A new hybrid routing protocol called ERPMO (Energy-Aware Routing Protocol using Mayfly Optimization) could provide substantial improvements in energy efficiency, lifespan, and data reliability for Wireless Sensor Networks (WSNs), according to a recent study published in Scientific Reports.
Traditional WSN routing protocols such as LEACH and PEGASIS are usually limited in their ability to adapt to dynamic and changing network conditions and manage energy resources effectively.
The new ERPMO protocol overcomes these issues by integrating K-means clustering, the Mayfly Optimization Algorithm (MOA), and TDMA (Time Division Multiple Access) scheduling into a single framework.
The mayfly algorithm, modeled on the swarming and mating behavior of mayflies, plays a central role in the selection of optimal cluster heads.
Each node is evaluated using a multi-factor fitness function that considers residual energy, distance to the base station, energy consumption rate, and local node density. This adaptive selection helps prevent premature energy depletion in high-load nodes and balances the overall energy distribution.
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Efficient Clustering and Power Management
The protocol begins by organizing sensor nodes into clusters using K-means, reducing the distance between nodes and their designated cluster heads.
In cases where nodes fall outside a cluster’s optimal communication range or have significantly lower residual energy, ERPMO dynamically forms sub-clusters.
These are managed by sub-cluster heads that aggregate data locally and forward it to the main cluster head, reducing energy expenditure over long distances and better scalability.
TDMA complements the routing design by assigning specific time slots to each node for communication. This structured scheduling eliminates collisions and reduces idle listening, as nodes enter sleep mode when not actively transmitting.
The result is lower energy waste and smoother synchronization, particularly in dense sensor environments.
Reliable, Fast, and Energy-Efficient Performance
The ERPMO protocol demonstrated substantial gains during simulation. It extended network lifetime to 1285 operational rounds, marking a 56 % increase compared to traditional approaches.
Nodes maintained an average residual energy of 0.32 Joules in 100-node deployments, indicating balanced usage. Packet delivery remained reliable at 96.3 %, with only 3.7 % packet loss, while cluster head selection accuracy reached 91.2 %. The protocol’s fairness index of 0.79 confirmed equitable energy usage across nodes.
Convergence occurred within 35 iterations, outperforming other algorithms such as PSO (47 iterations) and GA (62 iterations), enabling faster adaptation to changing network conditions.
Tests across networks of 50, 100, and 150 nodes revealed that ERPMO maintained consistent performance, with only minor drops in energy efficiency and CH accuracy under extreme densities.
Even against other leading routing methods, ERPMO delivered lower per-round energy consumption at 0.18 Joules and reduced synchronization delay to 3.5 milliseconds.
It also achieved the highest data aggregation efficiency at 92.4 % and recorded the lowest control overhead at 6.4 KB.
These outcomes are likely a result of its use of fitness-based cluster head selection, adaptive re-clustering, and TDMA coordination.
WSNs with Mayfly Optimization: The Future?
ERPMO offers a strong, scalable, and energy-conscious solution for modern sensor network challenges.
Its hybrid design is especially suited for long-term use in areas such as environmental monitoring, healthcare, and smart infrastructure. Future research will extend the model to support mobility, heterogeneous node configurations, and security-aware communication for resilient real-world applications.
Journal Reference
Sinduja B., et al. (2025). An energy-aware routing protocol using mayfly optimization (ERPMO) and TDMA scheduling in wireless sensor networks. Scientific Reports, 15, 40492. DOI: 10.1038/s41598-025-24315-x