Authors :
Momodu Kabiru Sanu; Biralatei Fawei; Diripigi Briyai Okolai
Volume/Issue :
Volume 10 - 2025, Issue 12 - December
Google Scholar :
https://tinyurl.com/3dfuykub
Scribd :
https://tinyurl.com/yr8hdkhs
DOI :
https://doi.org/10.38124/ijisrt/25dec1262
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
The study examines the impact of different routing protocols on WLAN performance. This research is motivated
by the increasing reliance on WLANs in both personal and professional domains, highlighting the need to optimize data
transmission efficiency for various network demands. The study focuses on three well-known routing protocols: Ad-hoc On-
Demand Distance Vector (AODV), Dynamic Source Routing (DSR), and Destination-Sequenced Distance-Vector (DSDV).
Each protocol was selected for its distinct characteristics in handling network changes, making them relevant for comparison
in dynamic WLAN environments. Using Cisco Packet Tracer network simulation software, the study modeled each protocol
within a WLAN framework, evaluating key performance metrics such as hop count, throughput, end-to-end delay, network
congestion, packet delivery ratio, delay (latency) and packet loss rate. This approach enabled the simulation of real-time
data transmission scenarios, providing insights into each protocol’s responsiveness and adaptability. Results indicate that
AODV and DSR are well-suited for dynamic high-mobility WLANs, showing strong adaptability and efficient path-finding
capabilities under changing conditions. In contrast, DSDV a table-driven protocol, demonstrated stable performance in
static environments but showed limitations in adaptability within rapidly changing network conditions. Overall, AODV
demonstrated the best balance of stability and adaptability, making it a favorable choice for WLANs that require flexibility.
This study contributes valuable insight into protocol selection for WLANs, underscoring the importance of aligning protocol
capabilities with specific network demands. Based on these findings, we recommend adopting AODV for WLANs in need of
flexibility and adaptability, while DSDV may be more suitable for static, low-mobility environments.
References :
- Alizadeh, M., & Mozaffari-Kermani, M. (2012). A survey of QoS routing protocols in wireless sensor networks. Journal of Network and Computer Applications, 35(2), 625–651
- Alqahtani, S., & Zhang, Y. (2020). Wireless Local Area Network (WLAN): A review of the history, standards, and evolution. Journal of King Saud University-Computer and Information Sciences, 32(3), 224–237.
- Bhargavi, G., Kumar, S., Prasad, N. V., & Reddy, K. K. (2021). Application of Routing Dynamics to Wireless Local Area Network Design Mechanism. Journal of Network and Systems Management, 29(1), 108–126.
- Bhushan, N., & Kumar, S. (2010). A survey on network simulators for wireless networks. International Journal of Computer Applications, 1(6), 12–18.
- Comer, D. (2012). Computer networks and internets. Pearson Education India.
- Feamster, N. (2014). Software-defined networking. Morgan & Claypool Publishers.
- Wang, L., Lehman, V., Hoque, A. M., Zhang, B., Yu, Y., & Zhang, L. (2018). A secure link state routing protocol for NDN. IEEE Access, 6, 10470-10482.
- Hoque, A. M., Amin, S. O., Alyyan, A., Zhang, B., Zhang, L., & Wang, L. (2013, August). NLSR: Named-data link state routing protocol. In Proceedings of the 3rd ACM SIGCOMM workshop on Information-centric networking (pp. 15-20).
- Alam, M. Z., Adhicandra, I., & Jamalipour, A. (2019). Optimal best path selection algorithm for cluster-based multi-hop MIMO cooperative transmission for vehicular communications. IEEE Transactions on Vehicular Technology, 68(9), 8314-8321.
- Benslimane, A., Barghi, S., & Assi, C. (2011). An efficient routing protocol for connecting vehicular networks to the Internet. Pervasive and Mobile Computing, 7(1), 98-113.
- Pradittasnee, L., Camtepe, S., & Tian, Y. C. (2016). Efficient route update and maintenance for reliable routing in large-scale sensor networks. IEEE Transactions on Industrial Informatics, 13(1), 144-156.
- Zhao, X., Wan, C., Sun, H., Xie, D., & Gao, Z. (2017). Dynamic rerouting behavior and its impact on dynamic traffic patterns. IEEE Transactions on Intelligent Transportation Systems, 18(10), 2763-2779.
- Liu, G., He, J., Luo, Z., Yao, X., & Fan, Q. (2024). Understanding route choice behaviors' impact on traffic throughput in a dynamic transportation network. Chaos, Solitons & Fractals, 181, 114605.
- Selim, I. M., Abdelrehem, N. S., Alayed, W. M., Elbadawy, H. M., & Sadek, R. A. (2025). MANET Routing Protocols’ Performance Assessment Under Dynamic Network Conditions. Applied Sciences, 15(6), 2891.
- Hashim, S. A., Hamza, E. K., & Kamal, N. N. (2024). Analyzing Dynamic Source Routing Protocol Behavior in MANETs. Ingenierie des Systemes d'Information, 29(6), 2357.
The study examines the impact of different routing protocols on WLAN performance. This research is motivated
by the increasing reliance on WLANs in both personal and professional domains, highlighting the need to optimize data
transmission efficiency for various network demands. The study focuses on three well-known routing protocols: Ad-hoc On-
Demand Distance Vector (AODV), Dynamic Source Routing (DSR), and Destination-Sequenced Distance-Vector (DSDV).
Each protocol was selected for its distinct characteristics in handling network changes, making them relevant for comparison
in dynamic WLAN environments. Using Cisco Packet Tracer network simulation software, the study modeled each protocol
within a WLAN framework, evaluating key performance metrics such as hop count, throughput, end-to-end delay, network
congestion, packet delivery ratio, delay (latency) and packet loss rate. This approach enabled the simulation of real-time
data transmission scenarios, providing insights into each protocol’s responsiveness and adaptability. Results indicate that
AODV and DSR are well-suited for dynamic high-mobility WLANs, showing strong adaptability and efficient path-finding
capabilities under changing conditions. In contrast, DSDV a table-driven protocol, demonstrated stable performance in
static environments but showed limitations in adaptability within rapidly changing network conditions. Overall, AODV
demonstrated the best balance of stability and adaptability, making it a favorable choice for WLANs that require flexibility.
This study contributes valuable insight into protocol selection for WLANs, underscoring the importance of aligning protocol
capabilities with specific network demands. Based on these findings, we recommend adopting AODV for WLANs in need of
flexibility and adaptability, while DSDV may be more suitable for static, low-mobility environments.