RSSI-guided cluster head selection for optimal optimization in IoT-enabled WSNs - Azamuddin, Ab Rahman (Institute of Electrical and Electronics Engineers Inc., 2023)
The Internet of Things (IoT) relies on Wireless Sensor Networks (WSN) to collect physical data from the environment. Sensor nodes in WSN have limited resources such as memory, energy, and processing power, and data transmission consumes the most energy. Therefore, clustering and data aggregation techniques are designed to achieve energy efficiency in WSN. This research paper proposes a new method, called Energy Efficient of Cluster Head and Relay Node (EECR), which selects Cluster Heads (CH) based on residual energy, distance to the Base Station (BS), and Received Signal Strength Indicator (RSSI). The EECR technique, which uses fuzzy logic for cluster head selection. The aggregated data of the cluster head is then transmitted to the BS to achieve energy efficiency. The EECR technique was tested under three different scenarios and achieved better results in terms of energy efficiency and network lifetime compared to SEP, MAP and EECR 1.