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A Comparative Analysis of Mobility Models for Network of UAVs

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1025))

Abstract

Flying Adhoc Network (FANET) is an emerging research area gaining lot of attention of researchers nowadays. FANET as the name suggests, is an ad hoc network of Unarmed Aerial Vehicles (UAVs) flying in the space and forming a connected network to accomplish a common task with cooperation of each other. Mobility of nodes in such networks has always been a challenging task and thus researchers have proposed many solutions over the time for directing nodes mobility within the region of interest. Since, FANET nodes tend to move at much greater speed as compared to nodes in other networks like mobile ad hoc networks (MANETs) and drain more energy pertaining to its self-organizing nature, various new mobility models have been suggested and traditional models for MANET have been modified in accordance with the need of FANETs. In this paper, we present comparative study of both old as well as the new mobility models. A systematic comparative analysis is done based on certain parameters like their ability to cover the area, maintenance of connectivity, collision avoidance and energy consumption. Also, the paper explores some future directions and research problems related to the FANETs.

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References

  1. Yanmaz, E., Yahyanejad, S., Rinner, B., Hellwagner, H., Bettstetter, C.: Drone networks: communications, coordination, and sensing. Ad Hoc Netw. 68, 1–15 (2018)

    Article  Google Scholar 

  2. Schleich, J., Panchapakesan, A., Danoy, G., Bouvry, P.: UAV fleet area coverage with network connectivity constraint. In: Proceedings of the 11th ACM International Symposium on Mobility Management and Wireless Access, pp. 131–138. ACM (2013)

    Google Scholar 

  3. Bujari, A., Calafate, C.T., Cano, J.C., Manzoni, P., Palazzi, C.E., Ronzani, D.: Flying ad-hoc network application scenarios and mobility models. Int. J. Distrib. Sens. Netw. 13(10), 1–17 (2017). https://doi.org/10.1177/1550147717738192

    Article  Google Scholar 

  4. Xie, J., Wan, Y., Kim, J.H., Fu, S., Namuduri, K.: A survey and analysis of mobility models for airborne networks. IEEE Commun. Surv. Tutor. 16(3), 1221–1238 (2014)

    Article  Google Scholar 

  5. Manimegalai, T., Jayakumar, C.: A conceptual study on mobility models in MANET. Int. J. Eng. Res. Technol. (IJERT) 2(11), 3593–3598 (2013)

    Google Scholar 

  6. Bettstetter, C., Hartenstein, H., Pérez-Costa, X.: Stochastic properties of the random waypoint mobility model. Wirel. Netw. 10(5), 555–567 (2004)

    Article  Google Scholar 

  7. Liang, B., Haas, Z.J.: Predictive distance-based mobility management for PCS networks. In: Proceedings of the Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies, INFOCOM 1999, vol. 3, pp. 1377–1384. IEEE (1999)

    Google Scholar 

  8. Messous, M.A., Sedjelmaci, H., Senouci, S.M.: Implementing an emerging mobility model for a fleet of UAVs based on a fuzzy logic inference system. Pervasive Mob. Comput. 42, 393–410 (2017)

    Article  Google Scholar 

  9. Atten, C., Channouf, L., Danoy, G., Bouvry, P.: UAV fleet mobility model with multiple pheromones for tracking moving observation targets. In: Squillero, G., Burelli, P. (eds.) EvoApplications 2016, Part I. LNCS, vol. 9597, pp. 332–347. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-31204-0_22

    Chapter  Google Scholar 

  10. Yanmaz, E.: Connectivity versus area coverage in unmanned aerial vehicle networks. In: IEEE International Conference on Communications (ICC 2012), pp. 719–723. IEEE (2012)

    Google Scholar 

  11. Bouachir, O., Abrassart, A., Garcia, F., Larrieu, N.: A mobility model for UAV ad hoc network. In: 2014 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 383–388. IEEE (2014)

    Google Scholar 

  12. Guillen-Perez, A., Cano, M.D.: Flying ad hoc networks: a new domain for network communications. Sensors 18(10), 3571 (2018)

    Article  Google Scholar 

  13. Zhao, H., Wang, H., Wu, W., Wei, J.: Deployment algorithms for UAV airborne networks toward on-demand coverage. IEEE J. Sel. Areas Commun. 36(9), 2015–2031 (2018)

    Article  Google Scholar 

  14. Jawhar, I., Mohamed, N., Al-Jaroodi, J., Agrawal, D.P., Zhang, S.: Communication and networking of UAV-based systems: Classification and associated architectures. J. Netw. Comput. Appl. 84, 93–108 (2017)

    Article  Google Scholar 

  15. Kuiper, E., Nadjm-Tehrani, S.: Mobility models for UAV group reconnaissance applications. In: International Conference on Wireless and Mobile Communications, ICWMC 2006, p. 33. IEEE (2006)

    Google Scholar 

  16. Li, X., Zhang, T., Li, J.: A particle swarm mobility model for flying ad hoc networks. In: 2017 IEEE Global Communications Conference on GLOBECOM 2017, pp. 1–6. IEEE (2017)

    Google Scholar 

  17. Cheng, X., Dong, C., Dai, H., Chen, G.: MOOC: a mobility control based clustering scheme for area coverage in FANETs. In: 2018 IEEE 19th International Symposium on “A World of Wireless, Mobile and Multimedia Networks” (WoWMoM), pp. 14–22. IEEE (2018)

    Google Scholar 

  18. Wang, W., Guan, X., Wang, B., Wang, Y.: A novel mobility model based on semi-random circular movement in mobile ad hoc networks. Inf. Sci. 180(3), 399–413 (2010)

    Article  Google Scholar 

  19. Kumari, K., Sah, B., Maakar, S.: A survey: different mobility model for FANET. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 5(6), 1170–1173 (2015)

    Google Scholar 

  20. Wan, Y., Namuduri, K., Zhou, Y., Fu, S.: A smooth-turn mobility model for airborne networks. IEEE Trans. Veh. Technol. 62(7), 3359–3370 (2013)

    Article  Google Scholar 

  21. Kumari, K., Sah, B., Maakar, S.: A brief survey of mobility model for FANET. In: Proceedings of National Conference on Innovative Trends in Computer Science Engineering (ITCSE) (2015)

    Google Scholar 

  22. Bai, F., Sadagopan, N., Helmy, A.: The IMPORTANT framework for analyzing the impact of mobility on performance of routing protocols for Adhoc networks. Ad Hoc Netw. 1(4), 383–403 (2003)

    Article  Google Scholar 

  23. Williams, S.A., Huang, D.: Group force mobility model and its obstacle avoidance capability. Acta Astronaut. 65(7–8), 949–957 (2009)

    Article  Google Scholar 

  24. Sanchez-Garcia, J., Garcia-Campos, J.M., Toral, S.L., Reina, D.G., Barrero, F.: A self organising aerial ad hoc network mobility model for disaster scenarios. In: 2015 International Conference on Developments of E-Systems Engineering (DeSE), pp. 35–40. IEEE (2015)

    Google Scholar 

  25. Biomo, J.D.M.M., Kunz, T., St-Hilaire, M.: An enhanced Gauss-Markov mobility model for simulations of unmanned aerial ad hoc networks. In: 2014 7th IFIP Wireless and Mobile Networking Conference (WMNC), pp. 1–8. IEEE (2014)

    Google Scholar 

  26. Kennedy, J.: Particle swarm optimization. In: Encyclopedia of Machine Learning, pp. 760–766. Springer, Boston (2011)

    Google Scholar 

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Correspondence to Ashima Adya .

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Adya, A., Sharma, K.P., Nonita (2019). A Comparative Analysis of Mobility Models for Network of UAVs. In: Gani, A., Das, P., Kharb, L., Chahal, D. (eds) Information, Communication and Computing Technology. ICICCT 2019. Communications in Computer and Information Science, vol 1025. Springer, Singapore. https://doi.org/10.1007/978-981-15-1384-8_11

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  • DOI: https://doi.org/10.1007/978-981-15-1384-8_11

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-1383-1

  • Online ISBN: 978-981-15-1384-8

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