Abstract
The communication between the flying birds or unmanned aerial vehicles (UAVs) a.k.a Flying Adhoc Network (FANET), is the most challenging task in an extremly vibrant environment. To overcome the problem of data dissemination in changed topology, many routing protocols are investigated and modified. The stable path and congestion avoidance are the evolving area in FANET. This paper investigates preliminary UAV routing protocol with different mobility models to examine the factors such as latency, average end-to-end (E2E) delay, packet delivery ratio (PDR), etc. in dynamic environment with numerous node count and node speed variations. The simulation results presented here show that increasing the node count from 0 to 49 keeping constant velocity of 20 m/sec reflects that throughput of Optimized Link State Routing (OLSR) is 1.7 kbps using Gauss Markov (GM) mobility model (MM), which is higher than throughput using Random Way-point (RWP) MM. For the same simulation condition, a lower average E2E delay of 0.44 ms for OLSR is achieved using GM MM. However, by increasing the node speed in the range of 20 m/sec to 100 m/sec for 50 nodes, the average throughput for Ad Hoc On-Demand Distance Vector (AODV) protocol increased to 28 kbps at 75 m/sec, which is higher than OLSR using RWP MM. The simulation achieves an end-to-end delay of 600 ms and 790 ms at 50 m/sec for AODV protocol using RWP MM and GM MM, respectively. Thus, the experiment demonstrates that GM MM with variable nodes and node speed performs better than RWP MM.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Arafat MY, Moh S (2019) Routing protocols for unmanned aerial vehicle networks: a survey. IEEE Access 7:99694–99720
Lansky J, Ali S, Rahmani AM, Yousefpoor MS, Yousefpoor E, Khan F, Hosseinzadeh M (2022) Reinforcement learning-based routing protocols in flying ad hoc networks (FANET): a review. Mathematics 10(16):3017
Lansky J, Rahmani AM, Malik MH, Yousefpoor E, Yousefpoor MS, Khan MU, Hosseinzadeh M (2023) An energy-aware routing method using firefly algorithm for flying ad hoc networks. Sci Rep 13(1):1323
Zhang Y, Qiu H (2023) Delay-aware and link-quality-aware geographical routing protocol for UANET via dueling deep Q-network. Sensors 23(6):3024
Horyna J, Baca T, Walter V, Albani D, Hert D, Ferrante E, Saska M (2023) Decentralized swarms of unmanned aerial vehicles for search and rescue operations without explicit communication. Auton Robot 47(1):77–93
Kumar S, Raw RS, Bansal A, Mohammed MA, Khuwuthyakorn P, Thinnukool O (2021) 3D location oriented routing in flying ad-hoc networks for information dissemination. IEEE Access 9:137083–137098
Nawaz H, Ali HM, Laghari AA (2021) UAV communication networks issues: a review. Arch Comput Methods Eng 28(3):1349–1369
Oubbati OS, Atiquzzaman M, Lorenz P, Tareque MH, Hossain MS (2019) Routing in flying ad hoc networks: survey, constraints, and future challenge perspectives. IEEE Access 7:81057–81105
Chen Y, Zhao N, Ding Z, Alouini MS (2018) Multiple UAVs as relays: multi-hop single link versus multiple dual-hop links. IEEE Trans Wireless Commun 17(9):6348–6359
Bae JH, Kim YS, Hur N, Kim HM (2018) Study on air-to-ground multipath channel and mobility influences in UAV based broadcasting. In: 2018 International conference on information and communication technology convergence (ICTC). IEEE, pp 1534–1538
Khan S, Khan MZ, Khan P, Mehmood G, Khan A, Fayaz M (2022) An ant-hocnet routing protocol based on optimized fuzzy logic for swarm of UAVs in FANET. Wireless Commun Mobile Comput
Cumino P, Lobato Junior W, Tavares T, Santos H, Rosário D, Cerqueira E, Gerla M et al (2018) Cooperative UAV scheme for enhancing video transmission and global network energy efficiency. Sensors 18(12):4155
Srivastava A, Prakash J (2021) Future FANET with application and enabling techniques: anatomization and sustainability issues. Comput Sci Rev 39:100359
Tuli EA, Golam M, Kim DS, Lee JM (2022) Performance enhancement of optimized link state routing protocol by parameter configuration for UANET. Drones 6(1):22
Rahmani AM, Ali S, Yousefpoor E, Yousefpoor MS, Javaheri D, Lalbakhsh P, Lee SW (2022) OLSR+: a new routing method based on fuzzy logic in flying ad-hoc networks (FANETs). Veh Commun:100489
Huang J, Zan F, Liu X, Chen D (2022) Wireless communications and mobile computing UAV routing protocol based on link stability and selectivity of neighbor nodes in ETX metrics. Wireless Commun Mobile Comput
Garg S, Ihler A, Bentley ES, Kumar S (2022) A cross-layer, mobility and congestion-aware routing protocol for UAV networks. IEEE Trans Aerosp Electr Syst
Kim T, Lee S, Kim KH, Jo YI (2023) FANET routing protocol analysis for Multi-UAV-based reconnaissance mobility models. Drones 7(3):161
Bekmezci I, Sahingoz OK, Temel Ş (2013) Flying ad-hoc networks (FANETs): a survey. Ad Hoc Netw 11(3):1254–1270
Zafar W, Khan BM (2016) Flying ad-hoc networks: Technological and social implications. IEEE Technol Soc Mag 35(2):67–74
Dentler J, Rosalie M, Danoy G, Bouvry P, Kannan S, Olivares-Mendez MA, Voos H (2019) Collision avoidance effects on the mobility of a UAV swarm using chaotic ant colony with model predictive control. J Intell Rob Syst 93(1):227–243
Gangopadhyay S, Jain VK (2023) A position-based modified OLSR routing protocol for flying ad hoc networks. IEEE Trans Veh Technol
Paredes WD, Kaushal H, Vakilinia I, Prodanoff Z (2023) LoRa technology in flying ad hoc networks: a survey of challenges and open issues. Sensors 23(5):2403
Chriki A, Touati H, Snoussi H, Kamoun F (2019) FANET: communication, mobility models and security issues. Comput Netw 163:106877
Singh R, Sukapuram R, Chakraborty S (2023) A survey of mobility-aware multi-access edge computing: challenges, use cases and future directions. Ad Hoc Netw 140:103044
Chen X, Tian S, Nguyen K, Sekiya H (2021) Decentralizing private blockchain-IoT network with OLSR. Future Internet 13(7):168
Varshney T, Katiyar A, Sharma P (2014) Performance improvement of MANET under DSR protocol using swarm optimization. In: 2014 International conference on issues and challenges in intelligent computing techniques (ICICT). IEEE, pp 58–63
Khare VR, Wang FZ, Wu S, Deng Y, Thompson C (2008) Ad-hoc network of unmanned aerial vehicle swarms for search & destroy tasks. In: 2008 4th International IEEE conference intelligent systems (vol 1). IEEE, pp 6–65
Moudni H, Er-rouidi M, Mouncif H, El Hadadi B (2016) Performance analysis of AODV routing protocol in MANET under the influence of routing attacks. In: 2016 International conference on electrical and information technologies (ICEIT). IEEE, pp 536–542
Riley GF, Henderson TR (2010) The ns-3 network simulator. In: Modeling and tools for network simulation. Springer, Berlin, Heidelberg, pp 15–34
Acknowledgements
The authors of this paper are thankful to L&T Mumbai, India, for their support in this presented research work.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Bakade, K.V., More, A. (2023). Performance Analysis of UAV Routing Protocol Based on Mobility Models. In: Pundir, A.K.S., Yadav, A., Das, S. (eds) Recent Trends in Communication and Intelligent Systems. ICRTCIS 2023. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-99-5792-7_1
Download citation
DOI: https://doi.org/10.1007/978-981-99-5792-7_1
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-99-5791-0
Online ISBN: 978-981-99-5792-7
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)