Improved aodv based on energy strength and dropping ratio

International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS)
Volume VI, Issue IV, April 2017 | ISSN 2278-2540
www.ijltemas.in Page 104
Improved AODV Based on Energy Strength and
Dropping Ratio
Ganga S, Binu Chandran R
Department of Computer Science, Mohandas College of Engineering & Technology, Anad, Thivanamthuparam
Abstract—Wireless Sensor Networks are the latest trends in the
market due to the demand for communication and networking
among the wireless network devices. The routing protocols are
used in the Wireless Sensor Networks for efficient
communication of data between sensor nodes. The designs of
routing protocols in Wireless Sensor Networks are very concern
because they are influenced by many challenging factors. To
design the networks, the factors needed to be considered are the
coverage area, mobility, energy power consumption,
communication capabilities etc.. Broadcasting is an inevitable
operation in the route discovery phase of AODV protocol. A
probability based AODV is proposed, it uses nodes remaining
energy and threshold random delay to generate the
rebroadcasting of route request packet. The route request packet
of AODV is modified to gather nodes remaining energy strength.
The performance of probability based AODV is compared with
AODV over packet delivery fraction, normalized routing
overhead, delay and average acquisition latency.
NS-2 based simulator is used to evaluate the performance of
routing protocol.
Keywords: AODV(Ad-hoc on demand vector), WSN(wireless
sensor networks), RREQ(route request)
I. INTRODUCTION
ireless Sensor Networks have emerged as an important
new area in wireless technology. A wireless network
consisting of tiny devices which senses and monitor physical
or environmental conditions such as temperature, pressure,
motion or pollutants etc...when placed at different areas, They
are self-organize and are connected with each other through
wireless links .These nodes communicate with each other
through multihop communication.
Features of sensor networks are self-organizing
capabilities, dynamic network topology, limited power, node
failures and mobility of nodes, short-range broadcast
communication and multi-hop routing, and large scale of
deployment. The strength of wireless sensor network lies in
their flexibility and scalability. They also deployed in an ad-
hoc fashion in remote location without the need of any
existing infrastructure.
The basic issues of WSN like, sensing range, placement or
deployment pattern, computational power, memory, battery
power and the transmission capacities, the energy
consumption by a node is a critical aspect, in order to increase
the network life time [4]. In WSN, a sensor node may
simultaneously sense, process and transmit data. In most cases
it is very difficult to recharge or change the battery as it is
having finite energy. Sensor nodes are useless when the
batteries are drained. Thus, it is critical and challenging to
design long lived WSN with the energy constraints.
Routing protocols are a key feature of any network. They
enable each node to learn about the other nodes in order to
find a link to their destination. Because some nodes could be
mobile in wireless sensor networks (WSNs), routes between
nodes change very often. Therefore, it is not possible to
establish fixed paths and infrastructure between nodes.
Routing in sensor networks is very challenging due to several
characteristics that distinguish them from communication and
wireless networks [2].
The routing protocols for Wireless networks have
been classified into two categories [2]: table-driven protocols
and on-demand protocols. They differ from each other on the
way they obtain the routing information. The table driven
protocols usually maintain the routing table of the whole
network whereas the on-demand protocols only try to keep
routes whenever it is required. A third category hybrid
protocols, is also there which combines both table driven and
on-demand protocol.
II. LITERATURE SURVEY
Different broadcasting protocols are designed in
order to minimize the number of rebroadcast packets. In
Paper[8], AODV is essentially a combination of both DSR
and DSDV. It is works on on-demand mechanism of Route
Discovery and Route Maintenance from DSR, plus the use of
hop-by-hop routing , sequence numbers, and periodic beacons
from DSDV.
In Counter-based broadcasting (CB) [7] protocol
predefines a relay counter threshold (CH). After receiving a
rebroadcast packet first time, the node initiates a counter C =
1 and sets a random relay delay (RRD), 0<RRD<Tmax. Before
the RRD expires, the node increases C by one whenever it
receives a redundant packet. When the RRD expires, the node
would drop this packet if C CH. Otherwise, the packet is
W

relayed. The performance of counter-based protocol mainly
depends on the selection of CH.
W. Peng et al. [9] and Lim et al. has proposed two
different neighbor-knowledge-based approaches. These
approaches require mobile hosts to periodically exchange
HELLO messages between neighbors. Neighbor-knowledge-
based approaches make rebroadcast decisions based on the
available neighborhood information. Therefore, the number of
rebroadcasts may be near optimal but HELLO messages
themselves consume channel bandwidth.
Ni et al. [7] also discussed area-based algorithms, distance-
based and location-based approaches. Area based algorithms
require support from GPS or other location devices. In
distance-based approach, a mobile node rebroadcast the
received broadcast packet only if the distance between this
node and the neighbor node is more than a threshold value.
The dynamically probability calculating
protocols[10,9,12] are also proposed because predefined
probability protocols[13] are not able to deliver better results.
These predefined probability base protocols are not able to
serve in all scenarios of network as dense and sparse network
topology.
Here, an approach is proposed that combines the advantages
of probabilistic and packet energy to dynamically generate
rebroadcast probability to yield higher throughput, better
reach ability, and lower latency.
III. AODV
Ad-hoc On-demand distance vector (AODV) discovers
routes whenever it is needed by route discovery process using
traditional routing tables; one entry per destination. AODV
uses a broadcast route discovery algorithm and then the
unicast route reply massage for finding the route[5].
Route Discovery: When a node wants to send a packet to
some destination node and does not have a valid route in its
routing table for that destination, it initiates a route discovery
process. Source node broadcasts a route request (RREQ)
packet to its Neighbours, which then forwards the request to
their neighbours and so on. Nodes generates a Route Request
with destination address, Sequence number and Broadcast ID
and sent it to his neighbour nodes. . Each node receiving the
route request sends a route back (Forward Path) to the node.
Route Reply: When the RREQ is received by a node that is
either the destination node or an intermediate node with a
fresh enough route to the destination, it replies by unicasting
the route reply (RREP) towards the source node. As the RREP
is routed back along the reverse path, intermediate nodes
along this path set up forward path entries to the destination in
its route table and when the RREP reaches the source node, a
route from source to the destination established.
Route Maintenance: A route established between source
and destination pair is maintained as long as needed by the
source. When a link break in an active route is detected, the
broken link is invalid and a RERR message is sent to other
nodes. These nodes in turn propagate the RERR to their
precursor nodes, and so on until the source node is reached.
The affected source node may then choose to either stop
sending data or reinitiate route discovery for that destination
by sending out a new RREQ message.
Fig 1. AODV route discovery process
IV.PROBABILITY BASED AODV
Probability based Broadcasting technique for routing
protocol is proposed to trim down flooding problem. It uses
node s remaining energy strength and threshold random delay
to generate rebroadcast probability dynamically for the
efficient broadcasting in route discovery. This technique is
analyzed over reactive Adhoc On-Demand Distance Vector
(AODV) protocol. The route request (RREQ) packet of
AODV is modified to gather energy information of nodes.
The performance of modified protocol is analyzed over
broadcast packets sent and End-to-End Delay using ns2
simulator.
The objective of the Probability based Broadcasting
technique is to find an efficient probabilistic based
broadcasting protocol which controls the rebroadcasting of
received broadcast packets. This protocol is based on the fact
that the extra coverage area by the rebroadcasting of a node is
inversely proportional to the number of broadcast packet it has
received. This proposed protocol is implemented on the

AODV. The AODV is broadcasting route request (RREQ)
packet to search the route from source to destination. In order
to collect node s current remaining energy information and
dropping information as two additional fields that are added in
the RREQ packet format, thus the format for the RREQ
packet is modified.
A. Modified RREQ Packet
The Probability based Broadcasting technique uses modified
RREQ packet frame for storing nodes remaining energy
strength as shown in following figure. Two field of 4 byes is
added to store node energy strength Si and dropping ratio Di
of node i. The additional memory used for this are very
nominal out of 32 bytes of RREQ packet frame. This modified
RREQ packet is used for broadcast in route discovery. At each
intermediate node this fields will be updated for the remaining
energy strength and dropping ratio at the time of rebroadcast.
Packets are rebroadcasted with this probability
Fig. 1. Frame of AODV RREQ packet
B. Methodology of Probability Based Broadcasting
Technique
Based on the number of received broadcast packets and
energy strengths, the probability is calculated as follows:
After receiving the broadcast packet at node i for for the first
time with remaining energy strengthS0, the node sets a
random relay delay [0, Tmax]. During this delay, it receives
all the rebroadcast packets having energy strength more than
Sth, receive energy threshold. Suppose these are another n-1
redundant packets with energy strength S1, S2, ,Sn-1,
respectively. After the random delay expires, this node relays
this broadcast packet with probability:
.
P =f(n)*E(S)*D(s)
where, ( ) ( ) ( )
( ) ( )
( ) ( )
Smax = max(S0,S1, , Sn-1), Smin = min(S0,S1, , Sn-1)
The f(n) and E(S) are monotonously decreasing
functions and are always less than and equal to 1. The
probability P is guaranteed to be less than 1 as both functions
are also f(n) ≤ 1 and E(S) ≤ 1 always.
Type
(8 bits)
Flags & Reserved
(16bits)
Hop Count
(8bits)
Broadcast ID
……………………………………………………….
……………………………………………………….
……………………………………………………….
Source Sequence Number
Node Remaining Energy strength Si
(Added New Field)
Dropping ratio Di(Added New Field)
Fig. 4. Modified frame of RREQ packet for probability based broadcasting
technique
C. Algorithm for Probability Based Broadcasting Technique
Initialize Counter = 0
While (Broadcast Packets are arriving)
{
Receive Broadcast packet P
if ((Node Energy Strength of P ≥ Sth )&& (Packet Drop Ratio ≤ Dth))
{
if (packet P is first)
= = Node Energy Strength of P
= = Drop ratio of P
Counter ++
Set threshold Random Delay T [0, Tmax]
else
{ if (threshold Random Delay T is not expired)
{ Counter ++
if ((Node Energy Strength of P > ) &&
(Dropping ratio of P > ))
= Node Energy Strength of P
else if ((Node Energy Strength of packet < ) &&
(Dropping ratio of P < ))
= Node Energy Strength of P
}
else
{
n = counter
f(n) = 1/n
E(S) = /
D(s)= /
Probability p = f(n)*E(S)*D(S)

Broadcast packet P with probability p
exit
}
}
}
else Discard packet P
D. Advantages of Proposed AODV
1) Controls rebroadcast packets and drops number of it
based on dynamic probability that results in much
less overhead
2) Proposed protocols ensure broadcasting coverage
with less number of redundant RREQ packets
3) Uses minimum energy to increase network lifetime.
4) Chooses reliable path avoiding transmitting nodes
that is having high drop ratio
TABLE I
SIMULATION PARAMETERS
S.No Parameters Values
1. Channel Wireless
2. Propagation Two Ray Ground
3. Mac Protocol 802.11
4. Routing Queue Drop tail
5. Antenna Omni Directional
6. Energy Model Battery
7. Initial energy 1J
8. Received power 0.3J
9. Transmitted power 0.6J
10. Simulation area 1000*1000
11. Number of nodes 100(fixed)
12. Pause time 0ns
13. Simulation stop time 100ns
14. Mobility 20,30,40,50,60
The analysis of AODV protocol and probability based
AODV is performed, where the number of parameters are set
for common nodes as shown in Table I. By using these
parameters both the protocols are simulated and the
performance is evaluated based on the performance metrics
discussed above.
V. CONCLUSION
In this paper Probability based Broadcasting technique is
proposed and analysed on AODV routing protocol for
Wireless Sensor Networks. The proposed protocol controls
rebroadcast packets and drops number of it based on the
probability that results in much less overhead than AODV.
This protocol uses the minimum energy strength of nodes to
calculate the broadcast probability. It is observed that the
simulated results the packet delivery fraction is good for
probability based AODV than AODV, but end to end delay is
high in probability based AODV.
REFERENCES
[1]. Chris karlof, David wagner, Secure routing in wireless sensor
Networks : Attacks and countermeasures, university of California,
[2]. Poulomi Goswami, Dr.A.D.Jadhav, Performance Evaluation of
Routing Protocols in WSN, Volume 2, Issue 3, June 2012
[3]. Manjusha Pandey and Shekhar Verma, Performance Evaluation of
AODV for Different Mobility Condition, 2011 International
conference on signal processing.
[4]. I.F.Akyildiz,Su.Weilian,Sankarasubramaniam,andE.Cayirci,“A
survey on sensor networks,”ACIEEECommunications magazine
40,8,102-114,2012
[5]. Adel.S.El ashheb, Performance Evaluation of AODV and DSDV
Routing Protocol in wireless sensor network Environment, CNCS
2012
[6]. Parma Nanda, S.C. Sharma; Probability Based Improved
Broadcasting for AODV Routing Protocol, ICASCE 2012
[7]. S.Y. Ni, Y.C. Tseng, Y.S. Chen, J.P. Sheu, The broadcast storm
problem in a mobile ad hoc network, Proceedings of the 1999
Fifth Annual ACM/IEEE International Conference on Mobile
Computing and Networking, IEEE Computer Society, New York,
August 1999, pp. 151
[8]. W. Peng, X. Lu, Poster, On the reduction of broadcast redundancy
in mobile ad hoc networks, Proceedings of the First ACM
International Symposium on Mobile Ad hoc Networking and
Computing, MOBIHOC, Boston, pp 129 130, MA, 2000.
[9]. H. Lim, C. Kim, Multicast tree construction and flooding in
wireless adhoc networks, Proceedings of the ACM International
Workshop on Modeling, Analysis and Simulation of Wireless and
Mobile Systems (MSWIM 2000), Boston, MA, 2000, pp. 6168.
[10]. Qi Zhang, Dharma P. Agrawal, Dynamic probabilistic
broadcasting in MANETs, Journal of Parallel and Distributed
Computing vol 65(2), Feb 2005, pp 220-233 Jie Wu , Fei Dai,
Efficient Broadcasting with Guaranteed Coverage in Mobile Ad
Hoc Networks, IEEE Transactions on Mobile Computing, 2005,
pp 1-35
[11]. C. K. Toh. Ad hoc Mobile Wireless Networks: Protocols and
Systems[M]. Prentice Hall 2005.
[12]. Y. Sasson, D. Cavin, A. Schiper, Probabilistic broadcast for
flooding in wireless mobile ad hoc networks. Technical Report
IC/2002/54, 2002

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