Boosting Edge-to-Cloud Data Transmission Efficiency with Semantic Transcoding

The evolution of network systems is driven by the increasing demand for higher data transmission volumes and reduced latency. This paper presents a semantic method to reduce latency in core network systems to accommodate the growing demand for high-speed data transmission. We minimize unnecessary transmissions and optimize bandwidth by prioritizing data relevance through semantic communication technologies. Our approach utilizes a transformer-based model from edge servers to the cloud to achieve minimal end-to-end latency. Experimental results demonstrate that our methods can reduce latency by up to 30%, offering a scalable solution that significantly enhances network performance and efficiency.