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Energy efficient modified TDMA schedule for reducing energy consumption in Wireless Sensor Networks

Abstract

Wireless Sensor Networks comprise low-cost, low-power, lightweight, and multifunctional sensor nodes capable of sensing and transmitting data from remote or hazardous environments to a central base station. These networks are widely deployed across various domains, including environmental monitoring, healthcare, and military applications. However, designing energy-efficient routing protocols remains a challenge due to limited battery capacity, constrained computational resources, absence of global addressing, and the dynamic topology of self-organizing nodes. The Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol, a widely used cluster-based routing scheme, organizes nodes into clusters where cluster heads (CHs) manage intra-cluster communication using a Time Division Multiple Access (TDMA) schedule. Despite its advantages, LEACH’s TDMA mechanism becomes inefficient under unbalanced clustering, resulting in increased energy consumption at CHs. To overcome this issue, the Modified TDMA (MTDMA) approach was introduced, which adapts scheduling to the largest cluster size. However, MTDMA increases energy usage due to frequent inter-CH communication for determining cluster capacities. This study proposes the Energy-Efficient Modified Time Division Multiple Access (EEMTDMA) algorithm, where the base station centrally determines maximum cluster capacity, eliminating CH-to-CH communication and significantly reducing energy consumption. The algorithm was implemented using the Castalia 3.3 simulator in the OMNeT + + framework. Simulation results show that EEMTDMA outperforms both LEACH with MTDMA and LEACH with standard TDMA, achieving an average energy consumption of 48.4 J and delivering 4.75 packets per node to the base station. These results represent improvements of 7.9 J and 1.62 packets compared to LEACH with MTDMA, and 13.29 J and 2.33 packets compared to LEACH with TDMA.

Research topics

  • Energy Efficient Wireless Sensor Networks
  • Green IT and Sustainability
  • Wireless Networks and Protocols

Sustainable Development Goals

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DOI: 10.1007/s42452-025-08055-1

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