Study of the Impact of Data Compression on the Energy Consumption Required for Data Transmission in a Microcontroller-Based System

As the number of Internet of Things (IoT) devices continues to rise dramatically each day, the data generated and transmitted by them follow similar trends. Given that a significant portion of these embedded devices operate on battery power, energy conservation becomes a crucial factor in their design. This paper aims to investigate the impact of data compression on the energy consumption required for data transmission. To achieve this goal, we conduct a comprehensive study using various transmission modules in a severely resource-limited microcontroller-based system designed for battery power. Our study evaluates the performance of several compression algorithms, conducting a detailed analysis of computational and memory complexity, along with performance metrics. The primary finding of our study is that by carefully selecting an algorithm for compressing different types of data before transmission, a significant amount of energy can be saved. Moreover, our investigation demonstrates that for a battery-powered embedded device transmitting sensor data based on the STM32F411CE microcontroller, the recommended transmission module is the nRF24L01+ board, as it requires the least amount of energy to transmit one byte of data. This module is most effective when combined with the LZ78 algorithm for optimal energy and time efficiency. In the case of image data, our findings indicate that the use of the JPEG algorithm for compression yields the best results. Overall, our research underscores the importance of selecting appropriate compression algorithms tailored to specific data types, contributing to enhanced energy efficiency in IoT devices.

Effects of insulin and beta-adrenergic blockade on certain indicators of carbohydrate metabolism in the blood and tissues of rats during short-lasting hypothermia

Administration of insulin 1 i.u./100 g of body weight to hypothermic rats causes a fall of glucose and lactate levels in the serum and a rise in myocardial glycogen level in relation to the group of control rats kept at room temperature and to the group of rats subjected only to hypothermia. Beta-adrenergic blockade (propranolol 0.6-1 mg/kg) caused no changes in the levels of carbohydrate metabolites in the serum of hypothermic rats but raised the myocardial glycogen level by 42% in relation to the animals subjected only to hypothermia. Simultaneous administration of both these agents during hypothermia produces a fall of the serum levels of glucose and pyruvate with a rise in the level of lactate, and raises the glycogen level in the myocardium (by about 161%) and in the skeletal muscle (by 54%) in relation to the rats subjected to hypothermia alone. Insulin and/or propranolol fail to prevent glycogen reserve exhaustion in the liver of hypothermic rats which could be due to activation of non-blocked alpha-adrenergic receptors or to the action of yet another glycogenolytic agent, e.g. glucagon, during hypothermia.