Jul 2026· International Journal of Electronics and Communication Engineering· 0 citations· 23 references
TL;DR
A new Enhanced Intelligent-based Energy and Mobility, and Obstacle-aware Clustering (EIEMOC) protocol to control the network congestion while meeting End-to-End Delay (E2D) constraints in delay-constrained FANET applications.
Abstract
Increases in the use of UAVs for communication have led to the widespread emergence of Flying Ad hoc Networks (FANET). Conversely, UAV’s mobility and environmental obstacles affect communication links, resulting in link unreliability and inefficient routing. To combat these challenges, an Energy and Mobility-Aware Stable and Safe clustering (EMASS) protocol has been developed, which prevents obstacles in the routing path and minimizes the influence of high mobility on data transfer. However, it does not address the congestion issue in FANET routing, which degrades the data transfer in delay-constrained applications. Hence, this manuscript proposes a new Enhanced Intelligent-based Energy and Mobility, and Obstacle-aware Clustering (EIEMOC) protocol to control the network congestion while meeting End-to-End Delay (E2D) constraints in delay-constrained FANET applications. The main optimization objectives of this protocol are the cumulative rates over the connections and various factors that influence the E2D for 1-hop communication. First, a dispersed delay-aware congestion control scheme is developed that integrates a 1-hop delay constraint to obtain the best solution. Then, a delay support factor is introduced for every connection, and the 1-hop delay constraint is updated by conjointly merging the cumulative arriving flow and the probability of data being rejected at a specific connection. Thus, this protocol maximizes the system reliability and reduces the E2D in a dispersed manner. Finally, extensive simulations establish that the EIEMOC achieves higher network performance compared to the classical protocols in FANETs.
Simulation results indicate that HOA-MEPFL-CLCT-RP outperforms existing models in terms of Packet Delivery Ratio (PDR), energy efficiency, End-to-End Delay (E2D), and routing overhead.
Shaleena H, Sumangala K· International journal of com...· 0 citations
Mobile nodes are continuously moving in the network and form the link to transfer the information between source and destination. All the mobile nodes have limited bandwidth and limited battery power. Energy is the primary source required for route establishment and data transfer to all the interconnected nodes. If the nodes have a limited amount of energy, it means immediate action is required to switch to the other node or re-establish the route for proper data transfer. In this research, a novel energy-efficient multipath routing for load balancing (EMRD-LB) is capable of improving the routing performance. The EMRD-LB approach is efficiently utilizing the energy of nodes and link capacity to avoid congestion from the network. This method enhances data flow and extends the operational lifespan of the network nodes. By dynamically adjusting the routing paths based on current energy levels, the system ensures optimal performance even under varying load conditions. The load balancing is required to reduce the packet dropping and control the extra load by reducing the data rate and buffer management. The proposed scheme is also capable of reducing overhead, which is typically increased due to data retransmissions and delays in acknowledgement packets. Flooding of overhead packets increases bandwidth consumption and delays in data forwarding. The performance of EMRD-LB is compared with QMR, AOMDV, and MMEE, and the performance of the proposed scheme is better. The EMRD-LB reduces delay, reduces packets dropping and improves data receiving.
Aradhana Saxena, Nitika Vats· International journal of com...· 0 citations
Mobile Ad-hoc Networks (MANETs) are a useful means for communication in military and emergency situations, as well as for various types of smart sensors and other mobile applications, since they allow mobile nodes to interact with each other without relying on a fixed communication structure. However, fast-moving and unpredictable nodes result in frequent changes to the topology of the network which also result in inconsistent route selections and more energy used to send and receive packets, thus leading to lower overall performance on the network. This paper introduces an adaptive routing scheme based on the Shrike Optimization Algorithm (ShOA) for improving MANET performance by overcoming these issues. The proposed Scheme identifies the most efficient routing paths through the use of the predation and decision-making abilities of Shrike Birds. This Shrike-based routing design reduces the amount of information lost in the form of packet losses and routing overheads, while providing reliable transfers of data by properly balancing the trade-off between exploring and exploiting. Based on extensive simulation results, the proposed ShOA-based MANET exhibits substantially improved performance in the areas of packet delivery ratios, end-to-end delay, throughput, and overall durabilitys compared to both optimization techniques currently used and conventional routing protocols. Therefore,the results support the conclusion that the Shrike Optimization Algorithm offers aviable option for developing reliable and energy-efficient mobile ad - hoc networks for communication
V. Vishu, S. Sivagnanam, L. P. Suresh et al.· International Conference on...· 0 citations
To overcome the inherent compromises between proactive and reactive data transmission in Vehicular Ad-hoc Networks (VANETs), this research introduces a novel framework tailored for highly unstable vehicular topologies. The developed system, termed the Dynamic Hybrid Routing Protocol (DHRP), merges the Optimised Link State Routing (OLSR) and Ad-hoc On-Demand Distance Vector (AODV) algorithms. A core feature of this architecture is its cross-layer power management module, which dynamically recalibrates transmission strength and routing paths by analysing real-time vehicle clustering and speed metrics. Comprehensive evaluations conducted via NS-3 and SUMO indicate that the proposed DHRP significantly surpasses both contemporary benchmarks and standard baselines. Notably, the architecture achieves a Packet Delivery Ratio (PDR) exceeding 90%, limits communication latency to well below the critical 40 ms safety boundary, and slashes energy expenditure by up to 90%. By effectively solving the traditional routing dichotomy, DHRP offers a highly scalable and sustainable communication backbone vital for the reliable operation of future Intelligent Transportation Systems (ITS).
: In dense multi-drone FANET environments, routing efficiency is often reduced due to constant competition for a wireless channel, frequent changes in network topology, and uneven energy consumption between UAV nodes. These factors lead to a decrease in the packet delivery ratio, an increase in delays on the busiest or most unstable routes, and a reduction in the total network lifespan. Although many existing routing methods utilize mobility forecasting or reinforcement learning, most are based on independent decision-making by individual agents. As a result, such approaches may create a significant service load and insufficiently account for competition for the communication channel, as well as the fair distribution of energy consumption between network nodes. To overcome these integrated challenges, this paper proposes FL-CARE, a Federated Learning-based Contention-Aware and Energy-balanced Routing protocol. In FL-CARE, each UAV acts as a learning agent using a multidimensional state (predicted link stability, channel contention, queue occupancy, residual energy) and a tail-latency-sensitive reward function. A lightweight federated learning mechanism enables collaborative, swarm-level intelligence with bounded communication overhead. Extensive MATLAB simulations demonstrate that FL-CARE outperforms state-of-the-art protocols MP-QGRD and RL-MPEAOLSR, improving PDR by 12-18%, reducing average delay by 20 – 25% and tail latency (p99) by up to 30%. Additionally, FL-CARE yields a 15-22% energy consumption per bit delivered, and control overhead reduction of 35-45%, and advances network lifetime by approx. 25% in dense network deployments. The proposed framework maintains low computational and communication overhead through lightweight local learning and compact federated model updates, while adaptive aggregation intervals facilitate efficient collaborative learning and scalable operation under varying network conditions. These simulation results validate the holistic integration with federated multi-agent learning, with emphasis on contention awareness and energy balancing is essential for scalable and efficient routing in next-generation dense FANETs.
H. Khujamatov, Elyanora Jolimbetova, Khaleel Ahmad et al.· Journal of Computer Science· 0 citations