conference paper · Proceedings of the Faculty of Science Conferences
Mobile ad-hoc networks provide dynamic, decentralised communication for critical situations such as remote sensing, disaster recovery, and military operations. A major constraint of these systems is the finite power capacity of mobile nodes, which directly curtails network performance and operational lifespan. Recent optimisation strategies seek to address these challenges through metaheuristic algorithms, adaptive transmission power control, and machine learning models. Notable approaches include trust-aware routing protocols, clustering techniques, and advanced mobility representations such as the Gauss-Markov model. An examination of current simulation metrics reveals key operational boundaries across existing research. Sustained progress requires the creation of lightweight and scalable algorithms, deeper integration with heterogeneous networking technologies, and the refinement of traffic and mobility models to reflect real operating conditions accurately.
Decentralised mobile networks are vital when fixed infrastructure is unavailable, especially during emergency disaster relief and remote field deployments. Because participating devices rely entirely on limited battery reserves, improving energy efficiency ensures that critical communications remain secure, operational, and resilient during high-stakes missions without premature system failure.
The reviewed techniques target applications in disaster recovery systems, defence communications, and remote environmental sensing. The underlying technology currently sits at an early, simulation-based stage of readiness. Commercialisation by network equipment vendors and communications developers will depend on transforming these theoretical and simulated models into lightweight, scalable software capable of functioning across diverse, real-world hardware environments.
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This systematic review paper provides a comprehensive analysis of recent advancements in energy optimization techniques for Mobile Ad-hoc Networks (MANETs). MANETs play a critical role in modern communication systems, enabling dynamic and decentralized networking in various applications, including disaster recovery, military operations, and remote sensing. However, energy consumption remains a significant challenge due to the limited power resources of mobile nodes, directly impacting network performance and lifespan. In recent years, optimization techniques such as metaheuristic algorithms, adaptive transmission power control, and machine learning models have shown remarkable potential in addressing these challenges by enhancing energy efficiency and prolonging network lifetime. This paper reviews the current trends in energy optimization for MANETs, including trust-aware routing protocols, clustering methods, and advanced mobility models like the Gauss-Markov model. Additionally, it provides a detailed analysis of the simulation parameters and metrics used in the studies, highlighting their applicability and limitations. The review also identifies key areas for future research, such as developing lightweight and scalable algorithms, integrating heterogeneous network technologies, and refining mobility and traffic models for more realistic simulations. The paper concludes by summarizing the key findings of the systematic review and emphasizing the importance of continuous innovation in energy optimization strategies to enhance the sustainability and reliability of MANETs. This review serves as a valuable resource for researchers and practitioners, guiding the development of robust and efficient networking solutions.
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DOI: 10.62050/fscp2024.481
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