Aug 2026· International Conference on Circuit, Power and Computing Technologies· pp. 2138-2143· 0 citations· 12 references
Abstract
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
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
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.
Ragvinder Kaur, Amit Sharma· Journal of Intelligent Decis...· 0 citations
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.
J. Rajeswari, R. Kousalya· International Journal of Ele...· 0 citations
A novel energy-efficient multipath routing for load balancing (EMRD-LB) is capable of improving the routing performance and reducing delay, reduces packets dropping and improves data receiving.
Aradhana Saxena, Nitika Vats· International journal of com...· 0 citations
Mobile Ad hoc Networks (MANETs) have emerged as a flexible
networking paradigm; however, they are associated with several challenges, including low
throughput, poor packet delivery ratio, high energy consumption, increased latency, and
significant routing overhead.
The Enhanced Hybrid Metaheuristic Ant Lion Optimization (EHMALO) method is
suggested as a solution to these limitations. EHMALO applies the RSSI-based Link Expiration
Time (R-LET), Context-Aware Dynamic Weight Adjustment Model (C-DWAM), and Dual
Phase Exploration-Exploitation Technique (D-PET). These techniques are incorporated along
with an enhanced Ant Colony Optimization (ACO) algorithm that uses the foraging techniques
to explore the path, and an improved Lion Optimization Algorithm (LOA) hunting strategy is
chosen to optimize the routing path. The Ad hoc On-demand Multipath Distance Vector
(AOMDV) routing algorithm is used in conjunction with the combined algorithm. To select the
optimal path, an adaptive adjustment parameter for the feedback mechanism is considered after
the iterations. This suggested approach is then used to assess performance metrics such as
packet delivery ratio, throughput, latency, energy efficiency, and routing overhead.
The effectiveness of the proposed EHMALO algorithm is illustrated using Network
Simulator-3 (NS-3) simulations for various network settings. The results are compared to
traditional techniques such as ACO, LOA, Particle Swarm Optimization-Genetic Algorithm
(PSO-GA), and Hybrid Ant Lion Optimization (HALO) with AOMDV techniques. The Quality
of Service (QoS) metrics have improved significantly as per the results
The suggested EHMALO method performs better, surpassing the drawbacks of
conventional bio-inspired methods. When route discovery and route maintenance are
considered, EHMALO maximizes energy efficiency, throughput, and packet delivery ratio
while minimizing the routing overhead ratio and end-to-end delay.
Thus, the proposed EHMALO performs significantly better than ACO with
AOMDV, LOA with AOMDV, PSO-GA, and HALO algorithms. The outcomes show that
EHMALO has the ability to improve MANET performance in dynamic contexts in a
dependable and scalable manner.
Aparna P. More, Rohini S. Kale, M. Rizvi· Recent Advances in Computer...· 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
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