I.J. Modern Education and Computer Science, 2016, 10, 25-32
Published Online October 2016 in MECS (http://www.mecs-press.org/)
DOI: 10.5815/ijmecs.2016.10.04
Copyright © 2016 MECS I.J. Modern Education and Computer Science, 2016, 10, 25-32
Modifying AODV to Reduce Load in MANETs
Gaurav Sharma
Gurukul Institute of Engineering and Technology, Kota
Email: grvsharma58@gmail.com
Manoj Singh and Prashant Sharma
Gurukul Institute of Engineering and Technology, Kota
Abstract—We propose a routing algorithm based on
AODV approach. We have modified AODV algorithm to
obtain better performance. At the same time, we have
tried to maintain the features of AODV algorithm by
maintaining a backward compatibility in our proposed
algorithm. Our algorithm tries to reduce RREQ packets
which are broadcasted in original AODV to find routing
paths. For this purpose our algorithm uses a location
aware approach to find distance to sink node. It also
makes use of busyness of nodes while selecting nodes to
participate in route discovery mechanism. Also this
scaling factor and busyness threshold can be made fixed
for each node in the network depending on size and
characteristics of the network.
Index Terms—AODV Routing Protocol, Load Balancing,
MANETs, Backward Compatibility
I. INTRODUCTION
Wireless sensor network are increasingly finding
popularity in many scientific and remote monitoring
applications related to military ecological health and
industrial processes. A wireless sensor network (WSN) is
defined in [1] as:
―A sensor network is a deployment of massive
numbers of small, inexpensive, self-powered devices that
can sense, compute, and communicate with other devices
for the purpose of gathering local information to
make global decisions about a physical environment‖
Due to certain special characteristics of the devices and
network routing in WSN has always been a challenge and
an active area of research. A related area of research is
routing methods for mobile ad-hoc networks (MANETs)
[2]. MANETs and WSN share some common features
like
Small battery operated devices as nodes
Dynamic Topology
Communication issues
Wireless Communication
Yet, MANETs are different in following aspects
Distributed operation
Autonomous nodes
Multihop Routing
Due to these differences, the routing of WSN cannot be
adopted directly for MANETs the of routing in MANETs
is to
Provide scalability – Because size of network may
vary from time to time. Limited bandwidth and
limited resources of nodes present a challenge here.
Ensure Quality of Service (QoS) in terms of high
Packet Delivery Ratio, low end to end delay, low
routing overhead etc.
Provide energy efficiency since the nodes have
limited energy.
Provide a link repair mechanism because the links
are prone to failures.
Provide dynamic route setup due to ever changing
topology and each node can play role of host and
router.
Mostly all features are provided by AODV routing
protocol [3] making it popular in MANETs.
AODV is a reactive routing protocol which involves
primitives for both route discovery and route maintenance.
Still AODV can be further improved to have better
QoS. It establishes routes as per requirement and has
enough flexibility to be adopted as per desired QoS of
applications. Lee et al in [4] address the problem of
breakage of links for a continuous data- packet delivery
and propose a Backup routing in ad hoc networks
(AODV-BR) protocol. All protocols proposed using
AODV direction were either reactive or pro-active. The
reactive protocol finds a route on demand and floods the
network with Route Request Packets (RREP). The
proactive routing protocol, on the other hand, distributes
the routing tables throughout the network to maintain
fresh lists of destinations and their routes. A variation to
both the protocols was proposed by Dargahi et al in [5]
who then brought about a combination of pro-active and
reactive dynamic routing protocol in their proposed Semi-
Proactive AODV (SP-AODV) protocol. In 2010, Jiang
and Hao [6] proposed an Improved AODV for ad hoc
network. The simulation is done through NS-2 and
optimizations in the optimized hello mechanism, local
repair mechanism and single route in AODV is done. A
different approach to routing was proposed by Nishat et
al in [7] who designed the Reverse AODV (RAODV).
This proposed approach involves the use of reverse
RREQs for finding the source node. The advantages of
26 Modifying AODV to Reduce Load in MANETs
Copyright © 2016 MECS I.J. Modern Education and Computer Science, 2016, 10, 25-32
the proposal are robust performance and reduced use of
path failure correction messages. Goswami et al [8]
analyzed the behavior of AODV and Destination
Sequence Distance Vector (DSDV) over frequent
changes node density and network topology.
Comprehensive analysis of AODV, DSDV and Dynamic
Source Routing (DSR) has been studied through
simulation in NS-2 by Mahmood et al [9]. The results
reflect that AODV might perform poorer in certain
situations; hence, there is a scope of improvement in the
basic AODV protocol. Low routing traffic overhead
makes AODV so popular. But the performance in terms
of hop routing is deteroited if the routes used in the
protocol are with high hop- count and high throughput.
Khan et al in [10] address this limitation of the AODV
protocol by modifying the route metric and the route
discovery mechanism. In2015, Qi, Wang and Jiang [11]
have proposed multipath routing protocol based on
AODV laying emphasis on node energy. The reason for
multipath routing is because it eliminates the need of the
source node to restart the route discovery process and
rather select the backup route for data transmission
directly when link is down or broken and is thus helpful.
Recent advances [12,13,14,15] in AODV assure that
there is still much to improve in the basic algorithm.
This paper suggests an improvement to AODV
protocol without incurring any routing overhead. Rather
the total number of packets floating in the network is
reduced making it overall energy efficient. The QoS
parameters for which the improvement is demonstrated
are average end to end delay and packet delivery ratio.
The experiments are performed through simulation using
NS2.
II. PROPOSED PROTOCOL
Our routing algorithm applies two changes to route
discovery process of AODV [3] to achieve better
performance than AODV.
(i) In our approach, location information is used in
route discovery process to restrict the broadcast of
Rote Request(RREQ) packets in the direction of
sink. As the location of Sink is already known to
all nodes, all the nodes which lie away from sink
nodes, compared to sender node do not broadcast
the RREQ packet thus limiting the number of
broadcast queries. For this, we have used an extra
parameter in RREQ packet called distance_val.
This distance_val is sent with RREQ packet which
is the scaled value computed from distance of
sender to sink and a dist_factor which maintains a
fixed value to increase or decrease distance based
on network characteristics. The computations of
this scaled value distance_val depends on three
parameters viz scalability_factor, distance between
sender/source & sink and dist_factor.
distance_val=(dist(s,d)–dist_factor)/ scalability_factor
where,
dist(s,d)= distance between sender (S) and destination
(D)
dist_factor= a factor to increase and decrease distance
for performance improvement
scalability_factor = a scale value of distance
depending on expected network size/width
Scalability_factor remains constant for every node in
the network.
Fig.1 Illustration of distance factor between sink and source Like
AODV, our algorithm also makes use of sequence numbers and hop
counts to avoid stale path and select a better path. Loops are also
avoided by using the same mechanism as AODV.
(ii) We have used a busyness_factor and
busyness_threshold values to check busyness of
nodes. Busyness of a node is defined as the total
packets in queue of a node divided by total limit of
packet queue in node. This helps in reducing the
packet drop rate as well as reducing the number of
RREQ request packets. Any node receiving this
RREQ packet check its packet queue and decides
whether it has to forward /process RREQ packet or
discard it, on the basis of the busyness threshold
value. In this way, already busy nodes ignore the
RREQ and do not participate in route discovery
procedure, which otherwise could result in packet
drops increasing the packet drop rate and affecting
delivery ratio.
Node busyness = (Current packets in packet queue /
total Limit of queue) *100
Both busyness_th and scalability_factor depends on
size and characteristics of the network. Busyness_th
depends on network load and sclalability_factor depends
on size of network. However, unlike scalability_factor,
busyness_th can be modified frequently based on needs
of network. For this purpose separate broadcast control
packets can be used. These values can also be predefined
in the nodes.
Pseudocode of Proposed Protocol
The modified algorithms in our approach over AODV
[3] are given below.
Modifying AODV to Reduce Load in MANETs 27
Copyright © 2016 MECS I.J. Modern Education and Computer Science, 2016, 10, 25-32
Algorithm: ROUTE REQUEST()
If Node has data to send
1. Check Route Table for next hop entry to destination
a. If No route entry found or route expired
i. Prepare RREQ packet and fill entries
ii. Compute distance_val and add it in RREQ
header
distance_val = (dist(s,d) – dist_factor) /
scalability_factor
iii. Broadcast the RREQ packet
b. If route entry is found, Send Data packet to next
hop entry in route table.
c.
Algorithm: RECV REQUEST()
If a Node Receives a RREQ
1. Check the packet
a. If it a destination node update route table entries,
send Route Reply (RREP) (unicast) to source
node through next hop node in route table.
b. If it has a route available to destination node
then update route table entries, send RREP
(unicast) to source node through next hop node
in route table.
c. If it’s not destination node and have no current
entries in route table
i. Check the distance_val in packet.
ii. Compute scaled value of distance(node,sink).
iii. If (distance_val(packet) <
distance(node,sink)), discard the RREQ
packet.
iv. Else check node busyness factor
1. If (node busyness > busyness_th) discard
the RREQ packet
2. Else
a. Compute new distance_val and
b. Update distance_val in RREQ packet
and
c. Broadcast the packet.
III. ASSUMPTIONS OF THE PROPOSED SCHEME
The assumptions of our proposed routing algorithm are
as follows:
(a) Node Deployment:- Nodes are assumed to be
mobile and are deployed randomly in the network
area. The sensor nodes are equipped with GPS
devices to provide location information.
(b) Sink Nodes:- Multiple mobile sink nodes in the
network that follows a pre-planned path and
schedule known to all the nodes in the network.
(c) Location Awareness: - Each node can find out its
own location in the network using GPS technology.
With location information, RREQ packets are
directed towards the direction of sink nodes
limiting the number of RREQ packets and
increasing performance of proposed algorithm.
(d) Node Mobility: - Node mobility makes the
performance of routing dependent on a variety of
random factors or simply unpredictable at times.
In our routing, we assume mobile nodes having
motion with randomly varying speed in any
direction constrained by maximum speed possible.
Sink nodes are also mobile. However, they are
supposed to follow a pre-planned motion path &
schedule such that even if any sink deviates from
its path it can regain the path and schedule by
itself. Also, a little deviation in sink will not affect
the performance of the proposed algorithm.
(e) Node Design: - Communication in MANETs is
achieved in hop by hop fashion using wireless
signals, so each sensor node is equipped with
proper devices for carrying out signalling and
communications. Sensor nodes have omni-
directional modems & antennas to transmit and
receive packets. Our routing algorithm supposes
that all nodes have good storage, high speed
processors, intelligent processing routines and
batteries for providing power.
IV. SIMULATION RESULTS
The simulations were done on the NS-2.The simulation
parameters used for simulation of the protocols are listed
in Table 1.
Table 1. Simulation Parameters And Values
SIMULATION SETTING
VALUE
Node Deployment Area
1000 x 1000 sq metres
Node Deployment Type
Random deployment ( Mobile
Nodes)
Node Motion
Max 10 m/sec (random in
each direction )
Transmission Range
250 metres
Size of Data Packet
512 bytes
Packet generation rate
2-5 packets/second
Initial Energy Value
200 Joule
scalability_factor
500( depends on network
size)
busyness_th
85 percent
Connections
60 random connections from
any node to sink each for
duration of 20 seconds
Total Sink
3
Total Simulation time
100 seconds.
There are 3 destination nodes referred to as sink nodes
which are considered to move in a pre-planned path. The
sinks pre-planned motion schedule is known to each of the
sensor nodes in the network. Packet dropping scenarios
and working of other messages (like hello, ack, error etc)
are assumed to be just like original AODV routing.
Given below are the three screenshots showing the
28 Modifying AODV to Reduce Load in MANETs
Copyright © 2016 MECS I.J. Modern Education and Computer Science, 2016, 10, 25-32
simulation of the proposed algorithm. Fig. 2 shows the
scenario of 30 nodes with node 4 as the source and three
differently colored nodes as the sinks.
Fig.3 shows how the source node multicasts request
packets to its neighborhood nodes. Since node 16 does
not satisfy the criteria of the proposed algorithm, the
route requests are sent to the remainig nodes 13, 23, 8 and
9 falling in the transmission range as shown.
Fig. 4 shows that at a later working stage, the nodes
that lie close to the sink nodes are more active than the
remaining as observed through the movement of nodes
8,9,13 and 23 as compared to node 16.
Fig.2. Simulation Screenshot 1
Fig.3. Simulation Screenshot 2
Modifying AODV to Reduce Load in MANETs 29
Copyright © 2016 MECS I.J. Modern Education and Computer Science, 2016, 10, 25-32
Fig.4 Simulation Screenshot 3
A. Performance Metrics
In our simulations, we evaluate the performance of our
proposed routing algorithm with respect to the number of
nodes in the network.
The following performance metrics were evaluated for
our proposed routing protocol.
End-to-End Delay
Number of hops
Packet Delivery Ratio
Throughput
Total Energy Consumed
B. Performance Evaluation through Results
Fig.5. Growth of Average end-to-end delay with number of nodes
Simulation results for average end to end delay of
proposed routing algorithm and AODV [3] are presented
in form of graph in Fig. 5. The end-to-end delay recorded
for AODV is always higher than the proposed protocol.
The reduction in end-to-end delay indicates faster delivery
of packets. With increasing number of nodes, the delay
increases because of increased traffic and larger distance
(hops) between source and destination. Growth with
increasing nodes is similar for both AODV and the
proposed protocol implying that the proposal retains
characteristics of AODV.
Average hop count or total hops required to deliver
packets from source to destinations can also be used to
observe the delay caused by a routing protocol. More hops
means larger delay. The proposed protocol has an overall
lesser loop count than AODV. Fig. 6 shows the growth in
total hops with increasing number of nodes for both
AODV and the proposal. The proposed method effectively
reduces the average hop count and total hops.
Fig.6. Growth of Total hops with number of nodes
Packet Delivery Ratio (PDR) is a metric which informs
about how many packets are actually delivered to the sink.
It reveals the useful proportion of total traffic in the
network. PDR is already very high for AODV. Fig. 7
shows variation in PDR when number of nodes is
increased. There is not much to drop. The proposed
protocol also follows the PDR curve of AODV, while