Energy-Efficient Architecture for Optimized IoT Data Transmission from Edge to Cloud

Abstract

Abstract Edge Computing and the Internet of Things (IoT) have recently experienced significant growth and transformed how data is processed and analyzed. Edge computing improves efficiency and reduces latency by processing data locally. However, transmitting data efficiently while conserving energy is still a major issue today, especially considering the volume and redundancy of data. The computational capacity and memory of edge gateways in the network's edge layers are limited, making it challenging to process data effectively. As a result, data transmission often becomes inefficient. To address this issue, our research introduces an energy-efficient architecture for edge gateways in the edge layer. This architecture leverages data deduplication and compression techniques for IoT data transmission from edge to cloud. The research's unique deduplication algorithm eliminates duplicate data, while the Lempel Ziv 4 compression algorithm compresses large data sets effectively. This method not only reduces energy consumption but also minimizes memory usage, facilitating quicker and more efficient data transmission. Consequently, this approach significantly alleviates energy consumption challenges and limited data processing capabilities in the edge layer.