Jul 2026· Journal of Intelligent Decision Making and Information Science· 0 citations· 73 references
TL;DR
An in-depth review of energy-efficient routing protocols that have been developed for FANETs and highlights the main research challenges, such as high mobility, dynamic topology, routing overhead, scalability, and security, and discusses future research directions to design more intelligent and energy-aware routing protocols.
Abstract
Flying Ad Hoc Networks (FANETs) have become an important research area because of their ability to provide communication between unmanned aerial vehicles (UAVs) in a wide range of applications such as military operations, agriculture, environmental monitoring, and smart transportation. However, the limited battery capacity of UAVs and the high dynamicity of FANETs make energy-efficient routing a great challenge. An efficient routing protocol should not only be energy efficient but also provide reliable communication, improve packet delivery, reduce delay, and increase network lifetime. Recently, many energy-efficient routing protocols have been proposed by researchers based on different approaches such as clustering, swarm intelligence, reinforcement learning, fuzzy logic, and hybrid techniques. Each approach has its own advantages and limitations depending on the network environment and application requirements. This paper offers an in-depth review of energy-efficient routing protocols that have been developed for FANETs. The reviewed protocols are analyzed according to their parameters used in the study, the simulator used, advantages, and limitations. We also provide comparisons that point out the strengths and weaknesses of existing approaches. In addition, this review highlights the main research challenges, such as high mobility, dynamic topology, routing overhead, scalability, and security, and discusses future research directions to design more intelligent and energy-aware routing protocols. The present review results and conclusions offer researchers a better understanding of current trends, and they also point out potential future research directions in energy-efficient FANET routing.
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
The adoption of a new communication paradigm is getting attention in the research world, where Flying Ad Hoc Networks (FANETs) have been deemed a viable approach for supporting coordinated operations of multiple Unmanned Aerial Vehicles (UAVs) in situations characterized by dynamic environments and the absence of infrastructure. Taking into consideration these drawbacks, in this paper, a novel and up-to-date AI-Based Mobility and Topology Management Framework for Flying Ad Hoc Networks via Hybrid Bio-Inspired Optimization is proposed. The proposed systems combine a Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) inspired model, introducing a novel hybrid model, with Artificial Intelligence techniques to provide a dynamic framework for optimizing UAV mobility patterns, topology formation, and communication paths within the proposed framework. Predictive mobility analysis using AI to make networks more adaptable and minimize topology changes. In addition, the hybrid optimization method will optimize the routing efficiency, reduce the communication overhead, and increase the packet delivery efficiency between nodes in the highly dynamic FANET environment. Results of experimental analysis prove that the proposed scheme has a better PDR of 96.4%, lower EED or end-to-end delay of 31%, and better topology stability that performs better than the traditional mobility management approaches with respect to reducing energy consumption.
Anshu Vashisth, Gagandeep Kaur, Ruhi Saxena et al.· 2026 7th International Confe...· 0 citations
This study proposes an intelligent Q-learning-enhanced Evolutionary Game Theory (QEGT) routing mechanism for USNs that leverages game-theoretic incentives and Q-learning to adaptively select strategies.
Anita Murmu, Saurabh Kumar Srivastava, Nuthan Chingeetham et al.· IEEE Open Journal of the Com...· 0 citations
Modern technological systems rely heavily on Wireless Sensor Networks (WSNs), which support many kinds of applications, including but not limited to: (1) environmental monitoring (2) medical monitoring and (3) smart city/infrastructure development. One major problem with extending the overall life of the network is the limited power source of the sensor nodes; therefore, energy-efficient communication has become one of the primary research areas. The direction of this work is a GA-based routing mechanism developed to minimize energy usage within WSNs. The proposed methodology employs evolutionary operators (e.g., selection, crossover, and mutation) that will adaptively develop low-energy routing paths and provide for an even distribution of traffic across all nodes. Also, node clustering, dynamic data aggregation, and multi-objective optimization are all methods used to improve network energy efficiency while not compromising the reliability of the data or the stability of the network. The simulations performed show that the proposed GA-based routing protocol offers improved power consumption, packet delivery rate and overall longevity of the network when compared to traditional methodologies such as LEACH or other energy aware GA methods. Additionally, the implementation analysis indicates a very high level of adaptability to node movement and variable traffic patterns, suggesting that it is robust and scalable. Thus, this research will help promote the development of energy-efficient wireless sensor networks (WSNs) as well as lay a solid foundation for future intelligent routing and effective resource management within future WSNs.
T. Sarkar, Manik Rakhra· 2026 International Conferenc...· 0 citations
The paper introduces RML-ZEREM to solve existing limitations, which functions as a Reinforcement Learning (RL) based Zone-Based Leader-Aware Energy-Efficient Routing Protocol for MANETs, which serves next-generation MANET applications.
Rani Sahu, Babita Rathore· Journal of Intelligent Compu...· 0 citations
Flying ad hoc networks—composed of self-organizing unmanned aerial vehicles (UAVs)—offer numerous applications in various fields, including military operations, industry, and agriculture. Due to the UAV network's unique characteristics, such as high node velocity, sparse UAV distributions, and frequent topology changes, their data routing encounters significant challenges, compromising the quality of service aspects. We introduce a hierarchical type-II fuzzy logic system integrated with a particle swarm optimization algorithm aimed at enhancing the quality of service parameters. The UAVs’ link quality, residual energy, distance, neighboring nodes’ degree, movement direction, and relative velocity are the fuzzy system inputs to compute UAV nodes’ utility, forming the most suitable multiple relay nodes in the optimized link state routing protocol. Meanwhile, our approach employs a hierarchical fuzzy structure to address the curse of dimensionality caused by the exponential growth of fuzzy rules. Furthermore, the particle swarm optimization algorithm adjusts the fuzzy membership functions to tackle ambiguity and uncertainty in the UAV environment. We simulate our approach using NS-3 and compare it with traditional methods under varying node densities and mobility models. The simulation outcomes demonstrate that our approach enhances end-to-end delay, packet delivery ratio, network throughput, and energy consumption compared to rival schemes.
Hamid Shokrzadeh, M. Vahedi, P. Rahmani· Journal of Intelligent &...· 0 citations