Application of the BeeAdHoc bee colony algorithm for routing to FANET
Abstract
FANETs are ad hoc networks based on unmanned aerial vehicles. Design of such a wireless network may vary vastly from existing networks due to aerial network characteristics such as high mobility of UAVs in 3D space. This paper presents experimental performance results that prove the advantages of the effective usage of protocols based on bee colony algorithm to solve routing tasks in FANETs.
References
1. Beni G., Wang J. Swarm intelligence in cellular robotic systems // Robots and Biological Systems: Towards a New Bionics. Springer, 1993. P. 703-712.
2. Курейчик В. M, Кажаров А. А. Использование роевого интеллекта в решении NP-трудных задач // Известия ЮФУ Технические Науки. 2011. Вып. 7, № 120. С. 30-36.
3. Курейчик В. В., Запорожец Д. Ю. Роевой алгоритм в задачах оптимизации // Известия ЮФУ Технические Науки. 2010. Вып. 7, № 108. С. 28-32.
4. Karaboga D., Akay В. A survey: algorithms simulating bee swarm intelligence // Artif. Intell. Rev. 2009. V. 31, № 1-4. P. 61-85.
5. Маха J-А., Mahmoud M.S.B., Larrieu N. Survey on UAANET Routing Protocols and Network Security Challenges // Ad Hoc Sens. Wirel. Netw. 2017.
6. Lucie P., Teodorovic D. Computing with bees: attacking complex transportation engineering problems // Int. J. Artif. Intell. Tools. 2003. V. 12, № 3. P. 375-394.
7. Калъчевская П. И., Леванова T. В. Алгоритм пчелиного роя для задачи размещения предприятий с ограничениями на объемы поставок. Сибирская государственная автомобильно-дорожная академия (СибАДИ), 2015. С. 1833-1837.
8. Курейчик В. В., Жиленков М. А. Пчелиный алгоритм для решения оптимизационных задач с явно выраженной целевой функцией // Информатика, вычислительная техника и инженерное образование. 2015. Вып. 1, № 21. С. 1-8.
9. Teodorovic D. Bee Colony Optimization (ВСО) // Innovations in Swarm Intelligence. Springer, Berlin, Heidelberg, 2009. P. 39-60.
10. Pham D. I., Haj Darwish A., Eldukhri E. E. Optimisation of a fuzzy logic controller using the bees algorithm // Int. J. Comput. Aided Eng. Technol. 2009. V. 1, № 2. P. 250-264.
11. Yang Х-S. Engineering optimizations via nature-inspired virtual bee algorithms // Artif. Intel 1. Knowl. Eng. Appl. Bioinspired Approach. 2005. P. 317-323.
12. Karaboga D., Basturk B. On the performance of artificial bee colony (ABC) algorithm // Appl. Soft Comput. 2008. V. 8, № 1. P. 687-697.
13. Wedde H. F., Farooq M, Zhang Y. BeeHive. An efficient fault-tolerant routing algorithm inspired by honey bee behavior // Lect. Notes Comput. Sci. 2004. V. 3172. P. 83-94.
14. Davidovic T, Teodorovic D., Selmic M. Bee Colony Optimization - part I: The algorithm overview // Yugosl. J. Oper. Res. 2015. V. 25, № 1. P. 33-56.
15. Teodorovic D., Selmic M, Davidovic T. Bee Colony Optimization - part II: The application survey // Yugosl. J. Oper. Res. 2015. V. 25, № 2. P. 185-219.
16. Wei S. et. al. Simulation study of unmanned aerial vehicle communication networks addressing bandwidth disruptions / ed. Pham K.D., Cox J.L. 2014. P. 908500-1-908500-10.
17. Gupta L., Jain R., Vaszkun G. Survey of Important Issues in UAV Communication Networks // IEЕЕ Commun. Surv. Tutor. 2015. P. 1-32.
18. Bekmezci I., Sahingoz О. K., Temel S. Flying Ad-Hoc Networks (FANETs): A survey // Ad Hoc Netw. 2013. V. 11, № 3. P. 1254-1270.
19. Sahingoz О. K. Networking Models in Flying Ad-Hoc Networks (FANETs): Concepts and Challenges // J. Intell. Robot. Syst. 2014. V. 74, № 1-2. P. 513-527.
20. Saleem Y., Rehmani M. H., Zeadally S. Integration of Cognitive Radio Technology with unmanned aerial vehicles: Issues, opportunities, and future research challenges // J. Netw. Comput. Appl. 2015. V. 50. P. 15-31.
21. Temel S., Bekmezci 1. On the performance of flying ad hoc networks (FANETs) utilizing near space high altitude platforms (HAPs) // IEEE International Conference on Recent Advances in Space Technologies (RAST). 2013. P. 461-465.
22. Bee-Inspired Protocol Engineering. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. 319 p.
23. Farooq M. Bee-inspired routing protocols for mobile ad hoc and sensor networks // Bee-Inspired Protocol Engineering. Springer, 2009. P. 235-270.
24. H. F. Wedde, M. Farooq, C. Timm. BeeAdHoc: an Efficient, Secure and Scalable Routing Framework for Mobile AdHoc Networks: Technical report PG460. School of Computer Science: University of Dortmund, 2005. P. 263.
25. Боронин П. H., Кучерявый A. E. Интернет вещей как новая концепция развития сетей связи // Информационные технологии и телекоммуникации. 2014. Вып. 3, № 7. С. 7-30.
26. Ahmed A., Ogunbiyi О., Aduragba Т. Optimal Data Collection from a Network using Probability Collectives (Swarm Based). 2015. V. 3, № 4. P. 49-58.
27. Дорохова А. А., Парамонов А. И. Исследование трафика и качества обслуживания в самоорганизующихся сетях на базе БПЛА // Информационные технологии и телекоммуникации. 2016. Вып. 2, № 4. С. 12-25.
28. Singh К., Ferma А. К. Experimental analysis of AODV, DSDV and OLSR routing protocol for flying adhoc networks (FANETs) // ШЕЕ International Conference on Electrical, Computer and Communication Technologies (ICECCT). 2015. P. 1-4.
29. Qazi S. et al. An Architecture for Real Time Monitoring Aerial Adhoc Network // IEЕЕ International Conference on Frontiers of Information Technology. 2015. P. 154-159.
30. Li Y., St-Hilaire M., Kunz T. Improving routing in networks of UAVs via scoped flooding and mobility prediction // IEЕЕ Wireless Days, IFIP. 2012. P. 1-6.
31. Bettstetter С., Resta G., Santi Р. The node distribution of the random waypoint mobility model for wireless ad hoc networks // IEEE Trans. Mob. Comput. 2003. V. 2, № 3. P. 257-269.
32. Bouachir O. et al. A mobility model for UAV Ad hoc network // IEEE International Conference on Unmanned Aircraft Systems (ICUAS). 2014. P. 383-388.
33. Broch J., Maltz D. A., Johnson D. B. Maximum battery life routing to support ubiquitous mobile computing in wireless ad hoc networks // Parallel Architectures, Algorithms, and Networks, 1999. (I-SPAN’99) Proceedings. Fourth International Symposium on. IEEE, 1999. P. 370-375.
34. Liu J. et al. End-to-end delay in mobile ad hoc networks with generalized transmission range and limited packet redundancy // IEEE Wireless Communications and Networking Conference (WCNC). 2012. P. 1731-1736.
35. de Moraes R. M., Sadjadpour H. R., Garcia-Luna-Aceves J. J. Throughput-delay analysis of mobile ad-hoc networks with a multi-copy relaying strategy // IEEE Conference on Sensor and Ad Hoc Communications and Networks (SECON). 2004. P. 200-209.
36. Jacquet P., Viennot L. Overhead in Mobile Ad-Hoc Network Protocols. 2000.
37. Broch J., Maltz D. A., Johnson D. B. A performance comparison of multi-hop wireless ad hoc network routing protocols // IEEE International Symposium on Parallel Architectures, Algorithms and Networks (I-SPAN’99). 1999. P. 370-375.
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Leonov A..., Litvinov G... Application of the BeeAdHoc bee colony algorithm for routing to FANET. The Herald of the Siberian State University of Telecommunications and Information Science. 2018;(1):85-95. (In Russ.)
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