Energy saving mechanism in fog assisted IoT enabled health monitoring framework

Abstract

This proposed research work discusses fog assisted IoT enabled health monitoring system performance. This system support local processing nearer the client machine for faster service and removing redundant data. This architecture is suitable for heavy traffic health data monitoring system like old or child monitoring or fitness care monitoring system. After processing huge data, only filtering data will be forwarded to cloud for processing. To transfer the huge amount of health monitoring data form IoT layer to Data Management and Processing Layer (DMPL) consume lots of energy. To minimize the energy requirement in the fog assisted DMPL layer, we adopt sleep mode operation and batch transferring data packet transfer technology. This paper studies the effect of sleeping mode on mean delay, number of data packets in the buffer and probability of blocking. The results show that proposed approach saves energy and effective framework for fog assisted health monitoring framework.