Throughput Optimization in Wireless Sensor Networks: Techniques, Challenges, and Future Directions

Wireless Sensor Networks (WSNs) are pivotal in enabling a wide range of applications, including environmental monitoring, industrial automation, smart agriculture, healthcare systems, and military surveillance. These networks consist of spatially distributed sensor nodes that collect and transmit data wirelessly, often in harsh or remote environments. A critical performance metric in WSNs is throughput, which refers to the amount of data successfully transmitted over the network within a given time frame. However, achieving high throughput is inherently challenging due to constraints such as limited energy resources, bandwidth restrictions, processing capabilities, and dynamic network conditions. Balancing throughput with other essential parameters like energy efficiency, reliability, and network lifetime is a major research focus. This paper presents a comprehensive review of existing techniques aimed at improving throughput in WSNs. Furthermore, it introduces a novel, integrated framework that leverages adaptive MAC protocols, in-network data aggregation, and cross-layer optimization to enhance throughput without sacrificing overall network performance or sustainability.