Mobile Ad hoc networks (MANETs) are power constrained since nodes are operated with limited battery supply. The important technical challenge is to avoid the node overutilization and increase the energy efficiency of each node with increasing traffic. If a node runs out of battery, its ability to route the traffic gets affected and hence, the network lifetime. There has been considerable progress in the battery technology, but not in par with the semiconductor technology. There are various techniques adopt the different approaches to achieve energy efficiency. The proposed approach uses a cost metric for path selection, which is a function of residual battery and current traffic load at a node. Further, the simulation and performance is carried through Qualnet network simulator. From the simulation results, it is observed that the proposed scheme has lower node overutilization with the less CBR connections.
Performance of CBR Traffic on Node Overutilization in MANETs
1. International Journal of Research and Scientific Innovation (IJRSI) | Volume IV, Issue III, March 2017 | ISSN 2321–2705
www.rsisinternational.org Page 21
Performance of CBR Traffic on Node Overutilization
in MANETs
Shridhar Kabbur
Department of ECE
Global Academy of Technology
Bengaluru-560098
Rajashri Y M
Department of ECE
Global Academy of Technology
Bengaluru-560098
Abstract - Mobile Ad hoc networks (MANETs) are power
constrained since nodes are operated with limited battery supply.
The important technical challenge is to avoid the node
overutilization and increase the energy efficiency of each node
with increasing traffic. If a node runs out of battery, its ability to
route the traffic gets affected and hence, the network lifetime.
There has been considerable progress in the battery technology,
but not in par with the semiconductor technology. There are
various techniques adopt the different approaches to achieve
energy efficiency. The proposed approach uses a cost metric for
path selection, which is a function of residual battery and current
traffic load at a node. Further, the simulation and performance is
carried through Qualnet network simulator. From the simulation
results, it is observed that the proposed scheme has lower node
overutilization with the less CBR connections.
Key Words - MANET, node overutilization, CBR, network
lifetime.
I. INTRODUCTION
n Mobile Ad Hoc networks (MANET), routing is a major
concern as the nodes are battery operated. Multipath routing
approaches [8] are being introduced to overcome the
limitation of single path routing. The paths chosen can be link
disjoint or node disjoint. Node disjoint paths have no common
nodes except source and destination. Link-disjoints have no
common links but can have common nodes. Multipath
approaches have several benefits such as, higher utilization of
bandwidth, lower end-to-end delay, higher network lifetime. It
also provides load balancing by forwarding the traffic through
multiple paths. An energy aware multipath routing protocol
provides a tradeoff between energy consumption and other
metrics, such as: link reliability, network capacity, throughput,
end-to-end delay. Many of the energy efficient techniques
minimize the energy consumption by selecting energy
efficient path. However, when some nodes on the path
forward large amounts of traffic they may die quickly due to
the over utilization of that path. We have considered the nodes
residual energy and its current traffic load for path selection.
A cost metric is proposed based on these parameters. The rest
of the paper is organized as follows: Few multipath protocols
are described in section-II. The proposed scheme is discussed
in section-III, Simulation parameters and results are discussed
in section-IV and conclusion in the section-V.
II. RELATED WORK
In Minimum Energy Routing (MER) authors [10]
described routing of a data packet on a route that consumes
the minimum amount of energy to get the packet to the
destination with the knowledge of cost of the link.MER incurs
higher routing overhead, but lower total energy. AODV
Multiple Alternative Paths (AODV-MAP) [2] is another
variant of AODV. It considers both fail-safe paths and disjoint
path. The main idea of the protocol is to find more number of
alternate paths. Scalable Multipath On-demand Routing
(SMORT) [3] is a multipath routing protocol based on AODV
[5]. It minimizes the routing overheads by using fail-safe paths
instead of node-disjoint and link-disjoint paths. AOMDV [4]
is one of the extensions of AODV [7]. It searches loop free
and link-disjoint paths.
III. ENERGY EFFICIENT ROUTING PROTOCOL
The proposed scheme describes route cost metric, technique to
minimize node over utilization and computation of
transmission power.
A) Route Cost Metric:
The lifetime of a node is based on cost function includes
Residual Battery (RB) power and Energy consumption rate
(EC). Let the energy consumption rate of a node u at time t is
CR u(t) and its residual battery be RB u(t).Let LT u(t) be the
lifetime of a node u at time t is given by equation (1)
LT u(t) = RB u(t)/ CR u(t) 1
The energy consumption rate CR u(t) is given by equation (2)
CR u(t) = (1- η) × CRold + η × CRnew 2
Where CRold and CRnew represents the last and newly
calculated value of energy consumption rate respectively η(< 1)
is a weight function.
B) Minimizing Node overutilization:
A critical node may exhaust battery and die due to the
heavy traffic. This affects and reduces the network lifetime. A
node drops RREQ packets if the connection request between
source-destination exceeds the limit and reset the connection
limit to that destination to One for the critical node
requirement. Thus the node will forward subsequent RREQ
packets for the connection establishment.
C) Computation of Transmission Power:
I
2. International Journal of Research and Scientific Innovation (IJRSI) | Volume IV, Issue III, March 2017 | ISSN 2321–2705
www.rsisinternational.org Page 22
A node calculates its transmission power for data
packets based on next-hop node’s location and mobility
pattern. A node u compute the transmission power required to
reach the next-node v on a path is given by equation (3)
Tx = (D + ∆) β
+ C 3
where, D is the Euclidean distance between u and v, ∆ is the
expected variance of distance between u and v considering the
mobility. β is the path loss exponent with 2 ≤ β ≤ 4, and C is a
constant. Expected variance is given by equation (4)
Δ= (Current time - Reply time ) * SN 4
Where Current time is the time at which node u is computing its
transmission power, Reply time is the time at which node u has
received the RREP packet from node v, SN is the speed of
node v.
IV. SIMULATION PARAMETERS AND RESULTS
We evaluated the scenario with 60, 80 and 100 nodes for 30
CBR applications using Qualnet 4.5 simulator. The simulation
parameters are as shown in the table 1 and the scenario in
Figure 1 and Figure 2.
Table 1: Simulation Parameters
Simulation Properties Property Values
Simulation Time 120 Minutes
Terrain-Dimension 1500 X 1500 m2
Traffic type CBR
Mobility model Random Waypoint
Speed 0 - 10 m/s
Pause time 30 second
Radio type 802.11b
Propagation limit -111 dBm
Receiver sencitivity -89
Data rate 2 Mbps
Packet size 512 bytes
Battery model Linear
Initial battery capacity 300 mAh
Figure 1: 60, 80 nodes with 30 CBR applications
Figure 2: 100 nodes with 30 CBR applications
The plots for an average energy consumption in transmit,
receive and idle mode for 60,80 and 100 nodes with 30 CBR
applications are shown in Figures 3 to 11.
Figure 3: 60 nodes with 30 CBR applications in transmit mode.
Figure 4: 60 nodes with 30 CBR applications in receive mode.
0
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EnergyConsumptioninmWh
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3. International Journal of Research and Scientific Innovation (IJRSI) | Volume IV, Issue III, March 2017 | ISSN 2321–2705
www.rsisinternational.org Page 23
Figure 5: 60 nodes with 30 CBR applications in idle mode.
Figure 6 : 80 nodes with 30 CBR applications in
transmit mode.
Figure 7 : 80 nodes with 30 CBR applications in
receive modes.
Figure 8 : 80 nodes with 30 CBR applications in
idle mode.
Figure 9: 100 nodes with 30 CBR applications in transmit
mode.
Figure 10: 100 nodes with 30 CBR applications in receive
mode.
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Mode
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4. International Journal of Research and Scientific Innovation (IJRSI) | Volume IV, Issue III, March 2017 | ISSN 2321–2705
www.rsisinternational.org Page 24
Figure 11: 100 nodes with 30 CBR applications in idle
mode.
It is observed from the above results that as the CBR
connections are increased,there is increase in the RREQ
packets.Thus flooding of more number of RREQ packets at
the receiver and transmitter thus the energy consumption
increases.When CBR connections are less,all the nodes
consume energy only for sensing the channel in idle
mode.When the connection limit is increased,less number of
nodes will be in idle mode results in reduction in the average
energy consumption.
V.CONCLUSION
In this paper we have suggested a route cost metric based on
residual battery power for the path selection in ordered to
achieve the efficient routing avoiding node overutilization.
When the CBR connections are less, the node will not be
overutilized.When the node is overutilized,battery gets drained
which leads to decreased network lifetime.
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EnergyConsumptioninmWh
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Average Energy Consumption in Idle Mode