Performance analysis of OLSR, DSDV and AODV protocols in a MANET Network

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portada volumen 33 numero 2
PDF (Spanish) MHT (Spanish)
Published : 2021-11-26
DOI : https://doi.org/10.37815/rte.v33n2.829
Keywords :
delay, heatmap, NS3, PDR, throughput
Christian Quinde
Paul Astudillo
Santiago Gonzalez
Abstract

This paper presents an analysis and comparison between the proactive routing protocols OLSR and DSDV and the reactive routing protocol AODV in a MANET network. Two scenarios were defined, the first one representing a soccer team attacking and the second one defending. To simulate each scenario the area of movement of the nodes (players) was varied. For this purpose, an investigation was carried out on the problems presented by these routing algorithms for Ad Hoc networks in different environments. In this way, an overview of the strategies and solutions that currently exist is obtained. Based on the information gathered, it is proposed to perform a simulation using NS3 in order to obtain results that resemble reality. The comparison is made based on throughput, PDR and Delay metrics. In each simulation, parameters such as node velocity and initial position are adjusted according to the behaviour of a real soccer player. The nodes move in a random trajectory within the specific area and one of them sends data to a fixed server node located at the edge of the area where the nodes move, simulating the bench where the receiver is located. The transmitted traffic is characterized to simulate realistic biometric data. From the results, it is concluded that AODV and DSDV have better performance than OLSR and the optimum transmission interval is 20 seconds. In addition, with a transmit power of 10 dBm, 100% throughput is guaranteed at the receiver.

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How to Cite
Quinde Romero, C., Astudillo Picon, P., & Gonzalez Martinez, S. (2021). Performance analysis of OLSR, DSDV and AODV protocols in a MANET Network. Revista Tecnológica - ESPOL, 33(2), 43-57. https://doi.org/10.37815/rte.v33n2.829
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Author Biographies

Christian Quinde

Christian Quinde obtained a Bachelor's degree in General Sciences at the Alborada Educational Center, Cuenca, Ecuador, in 2013. Later, he began studying Electronics and Telecommunications Engineering at the University of Cuenca. He is currently studying the last semester of the degree and is part of the board of the IEEE student branch at the University of Cuenca. His areas of interest are networking, wireless networks and radio frequency.

Paul Astudillo

Paul Astudillo obtained the title of Consumer Electronics Industrial Technician at the Daniel Córdova Toral school, Cuenca, Ecuador, in 2014. Later, he began studying Electronics and Telecommunications Engineering at the University of Cuenca. He is currently studying the last semester of the degree and is part of the board of the IEEE student branch at the University of Cuenca. His areas of interest are networking and programming.

Santiago Gonzalez

Santiago Gonzalez obtained the title of Electronic Engineer from the Universidad Politecnica Salesiana (UPS), Cuenca, Ecuador, in 2006 and the title of Master in Advanced Computer Technologies, by the Universidad Castilla-La Mancha, Ciudad Real, Spain, 2009. In 2013 , began working to obtain his doctorate degree in the Multimedia Communications research group (COMM) of the Institute of Telecommunications and Multimedia Applications (iTEAM) of the UPV. In 2017 he obtained his PhD in Telecommunications from the UPV. Currently, he works as a professor at the School of Electronic Engineering and Telecommunications of the University of Cuenca (Ecuador). His areas of interest are energy efficiency and QoS in ad hoc wireless networks.

References

Akbar, M. S., Yu, H., & Cang, S. (2016). Delay, Reliability, and Throughput Based QoS Profile: A MAC Layer Performance Optimization Mechanism for Biomedical Applications in Wireless Body Area Sensor Networks. Journal of Sensors, 2016. https://doi.org/10.1155/2016/7170943

Al-Dhief, F. T., Sabri, N., Salim, M. S., Fouad, S., & Aljunid, S. A. (2018). MANET Routing Protocols Evaluation: AODV, DSR and DSDV Perspective. MATEC Web of Conferences, 150, 06024. https://doi.org/10.1051/matecconf/201815006024

Antonio Durá Vaquera, J. (n.d.). Revisión Bibliográfica: Entrenamiento SAQ (speed, agility, quickness) en fútbol.

Bai, Y., Mai, Y., & Wang, N. (2017, June 7). Performance comparison and evaluation of the proactive and reactive routing protocols for MANETs. Wireless Telecommunications Symposium. https://doi.org/10.1109/WTS.2017.7943538

Beitelspacher, S., Besher, K. M., & Zamshed Ali, M. (2020, June 1). Sensor Driven Priority Routing of Health Care Data Packet in IoT Network. IEEE World Forum on Internet of Things, WF-IoT 2020 - Symposium Proceedings. https://doi.org/10.1109/WF-IoT48130.2020.9221478

Besher, K. M., Beitelspacher, S., Nieto-Hipolito, J. I., & Ali, M. Z. (2020). Sensor Initiated Healthcare Packet Priority in Congested IoT Networks. IEEE Sensors Journal, 1–1. https://doi.org/10.1109/jsen.2020.3012519

Campanile, L., Gribaudo, M., Iacono, M., Marulli, F., & Mastroianni, M. (2020). Computer network simulation with ns-3: A systematic literature review. Electronics (Switzerland), 9(2), 1–25. https://doi.org/10.3390/electronics9020272

Conti, M., & Giordano, S. (2014). Mobile ad hoc networking: Milestones, challenges, and new research directions. IEEE Communications Magazine, 52(1), 85–96. https://doi.org/10.1109/MCOM.2014.6710069

Gamess, E., & Russoniello, A. (2018). Evaluation of Different Routing Protocols for Mobile Ad-Hoc Networks in Scenarios with High-Speed Mobility. I. J. Computer Network and Information Security, 10, 46–52. https://doi.org/10.5815/ijcnis.2018.10.06

González, S., Castellanos, W., Guzmán, P., Arce, P., & Guerri, J. C. (2016). Simulation and experimental testbed for adaptive video streaming in ad hoc networks. Ad Hoc Networks, 52, 89–105. https://doi.org/10.1016/j.adhoc.2016.07.007

Hu, J., Wang, J., & Xie, H. (2020). Wearable bracelets with variable sampling frequency for measuring multiple physiological parameter of human. Computer Communications, 161, 257–265. https://doi.org/10.1016/J.COMCOM.2020.07.043

Kos, A., Milutinović, V., & Umek, A. (2019). Challenges in wireless communication for connected sensors and wearable devices used in sport biofeedback applications. Future Generation Computer Systems, 92, 582–592. https://doi.org/10.1016/j.future.2018.03.032

Külah, E., & Alemdar, H. (2020). Quantifying the value of sprints in elite football using spatial cohesive networks. Chaos, Solitons and Fractals, 139, 110306. https://doi.org/10.1016/j.chaos.2020.110306

Kurniawan, A., Kristalina, P., & Hadi, M. Z. S. (2020). Performance Analysis of Routing Protocols AODV, OLSR and DSDV on MANET using NS3. IES 2020 - International Electronics Symposium: The Role of Autonomous and Intelligent Systems for Human Life and Comfort, 199–206. https://doi.org/10.1109/IES50839.2020.9231690

Lamaarti, F., Arafsha, F., Hafidh, B., & El Saddik, A. (2019). Automated Athlete Haptic Training System for Soccer Sprinting. Proceedings - 2nd International Conference on Multimedia Information Processing and Retrieval, MIPR 2019, 303–309. https://doi.org/10.1109/MIPR.2019.00061

Li, R. T., Kling, S. R., Salata, M. J., Cupp, S. A., Sheehan, J., & Voos, J. E. (2016). Wearable Performance Devices in Sports Medicine. In Sports Health (Vol. 8, Issue 1, pp. 74–78). SAGE Publications Inc. https://doi.org/10.1177/1941738115616917

Li, S., Zhang, B., Fei, P., Shakeel, P. M., & Samuel, R. D. J. (2020). Computational efficient wearable sensor network health monitoring system for sports athletics using IoT. In Aggression and Violent Behavior (p. 101541). Elsevier Ltd. https://doi.org/10.1016/j.avb.2020.101541

Lloret, J., Garcia, M., Catala, A., & Rodrigues, J. J. P. C. (2016). A group-based wireless body sensors network using energy harvesting for soccer team monitoring. International Journal of Sensor Networks, 21(4), 208–225. https://doi.org/10.1504/IJSNET.2016.079172

Massard, T., Eggers, T., & Lovell, R. (2018). Peak speed determination in football: is sprint testing necessary? Science and Medicine in Football, 2(2), 123–126. https://doi.org/10.1080/24733938.2017.1398409

Mendez-Villanueva, A. (2012). Repeated High-Speed Activities during Youth Soccer Games in Relation to Changes in Maximal Sprinting and Aerobic Speeds. Article in International Journal of Sports Medicine. https://doi.org/10.1055/s-0032-1316363

Modric, T., Versic, S., & Sekulic, D. (2020). Aerobic fitness and game performance indicators in professional football players; playing position specifics and associations. Heliyon, 6(11), e05427. https://doi.org/10.1016/j.heliyon.2020.e05427

Pappalardo, L., Cintia, P., Ferragina, P., Massucco, E., Pedreschi, D., & Giannotti, F. (2019). PlayeRank: Data-driven performance evaluation and player ranking in soccer via a machine learning approach. ACM Transactions on Intelligent Systems and Technology, 10(5), 59. https://doi.org/10.1145/3343172

Sharma, M. S., & Shruti Thapar, M. (n.d.). Comparative Performance Analysis of AODV, DSDV and OLSR Routing Protocols in MANET Using OPNET. In International Journal of Novel Research in Computer Science and Software Engineering (Vol. 2). Retrieved May 12, 2021, from www.noveltyjournals.com

Singh, K., & Verma, A. K. (2015, August 26). Experimental analysis of AODV, DSDV and OLSR routing protocol for flying adhoc networks (FANETs). Proceedings of 2015 IEEE International Conference on Electrical, Computer and Communication Technologies, ICECCT 2015. https://doi.org/10.1109/ICECCT.2015.7226085

Wehbe, G. M., Hartwig, T. B., & Duncan, C. S. (2014). Movement analysis of australian national league soccer players using global positioning system technology. Journal of Strength and Conditioning Research, 28(3), 834–842. https://doi.org/10.1519/JSC.0b013e3182a35dd1

Yefa Mai, Yuxia Bai, & Nan Wang. (2017). Performance Comparison and Evaluation of the Routing Protocols for MANETs Using NS3. J. of Electrical Engineering, 5(4). https://doi.org/10.17265/2328-2223/2017.04.003