Adaptable Probabilistic Transmission Framework for Wireless Sensor Networks

The authors propose a novel framework that combines probabilistic transmission with Latin Squares characteristics to tune channel access, meeting various demands in network performance (Energy vs. Delay). The proposed technique is decentralized, scalable, and has low overhead. They develop an analytical model to estimate the network performance and validate the benefits of the proposed framework via simulation-based experiments. Smart sensor networks naturally apply to a broad range of applications with different requirements to network performance. One of the major requirements is proper energy utilization in Wireless Sensor Networks (WSN). At the same time, minimizing sensor query response time is equally crucial in mission-critical sensor networks.