DMRM: Enhanced QoS using Dynamic Multipath Routing for MANETS
*Baskaran.P1, Dr.K.Karuppasamy2
1
Assistant Professor, CSE Dept, Easwari Engineering College, Chennai
1
Email: baskarcse06@gmail.com, Ph: +919095074951
2
Professor & Head, Dept.of CSE, RVS College of Engineering and Technology, Coimbatore
2
Email: kps_cse@yahoo.co.in
Abstract
MANETS are Mobile Ad Hoc Networks
having no infrastructure and is a group of
mobile nodes, usually form a short-term
network based on any requirement.
Nowadays MANETS are used in widely in
many applications due to the availability of
the wireless devices. The Quality of Service
(QoS) is one of the important factors in
MANETS and is a demanding problem in
wireless networks than the wired networks.
Due to the battery power and frequent
mobility of the mobile nodes the topology of
the MANET is changed. It is necessary to
have a dynamic multipath routing
mechanism to improve the QoS of the
Mobile Ad Hoc Networks. This paper
proposed a novel dynamic multipath routing
mechanism for MANETS which identifies
an alternative path for data transmission
when the when the bandwidth of the current
link reduced to the given threshold or load
delay of a node reduced to the given
threshold. Simulation results shows that the
proposed method performs better in term of
average end-to-end delay and delivery ratio
when compared to single path protocol
Optimized Link State Routing (OLSR).
I.
Introduction
Ad hoc networks are self organizing and
dynamic in nature without base station
control. Different Ad hoc networks are (i)
Mobile Adhoc Networks (MANETs) (ii)
Vehicular Adhoc Networks (VANETs) (iii)
Wireless Sensor Network (WSN) (iv)
Wireless Mesh Network (WMN). Collection
of mobile nodes is usually called as Mobile
Ad Hoc Network (MANET). The MANETS
are infrastructure less and having the
property of dynamicity. The connection
between the mobile nodes are wireless.
Some of the applications of MANETS are
army rescue and search, natural calamity
areas and crowd control. Quality of Service
(QoS) is the important parameter in
MANETS for applications such as
multimedia data transmission and disaster
recovery MANET networks. But the QoS
guarantee of the any MANET network is a
challenging
task
[1].
In
wireless
communication due to less battery power,
node mobility and congestion in the channel
provides less QoS when compared to wired
networks. Also the QoS provisioning is one
of the typical tasks in MANETS. Unless
single path routing algorithms, the
MANETS are efficiently work in multipath
routing [2]. The QoS parameters such as
bandwidth, delay and load are deviating
normal values then an alternative path may
be found to transfer the packets to the
destination mobile node. In any emergency
situations, it is easy to install the MANET
than the wired network. Due to the dynamic
nature of the mobile nodes, the
implementation of efficient routing protocol
is very difficult task. There numerous
routing protocols have been proposed in the
literature. Due to the dynamic topology of
the MANETS the multi path routing
protocols plays a major role than the single
path routing algorithms.
This paper is organized as follows:
Section II deals with related work and
Section III explains the proposed method
DMRM. The results are discussed in Section
IV. Section V concludes the paper.
II.
Related Work
This section discusses some of the
routing protocols available in the literature.
Jiazi et al. proposed a Multi Path OLSR
(MP-OLSR) [1] which is based on the
optimized link state routing protocol. The
multiple paths in the mobile network are
obtained using the proposed Multipath
Dijkstra Algorithm. Various link metrics [2]
such as packet delay and bandwidth and cost
functions are used to implement multipath
dijkstra algorithm. The other parameters
used are route recovery and loop detection.
The proposed MP-OLSR is simulated using
Qualnet simulator for various scenarios. The
MP-OLSR
method
presented
better
performance during heavy load and
improves the life time of the network.
Bheemarjuna Reddy et al. have studied
the QoS of the Ad Hoc Wireless senor
networks [3]. The authors have explained
the QoS parameters to be considered in
MANETS and the issues in the QoS
provisioning. The challenges during QoS
provisioning and the solutions available in
the literature are described in [3]. The QoS
solutions are classified into Layer-wise
classification of QoSsolutions and Network
layer solutions. The different QoS
frameworks discussed in this paper are
based on Routing protocol, QoS resource
reservation signaling, Admission control and
Packet scheduling. INSIGNIA [4] is a QoS
framework which is used by INORA [5]
QoS framework. SWAN is a distributed Ad
Hoc Wireless network [6] having feedback
mechanism. Gaurav Singal et al. have
discussed the different Routing methods in
MANETS [7]. Ali et al. have proposed a
routing protocol for MANETS based on
threshold to improve QoS. The proposed
protocol is QMTR protocol [8] which works
with various QoS parameters. Available
bandwidth, node delay, load of the node are
considered for the routing. The proposed
QMTR protocol is based on SMORT in [9].
Goudarzi and Hosseinpour have
proposed a technique for Quality of
Enrichment (QoE) to transmit video over
MANETS [10]. The bandwidth allocation
strategy of the proposed method is based on
the network parameters. The method in [10]
is the
extended
version of the
communication framework in [11]. The
proposed method in [10] reduces the packet
loss with the help of convex optimization in
order to improve QoE. Venkatasubramanian
and Gopalan have proposed energy efficient
QoS algorithm for MANETS [12]. The
proposed method is implemented in Java
and provides better results in terms of packet
delivery ratio, delay, bandwidth and energy
when compared to PAMQR.
Asha and Mahadevan have proposed a
scheme for video transmission to enhance
QoS on MANETS. The proposed method in
[13] enhances the MANET network
performance with respect to channel
modeling, data transmission and queuing
modeling. MATLAB is used to implement
the proposed method and 150X150 m
network area is selected for simulation. The
network parameters such as bandwidth,
delay and throughput is compared with the
existing system and provides 18.60%
improvement. Amuthan et al. have
implemented a QoS method for MANETS
based on channel allocation named
HECAFQEM [14]. The proposed method
used channel conditions with respect to
Hyper-Erlang Factor. Queuing delay and the
transmission delay are two parameters used
for accepting the transmission requests.
HECAFQEM is simulated in ns-2 and
provides 23% and 19% more performance
with respect to the parameters packet
delivery ratio and throughput.
III.
DMRM: Dynamic Multipath
Routing for MANETS
Due to the dynamicity of the nodes in
the MANETS, it is necessary to find the
route dynamically. The proposed DMRM
algorithm finds the path of the packet
transmission dynamically. Usually the
shortest path is used to transmit the packet.
The DMRM algorithm uses a retroactive
priority queue [15] for dynamic shortest path
finding. Any node in the MANET network
is having data packet to send, it has to find
the route with the help of the route request
packet. After getting the reply from the
destination the packet will be transferred.
While considering the first reply, the route is
selected based on the priority queue
dynamically with respect to the network
bandwidth and delay. The operation on the
DMRM algorithm estimated the available
bandwidth of the current route and the delay
after a route reply message is received from
the destination. If bandwidth is less than the
bandwidth threshold and the delay is greater
than the delay threshold a new path will be
found using retroactive priority queue and
the data is transmitted. The available
bandwidth is calculated based on equation
(1) [16], the delay is calculated using the
method available in [17] and the load is
calculated using equation (2) [18].
 Idlet
BW Av  BWMax * 
 Intt
(1)



In equation (1) BWMax is the links
maximum bandwidth of the and the Idlet is
the duration of channel without any data
transmission over the inteval Intt . Idlet is
calculated as the difference between the
default time interval and the duration in
which the channel changes from busy to idle
and IEEE 802.11 is having the method to
calculate wheather the channel id idle or
busy.
 Qlen 
 CW 

Load i  X 
  1   X 
 MaxCW 
 MaxQlen 
(2)
In equation (2) Contention Window
(CW) and Queue length (Qlen) should be
minimum in order to reduce the load. The 
is set as 0.5 to equalize the priority of
contention window and queue length [18].
IV.
Results
The simulation is done through network
simulator (NS-2) [19]. The bandwidth of the
channel is preset as 2 Mbps. The parameters
which are used for simulation is depicted in
Table 1. The proposed DMRM algorithm
uses Constant Bit Rate (CBR) for the
parameters average end-to-end delay and
delivery ratio. Figure 1 depicts the model of
multi hop in MANETS. The parameters
considered for this simulation are delay,
delivery ratio and throughput. The proposed
approach DMRM is compared with OLSR
algorithm and the results are shown in
Figure 2, 3 and 4. The considered
parameters are performing better in the
proposed method DMRM when compared to
OLSR.
S
D
Figure 1. Model of Multi hop in MANETS
Table 1: Simulation Parameters
S.
No.
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
Parameters
Values
No. of Nodes
Area
MAC
Radio Range
Simulation
Time
Traffic Source
Packet Size
Mobility Model
Speed
Pass Time
Rate
30,50,70,100,150
1500 X 1500 m
IEEE 802.11 DCF
250 m
Figure 2. Number of Nodes Vs End to End
Delay
50 s
CBR
512 B
Random
10 m/s
5 sec
250kb/s to 500kb/s
Figure 3. Number of Nodes Vs Delivery Ratio
3.
Figure 4. Data Rate Vs Throughput
V.
Conclusions
The dynamic multi hop routing is one of
the important research problems in the
network community. The overloaded nodes
degrade the network performance and
packet loss may occur due to less
bandwidth. Due to overloading congestion
may occur and the delay also increased. To
increase the network QoS performance
dynamic path finding algorithm is proposed.
The proposed DMRM algorithm reduces
average end-to-end delay and improves
delivery ratio there by increasing the
throughput when comparing to the
optimized link state routing algorithm.
4.
5.
6.
Funding: This study was not supported by
any funding.
Conflict of Interest: The authors declare
that they have no conflict of interest.
References
1. Jiazi Yi, Asmaa Adnane, Sylvain
David, Benoît Parrein, “ Multipath
optimized link state routing for
mobile ad hoc networks”, Ad Hoc
Networks, vol. 9, pp. 28–47, 2011
2. H. Badis, K.A. Agha, Qolsr multipath routing for mobile ad hoc
7.
8.
networks based on multiple metrics:
bandwidth and delay, in: IEEE
Vehicular Technology Conference,
Los Angeles, CA, USA, 2004, pp.
2181–2184.
T.
Bheemarjuna
Reddy,
I.
Karthigeyan, B.S. Manoj, C. Siva
Ram Murthy, “Quality of service
provisioning in ad hoc wireless
networks: a survey of issues and
solutions”, Ad Hoc Networks, vol.
4,pp. 83–124, 2006.
S.B. Lee, A. Gahng-Seop, X. Zhang,
A.T. Campbell, INSIGNIA: An IPbased quality of service framework
for mobile ad hoc networks, Journal
of
Parallel
and
Distributed
Computing 60 (4) (2000) 374–406.
D. Dharmaraju, A.R. Chowdhury, P.
Hovareshti, J.S. Baras, INORA––A
unified signalling and routing
mechanism for QoSsupport in
mobile ad hoc networks, in:
Proceedings of ICPPW 2002, August
2002, pp. 86–93.
H. Ahn, A.T. Campbell, A. Veres, L.
Sun,
Supporting
service
differentiation for real-time and besteffort traffic in stateless wireless ad
hoc networks, IEEE Transactions on
Mobile Computing 1 (3) (2002) 192–
207.
Gaurav Singal, Vijay Laxmi, Manoj
S Gaur, D Vijay Rao, and Riti
Kushwaha, “QoS–aware Mesh based
Multicast Routing Protocols in AdHoc Networks: Concepts and
Challenges”,
M. Ali, B. G. Stewart, A. Shahrabi,
A.
Vallavaraj,
“QoS
Aware
Multipath Threshold Routing for
Mobile
Ad
hoc
Networks”
International Journal of Applied
Information Systems (IJAIS) – ISSN
: 2249-0868 Foundation of Computer
Science FCS, New York, USA
Volume 7– No. 1, April 2014
9. L. R. Reddy and S.V. Raghavan,
2007, "SMORT: Scalable multipath
on-demand routing for mobile ad hoc
networks", in proc. of Journal on Ad
Hoc Networks, vol. 5, no. 2, pp: 162188, March 2007.
10. P. Goudarzi, M. Hosseinpour,”QoE
enhancement for video transmission
over MANETS using distortion
minimization, Scientia Iranica D
(2012) 19 (3), 696–706.
11. Goudarzi, P. ‘‘An optimization
theoretic framework for video
transmission with minimal total
distortion over wireless networks’’,
EURASIP Journal on Wireless
Communication and Networking, pp.
189–192 (2009).
12. S. Venkatasubramanian and N.P.
Gopalan,
“Improving
Energy
Efficient QOS Performance for
Heterogeneous
MANET”
,
International Journal of Computer
Networks and Communications
Security, VOL. 2, NO. 2,
FEBRUARY 2014, 70–81
13. Asha , G. Mahadevan,” A combined
scheme of video packet transmission
to improve cross layer to support
QoS for MANET”, Alexandria
Engineering Journal, vol. 57, pp.
1501–1508, 2018.
14. Amuthan Arjunan , N. Sreenath , P.
Boobalan , K. Muthuraj, “HyperErlang channel allocation factorbased QoS enhancement mechanism
for mobile ad hoc networks”,
Alexandria Engineering Journal,
vol.57, pp. 799–811, 2018.
15. Sunita , Deepak Garg, “Dynamizing
Dijkstra: A solution to dynamic
shortest path problem through
retroactive priority queue”, Journal
of King Saud University – Computer
and Information Sciences, 2018
16. F. Qin and Y. Liu, 2009, Multipath
Routing for Mobile Ad Hoc
Network, Proc. of the 2009
International
Symposium
on
Information Processing (ISIP’09)
Huangshan, P. R. China, pp. 237240, August 21-23, 2009.
17. R. Kumar, A. K Sarje and M. Misra,
2010, “An AODV based QoS
Routing Protocol for Delay Sensitive
Applications in Mobile Ad Hoc
Networks”, Journal of Digital
Information Management, Vol 8 No.
5, October 2010.
18. X. Gao, X. Zhang, D. Shi, F. Zou
and W. Zhu, 2007, Contention and
Queue-aware Routing Protocol for
Mobile
Ad
hoc
Networks,
International Conference on Wireless
Communications, Networking and
Mobile Computing (WiCom 2007),
Shanghai, 21-25 Sept. 2007.
19. Network
Simulator,
http://www.isi.edu/nsnam/ns