Abstract
Cloud-MANET environments require a system to balance load and control congestion. As a result of integrating real-time network metrics with predictive traffic algorithms, the proposed model optimizes the management of dynamic topologies, network bandwidth constraints, and fluctuating traffic loads. In addition to energy-aware multi-path routing, the framework incorporates adaptive congestion control mechanisms to ensure data transmission is efficient and stable. This algorithm provides higher packet delivery ratios, reduces end-to-end delays, and increases throughput over existing algorithms, according to the evaluation results. Hybrid Cloud-MANET systems can benefit from this approach by optimizing resource utilization and network performance.
Article Type
Article
Revise Date
12-22-2024
Recommended Citation
Rani, Preeti and Falaah, Mohammed Hussien
(2024)
"Real-Time Congestion Control and Load Optimization in Cloud-MANETs Using Predictive Algorithms,"
NJF Intelligent Engineering Journal: Vol. 1:
Iss.
1, Article 6.
Available at:
https://iej.iunajafjournals.com/journal/vol1/iss1/6