Abstract— In Mobile Ad hoc Networks (MANETs) nodes are free to move arbitrarily with different speeds, which makes the network topology change randomly and unpredictably. The mobility models give the movement pattern of the nodes w.r.t. their direction, location and speed over time. Some of these models depict real life scenarios. This paper analyses the energy consumption of our previous proposed energy efficient algorithms viz. energy aware AODV (EA-AODV) and Optimized Energy Aware Routing (OEAR) scheme, under various mobility models. The mobility models considered in the paper are random walk, random waypoint, column based, reference point group mobility model. Simulation results obtained in NS2.34 show that OEAR has better energy consumption.

Index Terms— energy aware, routing schemes, mobility model,MANET

I. INTRODUCTION

obile Ad hoc Network (MANET) is an autonomous system of mobile nodes connected by wireless link that

can communicate with each other without the aid of any centralized authority [1]. The network is maintained by the end users rather than a single control point. This is because each node acts as a sending and forwarding node. The network topology in MANETs may change dynamically in an unpredictable manner since nodes are free to move.

Effective utilization of network energy becomes one of the major goals of routing protocols, as battery life of nodes is limited. Also, while developing any routing protocol, determining the performance of protocol under different mobility models is an important issue in MANETs. The mobility models mimic the movement behavior of actual users.This paper attempts to study the energy consumption pattern of different mobility models categorized under entity based and group mobility models. Two energy aware routing protocols: Energy Aware AODV routing (EAR) and

Dr. Seema Verma is working as Associate Professor at Banasthali University, Banasthali, INDIA. (e-mail: seemaverma3@ yahoo.com).

Pinki Nayak is with Amity School of Engineering & Technology, New Delhi, INDIA. Currently, she is also a research student at Bansthali University, Banasthali, INDIA. (e-mail: pinki_dua@yahoo.com)

Prof. Rekha Agarwal is the Director of Amity School of Engineering & Technology, New Delhi, INDIA. (e-mail: rarun96@yahoo.com).

Optimized Energy Aware Routing (OEAR) have been compared for different mobility models. The rest of the paper is organized as follows. Section 2 presents an overview of the various mobility models used in this paper. Section 3 gives the brief discussion on the energy aware routing algorithms. Section 4 includes the simulation environment setup used in NS-2 simulator. The simulation results are explained in section 5. Finally, section 6 gives conclusions.

II. MOBILITY MODELS

A. Random Walk Mobility ModelIt is the simplest entity based mobility model based on

Brownian motion and generates completely random movement patterns. In this mobility model, a mobile node moves from its current location to a new location by randomly choosing a direction and speed in which to travel (Fig. 1).The mobile node is initially placed in a random location inthe simulation area, and then moved in a randomly chosen direction between [0, 2pi] at a random speed between [0, Maxspeed] [2], [3].

B. Random Waypoint Mobility ModelRandom Waypoint Model [4] is the most widely used and studied mobility model. Movement of people in a cafeteria, airport, cinema hall or mall, and movement of nodes in a conference are some of its practical applications. The threeparameters used are Vmax, T, Vi; where the node velocity is uniformly distributed from 0 to Vmax, T is the pause time and Vi is the direction or advance vector. In this mobility model,the node randomly chooses a destination, called waypoint, and moves towards it in a straight line with constant velocity, which is selected randomly from 0 to Vmax. After reaching the waypoint, the node waits for the pause time and then repeats the same procedure (Fig. 2). The topology of the network is stable in low velocity with long pause time. It is highly dynamic for high velocity and small pause time. Thus by varying these two parameters, different mobility scenarios can be generated.

C. Reference Point Group Mobility ModelRPGM [5] is a group mobility model where nodes move in

a group in coordinated manner. Its parameters are Vmax, T, Rmax, Vi; where Vmax is the maximum speed, Rmax is the

Performance Analysis of Energy Aware Routing Schemes under Various Mobility Models

Seema Verma, Pinki Nayak, and Rekha Agarwal

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978-1-4673-4866-9/13/$31.00 ©2013 IEEE

International conference on Communication and Signal Processing, April 3-5, 2013, India

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Fig. 1. Traveling pattern of a MN using the 2-D Random Walk Mobility Model

maximum allowable range within the group from group logical center, T is pause time and Vi is the advance direction vector. The group motion/advance behavior is determined by logical center of each group called group leader. Initially, each member of the group is uniformly distributed in the neighborhood of the group leader. Subsequently, at each instant, every node has a speed and direction that is derived by randomly deviating it from the group leader’s position. RPGM can be used in simulating group movements in scenarios such as military battlefield communications, rescue workers in a disaster relief operation.

D. Column Based Mobility ModelA Column Mobility Model [6] is derived from RPGM. The

main difference is that groups in CMM move in columns and not in random fashion. The movement of tanks in an exercise area in military battle field scenario or movement of cars on roads, etc, can be realized through this model.

III. ENERGY AWARE ROUTING SCHEMES

The earlier energy aware routing schemes proposed by us, considered in this paper are as follows:

A. Energy Aware Routing (EA-AODV)This routing scheme [7] is based on AODV. It finds energy

efficient route by varying the transmission range of the nodes. Each node sets its transmission range to the most nearest node present after receiving the route replies from all the nodes having path to destination. The route request RREQ is sent at common transmission range of 250m.

B. Optimized Energy Aware Routing (OEAR)OEAR [8] selects nodes possessing more than 50% of

battery life and less number of buffered packets. Energy of thenetwork is further optimized by using variable transmission range between two selected nodes. Friis transmission equation is used to calculate the distance between two nodes.

Fig. 2. Traveling pattern of an MN using the 2-D Random WayPoint Mobility Model

IV. SIMULATION ENVIRONMENT

Simulations are performed using Network Simulator (NS-2.34). The simulation setup consists of flat topology covering an area of 1000 * 1000 m2 and a test bed of 50 nodes randomly and uniformly distributed in the entire area.. All random scenarios have been generated for varying speeds with different pause times. Traffic sources are chosen as UDP with a packet size of 512 bytes. The simulated values used for modeling network interface card is based on the 914 MHz Lucent WaveLan direct sequence spread spectrum radio model. It uses a bit rate of 2Mbps and radio transmission range of 250m. The IEEE 802.11 distributed coordinated function with CSMA/CA is used as the underlying MAC protocol. For generating the scenarios, the mobility scenariogeneration tool, BonnMotion was used.

TABLE ISIMULATION SETUP

Parameter Value

Number of nodes 50

Simulation Time 300s

Pause Time 5s

Environment Size 1000m X 1000m

Traffic Type CBR

Packet Size 512bytes

Initial Energy of Node 100 Joules

Transmission Power (for RREQ) 5 W

Reception Power Utilized 1W

Simulator NS-2.34

Antenna Type Omni directional

MAC type IEEE 802.11

Agent

User Datagram Protocol

(UDP)

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V. RESULT ANALYSIS This section gives the detailed simulation results of the

two energy efficient routing protocols i.e. EAR and OEAR compared under different mobility models. The performance metric used for comparison is the average energy consumption. Average energy consumed is defined as the average of the sum of the energy consumed at each transmitting and receiving node in the network.

The average energy consumed is evaluated for different node speeds. The mobility speed of nodes is varied from 5 m/sec to 30m/sec in steps of 5. As seen from Figure 3, the energy consumption increases with increase in speed of nodes. The EAR protocol consumes more energy under column mobility model. The energy consumption changes from 63 J to 70 J as speed increases from 5 m/sec to 30 m/sec.

Five groups were considered for simulations. Network connectivity was to be maintained in these groups. Since there are multiple paths in a group, energy consumption is more for EAR. EAR consumes minimum energy under

Fig. 3. Average Energy Consumed (J) with Mobility (m/sec) for EAR

Fig. 4. Average Energy Consumed (J) with Mobility (m/sec) for Optimized Energy Aware Routing Scheme

Fig. 5. Average Energy Consumed (J) with Mobility (m/sec) for Random Walk Model

random waypoint model. Average energy consumed becomes same for all mobility models at a speed of 30 m/sec.

Fig. 4 gives the average energy consumed for optimized energy aware routing (OEAR). As shown, under RPGM mobility model, OEAR has more energy consumption than column mobility model. These group mobility models were simulated for five groups establishing communication among them. OEAR performs better under random walk mobility model. The energy consumption is steady for OEAR at 46 J to 50 J under random walk model.

Figures 5, 6, 7, 8 give the comparison of average residual energy with speed for EAR and OEAR under random walk, random waypoint, community based and RPGM model respectively. Under all the mobility models, OEAR outperforms EAR. Energy consumption is less in OEAR as the algorithm considers nodes with high remaining power and the internal buffer of the nodes while selecting the route. EAR on the other hand only varies the transmission range of the nodes.

VI. CONCLUSION Mobility models play an important role in emulating real life scenarios. The paper evaluates the performance of two energy efficient routing protocols, energy aware AODV and OEAR for different mobility models. The mobility models are compared by varying the speed of the nodes. Simulation results show that energy consumption is more under column based model for EAR and RPGM for OEAR. On comparison of the two protocols, OEAR shows better performance in terms of energy consumption over EAR under all mobility models except RPGM. For RPGM, EAR has low energy consumption. Future work includes the energy consumption of these mobility models by varying node density, traffic load, number of sources, network size etc.

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Fig. 6. Average Energy Consumed (J) with Mobility (m/sec) for Random Waypoint Model

Fig. 7. Average Energy Consumed (J) with Mobility (m/sec) for Community Based Model

Fig. 8. Average Energy Consumed (J) with Mobility (m/sec) for RPGM Model

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[3] Mohd Izuan, Mohd Saad, Zuriati Ahmad and Zukarnain, “Performance Analysis of Random-Based Mobility Models in MANET Routing Protocol”, European Journal of Scientific Research, vol. 32, no. 4, pp.444-454, 2009.

[4] G. Jayakumar and G. Ganapathi, “Reference point group mobility and random waypoint models in performance evaluation of MANET routing protocols”, Journal of Computer Systems, Networks, and Communications, Article ID 860364, 2008.

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