Scalability and Reliability Analysis of Routing Techniques in Mobile Ad Hoc Networks

Abstract

Mobile ad hoc networks (MANETs), with no infrastructure, changing topology and self-configuration capabilities, have created a new paradigm in wireless communication. The routing of data packets in a MANET environment is challenging, as there are constant changes to the topology, limited bandwidth, movement of nodes and energy limitations. This study provides a comprehensive analysis of the effectiveness, scalability and reliability of various routing techniques commonly used in MANETs under different network conditions. Through the use of performance metrics, such as packet delivery ratio, end-to-end delay, throughput, routing overhead and network reliability, the study compares the behaviour of proactive, reactive and hybrid routing protocols. The simulation of a MANET was accomplished by varying node density, mobility patterns and traffic loads, to assess protocol performance under highly dynamic and large-scale network conditions. The results demonstrate that routing protocol performance is significantly impacted by network scalability and mobility. Reactive protocols are more adaptable to changes in a dynamic network, whereas proactive protocols provide lower latency in stable networks. Hybrid routing protocols provide balanced performance as they increase scalability and reliability of communication. The results of this study contribute to identifying the most effective routing strategies for next generation wireless ad hoc communication systems, and assist in developing reliable MANET applications for disaster recovery, military communications, intelligent transportation and IoT enabled environments.

Introduction

Mobile Ad Hoc Networks (MANETs) are decentralized wireless networks where mobile nodes communicate and also act as routers without fixed infrastructure. They are widely used in military, disaster recovery, IoT, and emergency systems due to their flexibility and fast deployment. However, MANETs face challenges such as high mobility, limited bandwidth, energy constraints, interference, and unstable network topology, which make reliable and efficient routing difficult.

To address these issues, routing protocols are classified into proactive, reactive, and hybrid types. Proactive protocols maintain continuous routing tables but create high overhead, reactive protocols create routes on demand but introduce delay, and hybrid protocols balance both approaches. Many techniques such as genetic algorithms, clustering, AI-based routing, and optimization methods have been proposed to improve scalability, reliability, and efficiency, but challenges still remain in dynamic and large-scale environments.

The paper proposes a comprehensive evaluation framework to analyze routing protocols in MANETs under varying conditions such as node density, mobility, and traffic load. The methodology includes network simulation (using NS-3), deployment of different routing protocols (DSDV, AODV, DSR, ZRP), and performance measurement using key metrics like packet delivery ratio, throughput, delay, routing overhead, and reliability.

The study evaluates scalability and reliability by testing networks with different numbers of nodes and mobility speeds using realistic simulation settings. Results are compared across protocols to understand their strengths, weaknesses, and adaptability in dynamic environments.

Conclusion

Using various communication criteria for the evaluation of proactive, reactive, and hybrid routing protocols, i.e. PDR, throughput, end-to-end delay, routing overhead, and network reliability and using experimental analysis, the hybrid routing protocol called ZRP showed a better overall performance result than the DSDV, DSR, and AODV routing protocols. The study demonstrated that ZRP achieved the highest PDR of 96.2%, throughput of 603Kbps, end-to-end delay of 32ms (lowest end-to-end delay recorded), and minimum routing overhead of 18.3%, which indicate that ZRP performed the best for routing in large-scale dynamic MANET environments in terms of scalability and communication efficiency. Furthermore, the scalability evaluation demonstrated that as node density increased, ZRP maintained stable routing performance with a PDR of 93.8% up to 150 nodes, whereas all other routing protocols experienced some degree of performance deterioration due to increased congestion and routing complexity. Reliability evaluation of the different routing protocols at different mobility speeds was also performed, with ZRP providing the highest reliability of communications at 92.7% at 25m/s of mobility speed, thereby demonstrating ZRP’s adaptability and stability under rapidly changing topology conditions. From the comparative evaluation among all routing protocols in varied mobility conditions, it was established that reactive routing protocols (AODV) outperformed proactive routing protocols in highly mobile conditions; however, hybrid routing protocols provided well-balanced, consistent communication performance with varied network conditions. Future research can also include exploration of energy-efficient routing optimization, blockchain-based secure routing, congestion-aware communications, and real-time MANET deployment on 5G and 6G mobile wireless communications to further enhance scalability and security, as well as reliable communication performance in the next generation of mobile ad hoc networks.

References

[1] H. M. Hariz, H. Ali Rasool, N. Karimov, A. F. Abed, F. Alsalamy and M. I. Hashim, \"Efficient Routing Using Multipath Routing Protocol with Genetic Algorithm in Mobile Ad Hoc Networks,\" 2025 International Conference on Next Generation Computing Systems (ICNGCS), Coimbatore, India, 2025, pp. 1-6, doi: 10.1109/ICNGCS64900.2025.11183420. [2] Q. Jumaa and K. Yadav, \"Stability and Efficiency Enhancements in Mobile Ad Hoc Networks with Multicriteria Relay Selection,\" 2025 International Conference on Next Generation of Green Information and Emerging Technologies (GIET), Gunupur, India, 2025, pp. 1-6, doi: 10.1109/GIET65294.2025.11234829. [3] D. R. Raman, V. Kumar, B. G. Pillai, D. Rabadiya, S. Patre and R. Meenakshi, \"Enhancing Quality of Service in Mobile Ad-Hoc Networks through Secure Routing with Multi-Constrained Network Feature Approximation,\" 2024 International Conference on Knowledge Engineering and Communication Systems (ICKECS), Chikkaballapur, India, 2024, pp. 1-5, doi: 10.1109/ICKECS61492.2024.10616525. [4] A. Alkhayyat, K. S. Kumar, M. M. Hiremath, A. Das and M. G. K, \"Escaping Strategy with Golden Jackal Optimization Based Clustering and Routing in Mobile Ad Hoc Network,\" 2024 International Conference on Data Science and Network Security (ICDSNS), Tiptur, India, 2024, pp. 1-5, doi: 10.1109/ICDSNS62112.2024.10690997. [5] L. Hussein, S. A V, Y. M. M. John, P. B. Edwin and S. S. M. Reddy, \"Intent Prediction-Based Secure Routing with Artificial Neural Network in Vehicular Ad Hoc Networks,\" 2025 Third International Conference on Networks, Multimedia and Information Technology (NMITCON), BENGALURU, India, 2025, pp. 1-7, doi: 10.1109/NMITCON65824.2025.11187452. [6] T. Alrwbaye and A. J. Alzahrani, \"Node Density-Based Routing Algorithms for Mobile Ad Hoc Networks,\" 2025 International Conference on Next Generation of Green Information and Emerging Technologies (GIET), Gunupur, India, 2025, pp. 1-6, doi: 10.1109/GIET65294.2025.11234822. [7] Vikas, R. P. Daund, D. Kumar, P. Charan, R. S. K. Ingilela and R. Rastogi, \"Intrusion Detection in Wireless Sensor Networks using Hybrid Deep Belief Networks and Harris Hawks Optimizer,\" 2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC), Coimbatore, India, 2023, pp. 1631-1636, doi: 10.1109/ICESC57686.2023.10193270. [8] N. Aslam and M. Shahnawaz, \"A Cryptographic Approach to Secure Ad-Hoc On-Demand Distance Vector Routing in Mobile Ad-Hoc Networks,\" 2025 International Conference on Computing, Intelligence, and Application (CIACON), Durgapur, India, 2025, pp. 1-6, doi: 10.1109/CIACON65473.2025.11189344. [9] M. J. AL-Mashhadani and K. Karoui, \"Rule-Based And AI-Based Routing Protocols For Mobile Ad Hoc Networks: A Comparative Review,\" 2025 7th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (ICHORA), Ankara, Turkiye, 2025, pp. 1-12, doi: 10.1109/ICHORA65333.2025.11017238. [10] S. Nagaraju, P. Johri, P. Putta, D. Kalla, S. Polvanov and N. V. Patel, \"Smart Routing in Urban Wireless Ad Hoc Networks Using Graph Attention Network-Based Decision Models,\" 2025 International Conference on Networks and Cryptology (NETCRYPT), New Delhi, India, 2025, pp. 212-216, doi: 10.1109/NETCRYPT65877.2025.11102255. [11] H. S. Sengar, G. G. Venkatesha, P. Chauhan, I. R. Mallela, V. Bhimanapati and O. Goel, \"Modelling and Analysis of Network Protocols for Mobile Ad-hoc Networks with Non-Ideal Conditions,\" 2025 International Conference on Pervasive Computational Technologies (ICPCT), Greater Noida, India, 2025, pp. 229-233, doi: 10.1109/ICPCT64145.2025.10939181. [12] R. Sharma, V. Sharma, T. K. Vashishth, S. Chaudhary, K. K. Sharma and S. Kaushik, \"Securing Routing in MANETs: A Comprehensive Review of Enhanced Optimized Link State Routing (EOLSR),\" 2025 International Conference on Intelligent Computing and Knowledge Extraction (ICICKE), Bengaluru, India, 2025, pp. 1-6, doi: 10.1109/ICICKE65317.2025.11136709. [13] P. C. S. Reddy, P. Shirley Muller, S. N Koka, V. Sharma, N. Sharma and S. Mukherjee, \"Detection of Encrypted and Malicious Network Traffic using Deep Learning,\" 2023 International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics (AIKIIE), Ballari, India, 2023, pp. 1-6, doi: 10.1109/AIKIIE60097.2023.10390386.

Copyright

Copyright © 2026 Ankur Bhardwaj, Sharad Kumar, Jagdeep Singh, Manoj Kumar, Sachin Kumar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.