A GA-Based Sustainable and Secure Green Data Communication Method Using IoT-Enabled WSN in Healthcare

This paper proposes an optimized Genetic Algorithm (GA) based sustainable and secure green data collection/transmission method for IoT enabled WSN in healthcare by optimizing intra cluster distance, systematic utilization of node’s energy and reducing hop count. For secure transmission of data, the communication data is encrypted us ing stream cipher and a pseudo randomly generated security key. Additionally, the proposed movable sink and data collection/transmission strategies shorten communication distance between sink and cluster head (CH) which diminishes the hotspot problem. The direct data collection helps in transmitting data directly to the sink, when the sinks are nearer to the sensor nodes with re spect to CH. Further, the incorporated dynamic sensing range minimizes overlapping of sensing range with a significant decrement in the transmission energy. The simulation results show that the proposed protocol outperforms the existing protocols on the performance metrics such as remaining energy, lifetime, stability period, throughput and number of clusters per rounds.