CARE: carbon-aware computing for blockchain-enabled internet of medical things

The integration of blockchain technology with the internet of medical things (IoMT) offers numerous benefits in healthcare data management services. But such system faces storage bottleneck due to the onset of huge volume of medical data through electronic health record. Increased storage and intensive data management protocols escalate the carbon emission by the IoMT system. Traffic adaptive elastic storage and scalable mining prove to be advantageous for the IoMT in terms of efficient storage and low latency. However, the carbon footprint of the adaptive system is yet to be proved. Carbon footprint has become an important quality factor to measure the efficiency of the software systems. In this paper, we propose an efficient technique to measure the carbon footprint of the IoMT system. The assessment framework is modularized to accommodate different IoMT architectures with specific application modules. The proposed system is tested with three different architectures of IoMT applications with varied scale system complexity. The obtained carbon footprint of the systems conforms the logical chronology of the data processing architecture and rightly identifies the most carbon efficient framework. The proposed framework substantiates the inference with data obtained from rigorous experiments.