and it is not the intended destination.
S
D
S
D
S
D
(a)
Request Zone
Request Zone
(b) (c)
Larger Request Zone
Figure 3: Request zone: An edge between two nodes means that
they are neighbors
plementing LAR algorithm requires that a node be able to deter-
mine if it is in the request zone for a particular route request – the
two LAR algorithms presented here differ in the manner in which
this determination is made.
LAR Scheme 1
Our first schemeuses a requestzone that is rectangularin shape(re-
fer to Figure 4). Assume that node S knows that node D was at lo-
cation
(
X
d
;Y
d
)
at time
t
0
. At time
t
1
, node S initiates a new route
discovery for destination D. We assume that node S also knows the
average speed
v
with which D can move. Using this, node S defines
the expected zone at time
t
1
to be the circle of radius R=v(
t
1
,
t
0
)
centered at location (
X
d
,
Y
d
).
In our first LAR algorithm, we definethe request zone to be the
smallest rectangle that includes current location of S and the ex-
pected zone (the circular region defined above), such that the sides
of the rectangle are parallel to the X and Y axes. In Figure 4(a),
the request zone is the rectangle whose corners are S, A, B and C,
whereas in Figure 4(b), the rectangle has corners at points A, B,
C and G – note that, in this figure, current location of node S is
denoted as
(
X
s
;Y
s
)
.
The source node S can thus determine the four corners of the
expected zone. S includes their coordinates with the route request
message transmitted when initiating route discovery. When a node
receives a route request, it discards the request if the node is not
within the rectangle specified by the four corners included in the
route request. For instance, in Figure 4(a), if node I receives the
route request from another node, node I forwards the request to
its neighbors, because I determines that it is within the rectangular
request zone. However, when node J receives the route request,
node J discards the request, as node J is not within the request zone
(see Figure 4(a)).
When node D receives the route request message, it replies by
sendinga route reply message (as in the flooding algorithm). How-
ever, in case of LAR, node D includes its current location and cur-
rent time in the route reply message. When node S receives this
route reply message (ending its route discovery), it records the lo-
cation of node D. Node S can use this information to determine the
request zone for a future route discovery. (It is also possible for
D to include its current speed, or average speed over a recent time
interval, with the route reply message. This information could be
used in a future route discovery. In our simulations, we assume that
all nodes know each other’s average speed.)
Size of the request zone:
Note that the size of the rectangular
request zone above is proportional to (i) average speed of move-
ment
v
, and (ii) time elapsed since the last known location of the
destination was recorded. In our implementation, the sender comes
to know location of the destination only at the end of a route dis-
covery (as noted in the previous paragraph). At low speeds, route
discoveries occur after long intervals, becauseroutes break less of-
ten (thus,
t
1
,
t
0
is large). So, although factor (i) above is small,
factor (ii) becomes large at low speeds, potentially resulting in a
larger request zone. At high speeds as well, for similar reasons, a
large request zone may be observed. So, in general, a smaller re-
quest zone may occur at speeds that are neither too small, nor too
large. For low speeds, it is possible to reduce the size of the request
zone by piggybackingthe location information on other packets,in
addition to route replies (this optimization is not evaluated here).
P (Xd, Yd+R)
Q (Xd+R, Yd)
S (Xs, Ys)
I (Xi, Yi)
C (Xd+R, Ys)
A (Xs, Yd+R)
J (Xj, Yj)
R
Request Zone
Expected Zone
B (Xd+R, Yd+R)
Network Space
(Xd, Yd)
(a) Source node outside the Expected Zone
P (Xd, Yd+R)
Q (Xd+R, Yd)U (Xd-R, Yd)
S (Xs, Ys)
R
T (Xd, Yd-R)
Expected Zone
Request Zone
Network Space
A (Xd-R, Yd+R)
G (Xd-R, Yd-R) C (Xd+R, Yd-R)
B (Xd+R, Yd+R)
(Xd, Yd)
(b) Source node within the Expected Zone
Figure 4: LAR scheme 1
LAR Scheme 2
In LAR scheme 1, source S explicitly specifies the request zone in
its route request message. In scheme 2, node S includes two pieces
of information with its route request:
Assume that node S knows the location
(
X
d
;Y
d
)
of node
D at some time
t
0
– the time at which route discovery is
initiated by node S is
t
1
,where
t
1
t
0
. Node S calculates
its distance from location
(
X
d
;Y
d
)
, denoted as
DI S T
s
,and
includes this distance with the route request message.
The coordinates
(
X
d
;Y
d
)
are also included with the route
request.
When a node I receives the route request from sender node S, node
I calculatesits distance from location
(
X
d
;Y
d
)
, denotedas
DI S T
i
,
and:
For some parameter
,if
DI S T
s
+
DI S T
i
, then node I
forwards the request to its neighbors. When node I forwards
the route request, it now includes
DI S T
i
and
(
X
d
;Y
d
)
in
the route request (i.e., it replaces the
DI S T
s
value received
in the route request by
DI S T
i
, before forwarding the route
request).
Else
DI S T
s
+
<DIST
i
. In this case, node I discards the
route request.
When some node J receives the route request (originated by
node S) from node I, it applies a criteria similar to above: If node
J has received this request previously, it discards the request. Oth-
erwise, node J calculates its distance from
(
X
d
;Y
d
)
, denoted as
DI S T
j
.Now,
The route requestreceivedfromI includes
DI S T
i
.If
DI S T
i
+
DI S T
j
, then node J forwards the request to its neigh-
bors (unless node J is the destination for the route request).
Before forwarding the request, J replaces the
DI S T
i
value
in the route request by
DI S T
j
.
Else
DI S T
i
+
<DIST
j
. In this case, node J discards the
request.
Thus, a node J forwards a route request forwarded by I (originated
by node S), if J is “at most
farther” from
(
X
d
;Y
d
)
than node I.
For the purpose of performance evaluation, we use
=0
in the
next section. Non-zero
may be used to trade-off the probability
of finding a route on the first attempt with the cost of finding the
route. Non-zero
may also be appropriate when location error is
non-zero, or when the hosts are likely to move significantdistances
during the time required to perform route discovery.
Figure 5 illustrates the difference between the two LAR schemes.
Consider Figure 5(a) for LAR scheme 1: When nodes I and K re-
ceive the route request for node D (originated by node S), they for-
ward the route request, as both I and K are within the rectangular
request zone. On the other hand, when node N receives the route
request, it discards the request, as N is outside the rectangular re-
quest zone. Now consider Figure 5(b) for LAR scheme 2 (assume
=0
): When nodes N and I receive the route request from node
S, both forward the route request to their neighbors, because N and
I are both closer to
(
X
d
;Y
d
)
than node S. When node K receives
the route request from node I, node K discards the route request, as
K is farther from
(
X
d
;Y
d
)
than node I. Observe that nodes N and
K take different actions when using the two LAR schemes.
Error in Lo cation Estimate
In the above, we assume that each node knows its own location
accurately. However, in reality there may be some error in the esti-
mated location. Let
e
denote the maximum error in the coordinates
estimated by a node. Thus, if a node N believes that it is at location
(
X
n
;Y
n
)
, then the actual location of node N may be anywhere in
the circle of radius
e
centered at
(
X
n
;Y
n
)
.
In the next section, we will refer to
e
as location error.Inthe
above LAR schemes, we assume that node S obtained the location
(
X
d
;Y
d
)
of node D at time
t
0
, from node D (perhaps in the route
reply message during the previous route discovery). Thus, node S
does not know the actual location of node D at time
t
0
– the actual
location is somewherein the circle of radius
e
centered at
(
X
d
;Y
d
)
.
To take the location error
e
into account,we modify LARscheme
1 so that the expected zone is now a circle of radius
e
+
v
(
t
1
,
t
0
)
.
The request zone may now be bigger, as it must include the larger
request zone. Apart from this, no other change is needed in the
algorithm. As the request zone size increases with
e
, the routing
overhead may be larger for large
e
. We make no modifications to
LAR scheme 2, even when location error
e
is non-zero. However,
the performance of scheme 2 may degrade with large location er-
ror, because with larger
e
, there is a higher chance that the request
zone used by the scheme will not include a path to the destination
(resulting in a timeout and another route discovery). We briefly
evaluate the case of
e>
0
at the end of the next section.
Expected Zone
R
S (Xs, Ys)
I
K
Request Zone
Network Space
N
(Xd, Yd)
(a) LAR scheme 1
DISTs
S (Xs, Ys)
K
I
Network Space
DISTk
(Xd, Yd)
DISTi
DISTn
N
(b) LAR scheme 2
Figure 5: Comparison of the two LAR schemes
4 Performance Evaluation
To evaluateour schemes,we performed simulations using modified
version of a network simulator, MaRS (Maryland Routing Simula-
tor) [5]. MaRS is a discrete-event simulator built to provide a flex-
ible platform for the evaluation and comparison of network rout-
ing algorithms. Three routing protocols were simulated – flooding,
LAR scheme 1 and LAR scheme 2. We studied several cases by
varying the numberof nodes, transmission range of eachnode, and
moving speed.
4.1 Simulation Model
Number of nodes in the network was chosen to be 15, 30 and 50
for different simulation runs. The nodes in the ad hoc network are
confined to a 1000 unit x 1000 unit square region. Initial locations
(X and Y coordinates) of the nodes are obtained using a uniform
distribution.
We assumethateach node movescontinuously,without pausing
at any location. Each node moves with an average speed
v
.The
actual speed is uniformly distributed in the range
v
,
and
v
+
units/second, where, we use
=1
:
5
when
v<
10
and
=2
:
5
when
v
10
. We consider average speeds (
v
) in the range 1.5 to
32.5 units/sec.
Each node makes several “moves” during the simulation. A
node does not pausebetween moves. During a given move, a node
travels distance
d
,where
d
is exponentially distributed with mean
20 units. The direction of movement for a given move is chosen
randomly. For each such move, for a given average speed
v
,the
actual speed of movement is chosen uniformly distributed between
[
v
,
; v
+
]
. If during a move (over chosen distance
d
), a node
“hits” a wall of the 1000x1000 region, the node bounces and con-
tinues to move after reflection, for the remaining portion of distance
d
.
Two mobile hosts are considered disconnected if they are out-
side each other’s transmission range. All nodes have the same
transmission range. For the simulations, transmission range val-
ues of 200, 300, 400, and 500 units were used. All wireless links
have the same bandwidth, 100 Kbytes per second.
In our simulation, simulation time is inversely proportional to
the average speed. For instance, simulations for average speed 1.5
units/sec run 4000 seconds of execution, whereas about 1333 sec-
onds for average speed 4.5 units/sec. As the average speed is in-
creased, for a given simulation time, the number of moves simu-
lated increases. Thus, although the simulations at different speeds
are for the same mobility model, as speed is increased, a particular
configuration (for instance, partition) that may not have occurred
at a lower speed can occur at the higher speed. On the other hand,
a configuration that did occur at a lower speed lasts a shorter time
when the speed is higher.
For the simulation, a sender and a destination are chosen ran-
domly. Any data packetsthat cannot be delivered to the destination
due to a broken route are simply dropped. The source generates 10
data packets per second (on average), with the time between two
packets being exponentially distributed. The data rate was chosen
low to speed up the simulation. However, this has the impact of
sendingsmall number of packetsbetweentwo route discoveries (as
compared to when the source continuously sends packets). This,
in turn, results in higher number of routing packets per data packet
(defined below).
When using the LAR schemes for route discovery, the sender
first uses our algorithm to determine a route – if a route reply is
not received within a timeout interval, the sender uses the flooding
algorithm to find the route. The timeout interval is 2 seconds on
average.
In our simulations, we do not model the delays that may be in-
troduced when multiple nodes attempt to transmit simultaneously.
Transmission errors are also not considered.