An Energy Efficient and Reliable Congestion Control Protocol For Multicasting In Mobile Adhoc Networks

Report as inappropriate Your report has been received

Shared by: ijcsiseditor

Tags

An, Energy, Efficient, and, Reliable, Congestion, Control, Protocol, For, Multicasting, In, Mobile, Adhoc, Networks

Stats

views:: 205
posted:: 2/13/2010
language:: English
pages:: 6

Public Domain

Document Sample

(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 7, No. 1, 2010

An Energy Efficient and Reliable Congestion Control
Protocol For Multicasting In Mobile Adhoc Networks

Dr.G.Sasi Bhushana Rao M.RajanBabu
Senior Professor Associate Professor
Department of Electronics and Communication Engineering Department of Electronics and Communication Engineering
Andhra University Lendi Institute of Engineering and Technology
Visakhapatnam Jonnada, Vizianagaram, AndhraPradesh, India
.

Abstract— This paper presents an energy efficient and reliable member. The group membership is dynamic means that hosts
congestion control protocol for multicasting in mobile adhoc may join and leave groups at any time Multicast packets are
networks (MANETs). Our proposed scheme overcomes the delivered to each member of a multicast group with the same
disadvantages of existing multicast congestion control protocols best-efforts reliability and performance as unicast packets to
which depend on individual receivers to detect congestion and members. Multicast groups may be of arbitrary size, may
adjust their receiving rates. In the first phase of our protocol, we change membership dynamically, and may have either a
build a multicast tree routed at the source, by including the nodes global or local scope. The senders do not need to know
with higher residual energy towards the receivers. In the second membership groups, and needs not to be a member of that
phase, we propose an admission control scheme in which a
group. [2]. In addition, within a wireless medium, it is crucial
multicast flow is admitted or rejected depending upon on the
output queue size. In the third phase, we propose a scheme which
to reduce the transmission overhead and power consumption.
adjusts the multicast traffic rate at each bottleneck of a multicast Multicasting can improve the efficiency of the wireless link
tree. Because of the on-the-spot information collection and rate when sending multiple copies of messages by exploiting the
control, this scheme has very limited control traffic overhead and inherent broadcast property of wireless transmission. Hence,
delay. Moreover, the proposed scheme does not impose any reliable multicast routing plays a significant role in MANETs
significant changes on the queuing, scheduling or forwarding [1].
policies of existing networks. Simulation results shows that our Multicasting can be used to improve the efficiency of the
proposed protocol has better delivery ratio and throughput with
wireless link when sending multiple copies of messages to
less delay and energy consumption when compared with existing
protocol.
exploit the inherent broadcast nature of wireless transmission.
So multicast plays an important role in MANETs Unlike
Keywords-Congestion Control; Mobile Adhoc Networks; typical wired multicast routing protocols, multicast routing for
Multicasting; admission control; multicast tree. MANETs must address a diverse range of issues due to the
characteristics of MANETs, such as low bandwidth, mobility
I. INTRODUCTION and low power. MANETs deliver lower bandwidth than wired
A mobile ad-hoc network (MANET) is composed of networks; therefore, the information collection during the
mobile nodes without any infrastructure. Mobile nodes self- formation of a routing table is expensive [1].
organize to form a network over radio links. The goal of A. Multicast Issues in MANET
MANETs is to extend mobility into the realm of autonomous,
Scalability: A multicast routing protocol is scalable with
mobile and wireless domains, where a set of nodes form the
respect to some constraints posed by MANETs.
network routing infrastructure in an ad-hoc fashion. The
majority of applications of MANETs are in areas where rapid Multicast service support: The multicast protocol defines
deployment and dynamic reconfiguration are necessary and conditions for joining/leaving groups, multicast participants
wired network is not available. These include military should be able to join or leave groups at will. On the other
battlefields, emergency search, rescue sites, classrooms and hand, service providers can be convinced to support multicast
conventions, where participants share information dynamically protocols.
using their mobile devices. These applications lend themselves
well to multicast operations [1]. Traffic control: Both source and core-based approaches
concentrate traffic on a single node. In stateless multicast
Multicasting is aimed to deliver data to a set of selected group membership is controlled by the source, which leads to
receivers. There is no restriction on the location or number of the vulnerability of multicast protocols for MANETs. Still
members in a host group. Multicast can be classified into one need to be investigated is how to efficiently distribute traffic
to many or many to many communication applications. The from a central node to other member nodes for MANETs.
important member identifications and functions are: group
member, sources, destination, forwarding nodes, non-group

196 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 7, No. 1, 2010

QoS: QoS defines a guarantee given by the network to redundancy according to the current link conditions. They
satisfy a set of predetermined service performance constraints simultaneously reduce unnecessary energy dissipation.
for the user in terms of end-to-end delay, jitter, and available
bandwidth. Therefore, multicast routing protocols must be D. Agrawal, T. Bheemarjuna Reddy, and C. Siva Ram
feasible for all kinds of constrained multicast applications to Murthy [5] propose a Robust Demand-driven Video Multicast
run well in a MANET. However, it is a significant technical Routing (RDVMR) protocol. Their protocol uses a novel path
challenge to define a comprehensive framework for QoS based Steiner tree heuristic to reduce the number of forwarders
support, due to dynamic topology, distributed management in each tree. They construct multiple trees in parallel with
and multi-hop connections for MANETs. reduced number of common nodes among them. Moreover,
unlike other on-demand multicast protocols, RDVMR
Multiple sources: Most of the existing multicast routing specifically attempts to reduce the periodic (non on-demand)
protocols in ad-hoc networks are designed for single source control traffic.
multicasting. However, a multicast group may contain
multiple sources due to different kinds of services or Guojun Wang, Jiannong Cao, Lifan Zhang, Keith C. C.
applications simultaneously provided by the networks. Each Chan [6] proposes a logical Hypercube-based Virtual
single source multicast routing protocol induces a lot of Dynamic Backbone (HVDB) model for QoS-aware multicast
communications. In this model, high fault tolerance and small
overhead and thus wastes tremendous network resources in a
multi-source multicast environment. diameter of hyper cubes are the basis for high availability, and
regularity and symmetry of hyper cubes contribute to good
The QAMNet [9] depends on the traffic pattern hence it is load balancing.
difficult to accurately estimate the threshold rate. The
protocols which support QoS for multicasting introduce Vida Lashkari B. O, Mehdi Dehghan [7] proposes an
network state and additional signaling. Such additional efficient algorithm named is proposed to improve the route
signaling packets for reservation protocol must be avoided as discovery mechanism in MAODV for QoS multicast routes.
this adds to network congestion, especially in high mobility QoS-MAODV especially can establish a multicast tree with
scenarios. the minimum required bandwidth support and decrease the
end-to-end delay between each destination and the source
The QMR and E-QMR protocols calculate approximately node. It can establish QoS routes with the reserved bandwidth
the available bandwidth based on the channel status. This on per chosen flow. To perform accurate resource reservation,
results in some problem. Each node can listen to the channel to they have developed a method for estimating the consumed
determine the channel status and computes the idle duration bandwidth in multicast trees by extending the methods
only for a period of time [10]. A lantern-tree topology is used proposed for unicast routing.
to provide QoS multicast routing. Need for a centralized MAC
scheme in ad hoc mobile networks with dynamic wireless Zeyad M. Alfawaer, GuiWei Hua, and Noraziah Ahmed
environments is its main disadvantage [12]. [8] introduced MANHSI (Multicast for Ad hoe Network with
hybrid Swarm Intelligence) protocol, which relies on a swarm
B. Proposed Solution intelligence based optimization technique to learn and
In this paper, we propose to design an energy efficient and discover efficient multicast connectivity. The proposed
reliable congestion control (EERCCP) protocol for protocol instances that it can quickly and efficiently establish
multicasting with the following phases. initial multicast connectivity and/or improved the resulting
connectivity via different optimization techniques.
In its first phase, it builds a multicast tree routed at the
source, by including the nodes with higher residual energy Harald Tebbe and Andreas J. Kassler [9] present QAMNet,
towards the receivers. Most of the existing schemes depend an approach to improve the Quality of Service (QoS) for
on individual receivers to detect congestion and adjust their multicast communication in MANETs. They extend existing
receiving rates which are much disadvantageous. In the second approaches of mesh based multicasting by introducing traffic
phase, we propose an admission control scheme in which a prioritization, distributed resource probing and admission
multicast flow is admitted or rejected depending upon on the control mechanisms, adaptive rate control of non-real-time
output queue size. traffic based on Medium Access Control (MAC) layer
feedback so as to maintain low delay and required throughput
In the third phase, we propose a scheme which adjusts the for real-time multicast flows.
multicast traffic rate at each bottleneck of a multicast tree.
Mohammed Saghir, Tat-Chee Wan, Rahmat Budiarto [10]
II. RELATED WORK has extended QMR to make it more effective than the previous
work. They propose a cross-layer framework to support QoS
Hua Chen, Baolin Sun [3] introduces an Entropy-based
multicasting. They have enhanced the IEEE 802.11 MAC
Fuzzy controllers QoS Routing algorithm in MANET
layer to estimate the available bandwidth at each node.
(EFQRM). The key idea of EFQRM algorithm is to construct
the new metric-entropy and fuzzy controllers with the help of Ravindra Vaishampayan, J.J. Garcia-Luna-Aceves [11]
entropy metric to reduce the number of route reconstruction so proposed a protocol for unified multicasting through
as to provide QoS guarantee in the ad hoc network. announcements (PUMA) in ad-hoc networks, which
establishes and maintains a shared mesh for each multicast
Tolga Numanoglu and Wendi Heinzelman [4] propose a
group, without requiring a unicast routing protocol or the pre
mesh networking inspired approach that adapts the amount of
assignment of cores to groups. PUMA achieves a high data

197 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 7, No. 1, 2010

delivery ratio with very limited control overhead, which is Hence, the residual energy ( E ) of each node can be
almost constant for a wide range of network conditions. calculated using (1) or (2) and (3)
N. Ben Ali, A. Belghith, J. Moulierac, M. Molnar [13] has E = Current energy – Consumed energy
proposed a new algorithm coined mQMA. This deals with two
main problems of traditional IP multicast, which are multicast 2) Algorithm:
forwarding state scalability and multi-constrained QoS 1. Consider a group G j = {N1 , N 2 , L , N 3 }
routing. The algorithm mQMA is a QoS multicast aggregation
algorithm which handles multiple additive QoS constraints. It 2. Measure the distance d of each node from source S
builds few trees and maintains few forwarding states for the
groups. The multicast tree aggregation technique, allows d ( S , N i ) where i = 1,2, L , n
several groups to share the same delivery tree. The mQMA
algorithm builds trees satisfying multiple additive QoS 3. Sort the nodes N i in ascending order of d .
constraints.
4. Create the partitions X 1 and X 2 of the nodes N i such
III. ENERGY EFFICIENT AND RELIABLE CONGESTION that
CONTROL PROTOCOL
X 1 = { N1 , L , N Q }
A. Energy Efficient Tree Construction
In our energy efficient and reliable congestion control X 2 = { N Q +1 , L , N n }
protocol we build a multicast tree routed at the source towards
the receivers. The distance i.e. the geographical location of the Where Q is the distance threshold.
nodes is assumed. Their residual energy is measured. The
nodes are sorted based on its location from the source and 5. Source unicast the packets to X 1
arranged in a sequence order. A threshold value Q is set and 6. In X 2 find a relay node N r which has max ( Ei )
the nodes which are less than Q(n < Q ) are unicast from the
source and the nodes which are greater than Q(n > Q ) are 7. Then S unicast the packets to N r which in turn
multicast. In case of multicasting the node which has the multicast the packets to the rest of the nodes in X 2 .
minimum energy per corresponding receiver is set as the relay
node. The relay node then forwards the packets from the
source to the corresponding receivers.
1) Calculating Residual Energy of a Node: Consider a
network with multicast groups G1 , G 2 , L , G x . Each group
{Gi } consists of N nodes. Every node in the MANET
calculates its remaining energy periodically. The nodes may
operate in either transmission or reception mode. Let
{E1 , E 2 , L , E n } are the residual energies of the nodes
measured by the following method.
The power consumed for transmitting a packet is given by
(1)

Consumed energy = TP * t (1)

Where TP is the transmitting power and t is transmission Figure 1. Energy efficient tree construction
time.
Source S unicast the packets to nodes N1 , N 2 , N 3 , N 4
The power consumed for receiving a packet is given by (2) and N 5 is the relay node. N 5 multicast the packets to the rest
Consumed energy = RP * t (2) of the nodes N 6 , L , N11 .
B. Multicast Admission Control
Where RP is the reception power and t is the reception time.
Most of the existing schemes depend on individual
The value t can be calculated as receivers to detect congestion and adjust their receiving rates
which are much disadvantageous. We propose a scheme which
t = D s / Dr (3) adjusts the multicast traffic rate at each bottleneck of a
multicast tree. Each node estimates its current traffic load and
Ds is Data size and Dr is Data rate arrival rate. Based on its traffic load, it estimates the receiving
rate. If the receiving rate is less than the arrival rate, it
adaptively adjusts its receiving rate.

198 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 7, No. 1, 2010

In order to adjust the total number of multicast flows IV. SIMULATION RESULTS
which traverse a bottleneck, the following procedure is used.
In our proposed scheme, based on the link’s output queue A. Simulation Model and Parameters
state, multicast flows at a bottleneck can be blocked or We use NS2 to simulate our proposed protocol. In our
released. Let the number of packets in the queue is N . Let simulation, the channel capacity of mobile hosts is set to the
QT 1 and QT 2 (QT 1 < QT 2) are two thresholds for the same value: 2 Mbps. We use the distributed coordination
function (DCF) of IEEE 802.11 for wireless LANs as the
queue size. Then the flow is released or blocked based on the
MAC layer protocol. It has the functionality to notify the
following conditions.
network layer about link breakage.
If N ≤ QT 1 , then the multicast flow is released.
In our simulation, 50 mobile nodes move in a 1000 meter x
If N > QT 2 , then the multicast flow is blocked. 1000 meter region for 50 seconds simulation time. We assume
In most of the existing schemes, in order to detect each node moves independently with the same average speed.
congestion and for adjusting the receiving rate they depend on All nodes have the same transmission range of 250 meters. In
the individual receivers. In our proposed scheme multicast our simulation, the minimal speed is 5 m/s and maximal speed
traffic rate is adjusted at each bottleneck of a multicast tree. is 5 m/s. The simulated traffic is Constant Bit Rate (CBR).
Whenever congestion happens or about to, then the multicast
Our simulation settings and parameters are summarized in
sessions which traverse the branch are blocked. Thus the table I
packets are stopped from entering the branch. The blocked
flows are released to traverse the branch when the branch is TABLE I. SIMULATION PARAMETERS
lightly utilized.
No. of Nodes 50
C. Multicast Traffic Rate Adjustment Area Size 1000 X 1000
When the available bandwidth is less than the required Mac 802.11
bandwidth or the queue size is less than a minimum threshold Radio Range 250m
value, it indicates the possibility of congestion or packet loss. Simulation Time 50 sec
The behaviour of the multicast session is expressed as Traffic Source CBR
Packet Size 250,500,…1000
R(t + 1) = {R(t ) − g If R (t ) > B Mobility Model Random Way Point
Speed 5m/s
R (t ) + g If R(t ) ≤ B Receivers 5,10,…25
Pause time 5s
R (t ) otherwise} Transmit Power 0.660 w
Here R(t ) denotes the instantaneous rate of the multicast Receiving Power 0.395 w
Idle Power 0.335 w
session at time t . B is the bottleneck bandwidth.
Initial Energy 3.1 J
When R(t ) > B then the network is congested and the B. Performance Metrics
multicast session decreases its rate by a step g .
We compare our EERCCP protocol with the multicast
If R(t ) ≤ B then the network is not congested and the AODV [14] protocol. We evaluate mainly the performance
according to the following metrics.
multicast session increases its rate by a step g .
Average end-to-end delay: The end-to-end-delay is
The proposed scheme overcomes most of the averaged over all surviving data packets from the sources to
disadvantages of existing schemes: the destinations.
1. Link errors cannot cause the proposed scheme to Average Packet Delivery Ratio: It is the ratio of the No.
wrongly block a layer, because instead of the loss information of packets received successfully and the total no. of packets
at receivers, the queue state at a bottleneck is used as the sent.
metric to adjust the multicast traffic rate at the bottleneck.
Average Energy Consumption: The average energy
2. Link access delay caused by competition in MANETs consumed by the nodes in receiving and sending the packets
cannot hinder the rate adjustment in this scheme, because, it are measured.
blocks multicast layers right at each bottleneck of a multicast
tree instead of depending on receivers to request pruning to Throughput: It is the number of packets received by all
drop layers. the nodes in the network.

3. Because of the on-the-spot information collection and C. Results
rate control this scheme has very limited control traffic 1) Based On Receivers: In this experiment, we vary the
overhead. group size or the number of receivers per group as 5,10…..25.
Moreover, the proposed scheme does not impose any
significant changes on the queuing, scheduling or forwarding
policies of existing networks.

199 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 7, No. 1, 2010

When the number of receivers is increased,
Receivers Vs Delay
Figure 2 shows the end-to-end delay occurred for both
6 AODV and EERCCP. As we can see from the figure, the
5.8 delay is less for EERCCP, when compared to AODV.
5.6 Figure 3 shows the delivery ratio for both AODV and
Delay

AODV
5.4 EERCCP EERCCP. As we can see from the figure, the delivery ratio is
5.2
high for EERCCP, when compared to AODV.
5 Figure 4 shows the energy consumption for both the cases.
5 10 15 20 25 As we can see from the figure, the energy consumption is less
Receivers for EERCCP, when compared to AODV.
Figure 3 shows the throughput occurred for both the cases.
Figure 2. Receivers Vs Delay As we can see from the figure, the throughput is high for
EERCCP, when compared to AODV.
Receivers Vs DelRatio 2) Based on Psize: In this experiment, we vary the packet
size as 250,500…..1000.
1
Psize Vs Delay
0.8
DelRatio

0.6 AODV
6
0.4 EERCCP 5.95
5.9
0.2 5.85

Delay
AODV
0 5.8
5.75 EERCCP
5 10 15 20 25 5.7
Receivers 5.65
5.6
250 500 750 1000
Figure 3. Receivers Vs Delivery Ratio Psize

Receivers Vs Energy Figure 6. Psize Vs Delay

1.7 Psize Vs De lRatio
1.65
Energy

AODV 0.5
1.6 0.4
EERCCP
DelRatio

1.55 0.3 AODV
0.2 EERCCP
1.5
5 10 15 20 25 0.1
0
Receivers
250 500 750 1000
Psize
Figure 4. Receivers Vs Energy
Figure 7. Psize Vs DelRatio
Receivers Vs Throughput

Psize Vs Energy
3000
2500
1.75
Throughput

2000
AODV 1.7
1500
EERCCP
Energy

1000 1.65 AODV
500 1.6 EERCCP
0 1.55
5 10 15 20 25
1.5
Receivers 250 500 750 1000
Psize
Figure 5. Receivers Vs Throughput
Figure 8. Psize Vs Energy

200 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 7, No. 1, 2010

[3] Hua Chen, Baolin Sun,” An Entropy-Based Fuzzy Controllers QoS
Psize Vs Throughput Routing Algorithm in MANET”,IEEE,2009
[4] Tolga Numanoglu and Wendi Heinzelman,” Improving QoS in
2000 Multicasting Through Adaptive Redundancy”, University of Rochester
Center for Electronic Imaging Systems
Throughput

1500 [5] D. Agrawal, T. Bheemarjuna Reddy, and C. Siva Ram Murthy,” Robust
AODV Demand-Driven Video Multicast over Ad hoc Wireless
1000 Networks”,IEEE,2006
EERCCP
[6] Guojun Wang, Jiannong Cao, Lifan Zhang, Keith C. C. Chan,” A Novel
500
QoS Multicast Model in Mobile Ad Hoc Networks”, IEEE International
Parallel and Distributed Processing Symposium,2005
0
[7] Vida Lashkari B. O., Mehdi Dehghan” QoS-aware Multicast Ad hoc On-
250 500 750 1000
Demand Distance Vector Routing”, WCE 2007
Psize [8] Zeyad M. Alfawaer, GuiWei Hua, and Noraziah Ahmed,” A Novel
Multicast Routing Protocol for Mobile Ad Hoc Networks”, ISSN, 2007
[9] Harald Tebbe and Andreas J. Kassler ,” QAMNet: Providing Quality of
Figure 9. Psize Vs Throughput Service to Ad-hoc Multicast Enabled Networks”, Wireless Pervasive
Computing, 2006 1st International Symposium on, IEEE,2006
When the Psize is increased, [10] Mohammed Saghir, Tat-Chee Wan, Rahmat Budiarto,” QoS Multicast
Routing Based on Bandwidth Estimation in Mobile Ad Hoc Networks”,
Figure 6 shows the end-to-end delay occurred for both ICCCE2006
AODV and EERCCP. As we can see from the figure, the [11] Ravindra Vaishampayan, J.J. Garcia-Luna-Aceves,” Efficient and
delay is less for EERCCP, when compared to AODV. Robust Multicast Routing in Mobile Ad Hoc Networks”, IEEE, 2004
Figure 7 shows the delivery ratio for both AODV and [12] Y. Chen and Y. Ko, “A Lantern-Tree Based QoS on Demand Multicast
Protocol for A wireless Ad hoc Networks,” IEICE Trans.
EERCCP. As we can see from the figure, the delivery ratio is Communications, vol. E87-B, 2004
high for EERCCP, when compared to AODV. [13] 13 N. Ben Ali, A. Belghith, J. Moulierac, M. Molnar,” QoS multicast
Figure 8 shows the energy consumption for both the cases. aggregation under multiple additive constraints”, Elsevier, 2008
As we can see from the figure, the energy consumption is less [14] Elizabeth M. Royer, Charles E. Perkins,” Multicast Operation of the Ad-
hoc On-Demand Distance Vector Routing Protocol”,ACM,1999
for EERCCP, when compared to AODV.
Figure 9 shows the throughput occurred for both the cases.
As we can see from the figure, the throughput is high for Dr.G.Sasi Bhushana Rao received his BE from
EERCCP, when compared to AODV. GITAM, Visakhapatnam. ME, PhD, MBA (HRD &
Marketing) from Osmania University. He has 22 years
V. CONCLUSION of research and development, administrative
experience as asst. General Manager (CNS) in Airport
In this paper, we have proposed an energy efficient and Authority of India, Ministry of Civil Aviation and
reliable congestion control protocol for multicasting in mobile ISRO, Govt. of India. Presently he is working as
adhoc networks. Our proposed protocol overcomes the Senior Professor in E C E Dept. at Andhra University
disadvantages of existing multicast congestion control Visakhapatnam. His areas of interest are GPS, Signal
protocols which depend on individual receivers to detect Processing and Mobile Communications. He has more than 100 in various
International and National Journals and conferences (including IEEE, IEE)
congestion and adjust their receiving rates. In the first phase presently ongoing project works under his guidance are DRDO (N S T L),
of our protocol, we have built a multicast tree routed at the CSIR, UGC, AICTE and WIPRO research projects in the department of
source, by including the nodes with higher residual energy electronics and communication engineering Andhra University
towards the receivers. In the second phase, we have proposed Visakhapatnam. He is senior member in IEEE.
an admission control scheme in which a multicast flow is
admitted or rejected depending upon on the output queue size. M. RajanBabu received B.Tech from Bapatla
In the third phase, we have proposed a scheme which adjusts Engineering College-Bapatla and M.Tech from J N T
the multicast traffic rate at each bottleneck of a multicast tree. U College of Engineering-Kakinada in the
Because of the on-the-spot information collection and rate Department of Electronics And Communication
control, this scheme has very limited control traffic overhead Engineering, He is pursuing his PhD under the
guidance of Dr. G. Sasi Bhushana Rao on wireless
and delay. Moreover, the proposed scheme does not impose networks from Andhra University He is having 12
any significant changes on the queuing, scheduling or years of teaching experience currently he is working
forwarding policies of existing networks. Simulation results as Associate Prof in Lendi Institute of Engineering and technology Jonnada
have shown that our proposed protocol has better delivery Vizianagaram (dt) A.P -India
ratio and throughput with less delay and energy consumption
when compared with existing protocol.
REFERENCES
[1] Luo Junhai, Xue Liu, Ye Danxia,” Research on multicast routing
protocols for mobile ad-hoc networks”, Elsevier, 2007
[2] Abdussalam Nuri Baryun, and Khalid Al-Begain,” A Design Approach
for MANET Multicast Protocols”, ISBN, 2008

201 http://sites.google.com/site/ijcsis/
ISSN 1947-5500