International Journal of Research and Scientific Innovation (IJRSI) | Volume IV, Issue III, March 2017 | ISSN 2321–2705
Performance of CBR Traffic on Node Overutilization in MANETs Shridhar Kabbur
Rajashri Y M
Department of ECE Global Academy of Technology Bengaluru-560098
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.
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.
Key Words - MANET, node overutilization, CBR, network lifetime.
III. ENERGY EFFICIENT ROUTING PROTOCOL
I. INTRODUCTION
I
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
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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:
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International Journal of Research and Scientific Innovation (IJRSI) | Volume IV, Issue III, March 2017 | ISSN 2321–2705 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.
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.
IV. SIMULATION PARAMETERS AND RESULTS
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 512 bytes Linear
Initial battery capacity
300 mAh
35 30 25 20 15 10 5 0 5
10
20
25
30
No. of CBR Application Figure 3: 60 nodes with 30 CBR applications in transmit mode.
Average Energy Consumption in Receive Mode Energy Consumption in mWh
Packet size Battery model
Average Energy Consumption in Transmit Mode Energy Consumption in mWh
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.
80 70 60 50 40 30 20 10 0 5
10
20
25
30
No. of CBR Application Figure 1: 60, 80 nodes with 30 CBR applications
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Figure 4: 60 nodes with 30 CBR applications in receive mode.
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International Journal of Research and Scientific Innovation (IJRSI) | Volume IV, Issue III, March 2017 | ISSN 2321â&#x20AC;&#x201C;2705 Average Energy Consumption in Idle Mode
250 200 150 100 50 0 5
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30
Energy Consumption in mWh
Energy Consumption in mWh
Average Energy Consumption in Idle Mode
250 200 150 100 50 0 5
No. of CBR Application Figure 5: 60 nodes with 30 CBR applications in idle mode.
20
25
30
Figure 8 : 80 nodes with 30 CBR applications in idle mode.
Average Energy Consumption in Transmit Mode
Average Energy Consumption in Transmit Mode
30 25 20 15 10 5 0 5
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No. of CBR Application
Energy Consumption in mWh
Energy Consumption in mWh
10
No. of CBR Application
25 20 15 10 5 0 5
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No. of CBR Application Figure 6 : 80 nodes with 30 CBR applications in transmit mode. Figure 9: 100 nodes with 30 CBR applications in transmit mode.
80 70 60 50 40 30 20 10 0 5
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No. of CBR Application Figure 7 : 80 nodes with 30 CBR applications in receive modes.
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Average Energy Consumption in Receive Mode Energy Consumption in mWh
Energy Consumption in mWh
Average Energy Consumption in Receive Mode
100 80 60 40 20 0 5
10
20
25
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No. of CBR Application Figure 10: 100 nodes with 30 CBR applications in receive mode.
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International Journal of Research and Scientific Innovation (IJRSI) | Volume IV, Issue III, March 2017 | ISSN 2321–2705
Energy Consumption in mWh
Average Energy Consumption in Idle Mode
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. REFERENCES
250 200 150 100 50 0 5
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No. of CBR Application
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.
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