International Journal of Interactive Mobile Technologies (iJIM) – eISSN: 1865-7923 – Vol. 14, no. 17, 2020


Paper—Performance Analysis of Stationary and Deterministic AODV Model 

Performance Analysis of Stationary and Deterministic 

AODV Model 

https://doi.org/10.3991/ijim.v14i17.16643 

Kothai G(), Poovammal E 
SRM Institute of Science and Technology, Kattangulathur, Tamil Nadu 

kothaig@srmist.edu.in 

Abstract—Vehicular Adhoc Network (VANET) is an emerging technology 

that provides a digital communication among vehicles, persons and Road-Side 

Units (RSU). VANETs are highly vulnerable to cyber-attacks. These cyber-

attacks make a wrong illusion on traffic jam, can inject false information 

regarding traffics and injects large amount of spam messages that disrupts the 

normal functionalities. The main objective of the research work is to implement 

and analyze the different models that help in improving the traffic management. 

The scenarios are simulated, and the performance is analyzed using the 

OMNET++ Simulator. 

Keywords—Roadside Units, Cyberattacks, illusion, VANET, spam. 

1 Introduction 

Vehicular Ad-hoc Network (VANET) is one of the new research challenges in road 

traffic safety, traffic engineering or efficiency, comfort and quality of road travel, 

dynamic topology, frequent disconnection, etc [R1]. It helps in providing safety 

management, traffic management, driver comfort management, maintenance 

management. It also helps in maintaining communication among the group of vehicles 

that form a network. In VANET, communication takes place in two ways. When a 

vehicle directly communicates with other vehicle then it is V2V communication or 

Inter-Vehicular communication [R1, R15]. If a vehicle communicates with the 

infrastructure or roadside unit (RSU) then it is V2I communication [R6]. Some of the 

vehicular applications are Road Safety, Traffic Efficiency and Management, Comfort 

and Infotainment etc [R2]. 

Three basic components of system model are:  

• Trusted Authority (TA) 

• Road-Side Unit (RSU) 

• On-Board Unit (OBU) 

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Paper—Performance Analysis of Stationary and Deterministic AODV Model 

1.1 Trusted Authority 

TA is an authorized centre that provides registration and certification for RSU and 

OBU. It generates group key and signature that are further sent to the RSU in the 

domain [R3]. 

Road-Side Unit: Vehicles are managed and get communicated with other vehicle by 

RSU within a communication range. It also acts as a bridge between trusted authority 

and on-board unit through wired or wireless channel [R3]. 

On-Board Unit: OBU periodically broadcasts the traffic-related information such 

as location, speed, direction to improve the road environment for drivers and 

passengers. To store security information, each vehicle has a temper-proof device 

(TPD) [R3]. 

To improve the road safety and road efficiency, there is various communication 

standards available, which provide the radio access required for the communication 

between the vehicles [R4]. Emergency and warning messages, Interpersonal 

messages, Routing and safety messages and Information and Entertainment messages 

are the four types of messages that help in communicating between the vehicles and 

infrastructure in VANET [R4]. The basic standards for wireless access in VANETs 

are cellular access in vehicular environment (2G/2.5G/3G/4G), dedicated short range 

communication (DSRC), Wireless access in vehicular Environment (WAVE) and 

WIMAX. The various attacks in VANET are Denial of Service attack (DOS), 

Distributed Denial of Service attack (DDOS), Sybil attack, Blackhole attack, Grey 

hole attack, worn hole attack, etc [R5]. VANET uses diverse cryptographical 

algorithms such as MD5, ECC, RSA, SHA1. There are some issues associated with 

these security protocols [R12]. Some routing protocols like AODV helps in detecting 

and preventing the attacks in VANET. The performances are compared between 

different routing protocols such as AODV, DSR and DSDV. It is observed that 

AODV performs better than other routing protocols in different scenarios like saving 

bandwidth and power consumption [R13, R14].  

2 AODV and Mobility Models 

The protocols, agents and other models are provided by the open source model 

library called INET framework for OMNET++ simulation environment [R11]. The 

Adhoc On-Demand Distance Vector (AODV) routing protocol is one of the reactive 

protocols where routes are created on demand [R9]. Instead of maintaining up-to-date 

route information, the AODV routing protocol broadcasts the messages over the 

network for route discovery process [R3]. This model undergoes Route Discovery and 

Route Maintenance. Route Discovery is done through Route REQUEST (RREQ) and 

Route REPLY (RREP) and Route Maintenance is done through Route ERROR 

(RERR). 

When a source node wants to send a message to the destination node at first it 

checks in the Route Table and if the route exists then the packet is delivered through 

the route [R3]. If the route does not exist, then Source node broadcasts Route Request 

(RREQ) to the intermediate nodes. The broadcast Route Request consists of Source 

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Paper—Performance Analysis of Stationary and Deterministic AODV Model 

Address, Request ID, Source Sequence Number, Destination Address, Destination 

Sequence Number and Hop Count [R4, R10].  

When the intermediate node receives the RREQ message it has two possibilities. If 

the node does not have a Valid Route to destination, then it forwards the request 

message to all other nodes [R4]. If the node has a valid route, then it Unicast the 

Route Reply (RREP) message. This RREP message contains Source Address, 

Destination Address, Destination Sequence Number, Hop Count and Lifetime [R4]. 

When the route request message is received multiple times, the duplicate copies will 

be discarded, by comparing the Broadcast ID and Source ID pairs.  

The previous nodes broadcast ID is stored when RREQ is forwarded. If the Route 

Reply is not received before time expires, the entry will be deleted [R4]. All the nodes 

in the network will monitor the neighbourhood nodes and if any active route gets lost 

then it will send the Route Error Message (RERR) to all other nodes in the network 

[R4]. The active module called simple modules and grouping of simple modules 

called compound module are the two types of modules that helps in communicating 

with message passing [R7]. The position and orientation are described by mobility 

models in a 3D Euclidean coordinate system [R8]. The two different mobility models 

are single or group mobility models [R8]. The mobility model that describes the 

motion of entities independent to each other is known as single mobility model. A 

node undergoing motion and the members of the group are dependent to each other is 

provided by group mobility model [R8]. 

The AODV model is categorized as Stationary model and Mobility model. The 

Stationary model is classified as Stationary Mobility, Static Grid Mobility, Static 

Concentric Mobility. The Classification of Mobility model is shown in the below 

figure 1. 

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Paper—Performance Analysis of Stationary and Deterministic AODV Model 

 

Fig. 1. Classification of Mobility Models 

3 Analysis of Results 

The simulation output of the AODV Stationary model and AODV Mobility model 

for fixed number of nodes as 20. The experiment run for 12 seconds and the 

calculated values based on the node shut down and start up time is tabulated are 

tabulated. 

3.1 Stationary model 

The Stationary models can define only the position and orientation but not the 

motion [R8]. The different stationary models are Stationary Mobility model that 

provides the positioning of nodes in deterministic and random manner [R8]. In a 

rectangular grid if mobility models are placed then it is Static Grid Mobility Model 

and if several models are placed in a set of Concentric Circles then it is Static 

Concentric Mobility [R8]. 

 

 

 

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Paper—Performance Analysis of Stationary and Deterministic AODV Model 

Table 1: Calculated values for Stationary model 

No of Events 

No of Nodes 20 

Time Taken When 

1 Node Shuts Down 
5 Nodes Shuts 

Down 

10 Nodes Shuts 

Down 

15 Nodes Shuts 

Down 

200 3.19 3.19 3.19 3.19 

400 3.19 3.19 3.19 3.2 

600 3.2 3.2 3.2 3.2 

800 3.2 4.19 4.19 4.19 

1000 5.19 6 6 6.19 

1200 6.19 7.19 7.19 8.19 

1400 8.19 9.19 9.19 10.19 

1538 8.5 10.19 10.19 12 

1600 9.19 11 11.19  

1678 10 11.19 12  

1713 10.5 12   

1800 11.19    

1924 12    

 

 

Fig. 2. Stationary Model 

The Table I shows that when the nodes in a network are in stationary model, there 

are 1924 events occurred by 12 seconds even after one node shutdown from the 

Time in 

(sec) 

No. of Events 

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Paper—Performance Analysis of Stationary and Deterministic AODV Model 

network. If five nodes shutdown then total number of events is 1713. If the ten and 

fifteen nodes shutdown then total number of events are 1678 and 1538. In a network 

when there is increase in number of nodes shutdown then total number of events gets 

decreases in this model. 

3.2 Deterministic models 

Deterministic mobility models are models that help in describing the motion using 

non-random mathematical models. The various deterministic mobility models are 

Linear Mobility helps in moving the nodes with constant speed and acceleration in 

linear manner. If the nodes move around circular and rectangular that is parallel to 

XY plane with constant speed, then it is Circle Mobility and rectangle mobility 

model. If the node orients towards the position of any other mobility model, then it is 

facing mobility model [R8]. 

Linear mobility model: The above Table II shows that when the nodes in a 

network are in linear mobility model there are 8523 events occurs by 12 seconds even 

after one node shutdown in the network. If five nodes shutdown then total number of 

events is 6780. If the ten and fifteen nodes shutdown then total number of events are 

6354 and 5589. In a network when there is increase in number of nodes shutdown 

then total number of events gradually gets decreases in this model.  

Table 2: Calculated values for Linear Deterministic Model 

No of Events 

No of Nodes 20 

Time Taken When 

1 Node Shuts Down 
5 Nodes Shuts 

Down 

10 Nodes Shuts 

Down 

15 Nodes Shuts 

Down 

1000 3.19 3.19 3.19 3.19 

2000 5.19 5.19 5.19 5.19 

3000 6 6.19 6.19 6.2 

4000 8.2 8.2 8.2 8.5 

5000 8.6 9.19 9.19 9.6 

5589 9 11 11.19 12 

6000 11.2 11.2 11.2  

6354 11.25 11.2 12  

6780 11.3 12   

7000 11.52    

8000 11.52    

8523 12    

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Paper—Performance Analysis of Stationary and Deterministic AODV Model 

 

 

Fig. 3. Linear Deterministic Mod 

Circle mobility mode: From table III it is known that when the all the nodes in a 

network are in Circle Mobility model the total number of events occurred at one node, 

five nodes, ten and fifteen nodes shutdown then total number of events are lesser 

when compared to Linear Deterministic Mobility model. 

Table 3: Calculated values for Circle Deterministic model 

No of Events 

No of Nodes 20 

Time Taken When 

1 Node Shuts Down 
5 Nodes Shuts 

Down 

10 Nodes Shuts 

Down 

15 Nodes Shuts 

Down 

1000 3.19 3.19 3.19 3.19 

2000 4 4.19 4.19 4.4 

3000 6.8 7.19 7.19 7.6 

4000 9.2 9.19 9.2 9.6 

4642 9.2 9.5 10.19 12 

5000 9.2 10.3 11.1  

5361 10 11.2 12  

5558 10.5 12   

6000 11.19    

6377 12    

Time in 

(sec) 

No. of Events 

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Paper—Performance Analysis of Stationary and Deterministic AODV Model 

 

 

Fig. 4. Circle Deterministic Mobility Model 

3.3 Combining deterministic models  

Table 4: Calculated values for Deterministic model 

No of Events No of Nodes 20 

Time Taken When 

1 Node Shuts Down 5 Nodes Shuts 

Down 

10 Nodes Shuts 

Down 

15 Nodes Shuts 

Down 

1000 3.2 3.2 3.2 3.2 

2000 5.8 6 6 6.19 

3000 6.5 6.62 6.6 6.5 

4000 7 7 7.01 8.5 

5000 7.01 7.4 8 10.8 

5273 7.09 8.01 8.3 12 

6000 7.19 9.52 10  

7000 7.52 10 11.3  

7154 7.54 10 12  

8000 8.19 10.64   

8452 8.5 12   

9000 9.52    

10000 10    

11000 10.64    

12000 11.6    

12114 12    

Time in 

(sec) 

No. of Events 

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Paper—Performance Analysis of Stationary and Deterministic AODV Model 

 

 

Fig. 5. Linear and Circle Deterministic Mobility Model 

In table IV, the linear and Circle Deterministic Models are combined, there are 

12114 events occurred by 12 seconds even after one node shutdown from the 

network. If five nodes, ten and fifteen nodes shutdown then total number of events are 

8452, 7154 and 5273. By combining two Deterministic Models there is dramatic 

increase in number of events than the linear and circle models. 

3.4 Static and Deterministic model 

Table 5: Calculated for static and Mobility model 

No of Events 

No of Nodes 20 

Time Taken When 

1 Node Shuts Down 5 Nodes Shut Down 
10 Nodes Shuts 

Down 
15 Nodes Shut 

Down 

1000 3.2 3.2 3.2 3.2 

2000 3.52 3.52 3.52 3.52 

3000 3.99 3.99 3.99 3.53 

4000 4 4 4 5.7 

5000 4.6 4.64 4.64 8 

6000 5 5 5 10.3 

6704 5.8 5.19 5.19 12 

7000 6.1 5.21 5.21  

8000 8.19 5.62 5.62  

9000 10.3 6 6  

9559 12 6.4 6.4  

Time in 

(sec) 

No. of Events 

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Paper—Performance Analysis of Stationary and Deterministic AODV Model 

10000  6.52 6.5  

11000  6.64 6.64  

12000  7.52 7.52  

13000  9.2 9.5  

14000  11.19 11.5  

14594  11.52 12  

15000  11.52   

15721  12   

 

 

Fig. 6. Static and Mobility Model 

In table V, the Stationary and Deterministic Models are combined, there are 9559 

events occurred by 12 seconds even after one node shutdown from the network. The 

source and destination node are in stationary model and all other eighteen nodes are in 

Circular Deterministic Models.  If five nodes, ten and fifteen nodes shutdown then 

total number of events are 15721, 14594 and 6704. By combining two Different 

AODV Models there is dramatic increase in number of events during five and ten 

nodes shutdown than one node shutdown. But there is decrease in number of events 

for fifteen nodes shutdown when compared to one node shut down.  

No. of Events 

Time in 

(sec) 

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Paper—Performance Analysis of Stationary and Deterministic AODV Model 

4 Conclusion 

In this paper the analysis of performance of Stationary model and Deterministic 

Mobility models are done using AODV reactive routing protocol. The simulation is 

carried out in OMNET++ Simulator and the results are presented. After the analysis, 

we observed that combining Stationary and Deterministic model gives 20% higher 

performance when compared to other models in terms of number of events and time 

for more than one node shutdown. By combining two Deterministic Models gives 

10% higher performance when compared to other models in terms of number of 

events and time for one node shutdown. The work can be extended for detecting the 

black hole attack by finding the average end to end delay, packet delivery ratio and 

throughput. 

5 References 

[1] Sabih ur Rehman, M. Arif Khan, Tanveer A. Zia, Lihong Zheng,” Vehicular Ad-Hoc 

Networks (VANETs) - An Overview and Challenges”. Journal of Wireless Networking 

and Communications 2013, doi: 10.5923/ jjwnc.20130303.02, pp 3(3): 29-38. 

[2] Anna Maria Vegni, Mauro Biagi and Roberto Cusani,” Smart Vehicles, Technologies and 

Main Applications in Vehicular Ad hoc Networks”. INTECH Open Science |Open Minds 

https://doi.org/10.5772/55492 

[3] M.Danya Priyadharshini, Christo Ananth,” A Secure Hash Message Authentication Code 

to Avoid Certificate Revocation List Checking In Vehicular Adhoc Networks”. 

International Journal of Applied Engineering Research, ISSN 0973-4562 Vol. 10 No.2 

(2015), pp. 1250-1254. 

[4] Vinita Jindal, Punam Bedi,” Vehicular Ad-Hoc Networks: Introduction, Standards, 

Routing Protocols and Challenges”. IJCSI International Journal of Computer Science 

Issues, Volume 13, Issue 2, March 2016 ISSN (Print): 1694-0814 | ISSN (Online): 1694-

0784, https://doi.org/10.20943/01201602.4455. 

[5] Manpreet kaur, Nitin Bhagat,” A Review on Various Attacks in VANET”. IJCAT - 

International Journal of Computing and Technology, Volume 3, Issue 5, May 2016, ISSN: 

2348 – 6090, pp:292-294. 

[6] I NET Framework, https://inet.omnetpp.org/docs/ users-guide/ch-introduction.html#what-

is-inet-framework. 

[7] OMNET ++ Simulation Manual, Https://doc.omnetpp.org/omnetpp/manual/. 

[8] Node Mobility, Https://inet.omnetpp.org/docs/users-guide/ch-mobility.html 

[9] Arvind Kumar Shukla, C.K.Jha, Nitin Sexena, Sanjay Kumar Biswash,” The analysis of 

AODV, based on mobility model”. 3rd IEEE International Advance Computing Conference 

(IACC), doi:10.1109/iadcc.2013.6514266, 2013, pp:440-443. https://doi.org/10.1109/ 

iadcc.2013.6514266 

[10] Prashant Kumar Maurya, Gaurav Sharma, Vaishali Sahu, Ashish Roberts, Mahendra 

Srivastava,” An Overview of AODV Routing Protocol”. International Journal of Modern 

Engineering Research (IJMER), vol.2, Issue.3, May-June 2012, ISSN: 2249-6645, pp:728-

732. 

[11] Halabi Hasbullah, Irshad Ahmed Soomro, Jamalul-lail Ab Manan,” Denial of Service 

(DOS) Attack and Its Possible Solutions in VANET”. World Academy of Science, 

iJIM ‒ Vol. 14, No. 17, 2020 43

10.5923/%20jjwnc.20130303.02,%20pp%203(3):%2029-38.
https://doi.org/10.5772/55492
https://doi.org/10.20943/01201602.4455
https://inet.omnetpp.org/docs/%20users-guide/ch-introduction.html%23what-is-inet-framework.
https://inet.omnetpp.org/docs/%20users-guide/ch-introduction.html%23what-is-inet-framework.
https://doc.omnetpp.org/omnetpp/manual/
https://inet.omnetpp.org/docs/users-guide/ch-mobility.html
https://doi.org/10.1109/iadcc.2013.6514266
https://doi.org/10.1109/iadcc.2013.6514266


Paper—Performance Analysis of Stationary and Deterministic AODV Model 

Engineering and Technology International Journal of Electronics and Communication 

Engineering, vol:4 No.5,2010, pp:813-817. 

[12] Durga R, Poovammal E.,” Generation of RAESSES Hash Function for Medical 

Blockchain Formation Based on High Dynamic Chaotic Systems.” International Journal of 

Advanced Science and Technology, Issue Vol. 29 No. 06 (2020), 29(06), 8427-8440. 

[13] Mohammad Alnabhan, Mahmoud Alshuqran, Mustafa Hammad, Mohammad Al 

Nawayseh, “Performance Evaluation of Unicast Routing Protocols in MANETs – Current 

State and Future Prospects”. International Journal of Interactive Mobile Technologies 

(iJIM), Vol:11 No.01, https://doi.org/10.3991/ijim.v11i1.6295 

[14] Mada’ Abdel Jawad, Saeed Salah, Raid Zaghal,” DSDV Extension to Enhance the 

Performance of Ad Hoc Networks in High Diverse-Velocity Environments”. International 

Journal of Interactive Mobile Technologies (iJIM), Vol: 14 No.06, https://doi.org/10. 

3991/ijim.v14i06.11889. 

[15] Petros Mashwama, Stephen Gbenga Fashoto, Elliot Mbunge, Simanga Gwebu, 

“Development of a Mobile Inter-Vehicular Communication System Based on Gossip 

Algorithm”. International Journal of Interactive Mobile Technologies (iJIM), Vol:14 

No.11, https://doi.org/10.3991/ijim.v14i11.12949 

6 Authors 

G. Kothai is a Research Scholar in the Department of Computer Science and 

Engineering at SRM Institute of Science and Technology. She obtained her B.E. 

Degree in Computer Science and Engineering at Sasurie Academy of Engineering in 

the year 2016 and M.E degree in Computer Science and Engineering from 

Coimbatore Institute of Technology. Her research interests include Vehicular adhoc 

network security, Cyber Security, Network security and Machine Learning. Email: 

kothaig@srmist.edu.in 

Dr. E. Poovammal is a Professor in the Department of Computer Science and 

Engineering at SRM Institute of Science and Technology. She joined in SRM in the 

year 1996. Before joining SRM, she worked in industry for five years. She obtained 

her B.E. Degree in Electrical and Electronics Engineering from Madurai Kamaraj 

University in the year 1990, M.E degree in Computer Science and Engineering from 

Madras University and Ph.D. degree in Computer Science and Engineering from 

SRM University. Her research interests include Big Data Analytics and Machine 

Learning. She is certified as Adjunct Faculty by Institute of software Research, 

Carnegie Mellon University, Pittsburgh, USA and served for 4 years. She has 

published more than 40 referred journals and presented in various international and 

national conferences. She is fellow member of IE (I) and active member of 

professional bodies such as IEEE, IET, ACM, ISCA, ISTE. Email: 

poovamme@srmist.edu.in 

Article submitted 2020-06-26. Resubmitted 2020-07-25. Final acceptance 2020-07-26. Final version 

published as submitted by the authors.  

44 http://www.i-jim.org

https://doi.org/10.3991/ijim.v11i1.6295
https://doi.org/10.3991/ijim.v14i06.11889
https://doi.org/10.3991/ijim.v14i06.11889
https://doi.org/10.3991/ijim.v14i11.12949
mailto:poovamme@srmist.edu.in