An Energy-Efficient MAC Protocol for Linear Sensor Networks with Congestion-Aware Scheduling

The distinctive linear topology of Linear Sensor Networks (LSNs) has made them a popular area of study because of the many useful applications they have found, including structural health assessment, pipeline monitoring, and border surveillance. Energy efficiency must be a primary design objective for LSNs due to the fact that, despite their potential, their performance is severely limited by the energy resources available to sensor nodes. In this research, Staggered Cooperative Forwarding MAC (SCF-MAC) is designed for LSNs, which improves data flow efficiency and reduces idle listening and collision overheads. A 2-Dimensional Discrete-Time Markov Chain (2D-DTMC) model is proposed in this research to accurately represent and alleviate network bottlenecks, especially in the vicinity of the sink node, where congestion is most probable. The system may optimize transmission plans and buffer management policies by modeling transitions based on both retransmission attempts and queue buildup. This reduces packet drops and improves Throughput. This grid-based state representation allows for more precise energy-aware MAC scheduling by capturing the nodes’ probabilistic behavior in response to traffic load and link reliability. In several metrics, including Throughput, energy consumption, packet delivery ratio, and delay, SCF-MAC-2D-DTMC proves far superior to current state-of-the-art MAC protocols in rigorous discrete-time simulations. Longevity and dependability in linear sensor networks are improved by including the 2D-DTMC model into MAC protocol design, which leads to smarter and more adaptable channel access behavior.