Threshold-based Energy Efficient Clustering Protocol for Corrosion Risk Monitoring of Reinforced Concrete

In recent years, wireless sensor networks (WSN) are being used by a wide range of applications. Sensor nodes are used for gathering data about the various physical parameters of the system under study. As sensor nodes are battery powered, energy efficiency is an important challenge faced by WSN. Clustering is a technique for improving the energy efficiency of the sensor network. The reported piece of work uses the soft computing technique, Biogeography-Based Krill Herd Algorithm (BBKH) for energy efficient clustering that results in improving the network lifetime. While cluster heads are selected, the rate adjustment is made for congestion mitigation. Likewise, a threshold based data forwarding method is also employed for further improvement of the network lifetime. Based on threshold principle, sending of similarly sensed data repeatedly is avoided. The network lifetime is compared before and later on using the threshold value. The obtained results after using the threshold concept are 18.80 % better than its threshold free counterpart. The proposed method is used in structural health monitoring (SHM) application where the corrosion risk is monitored in the reinforced concrete structures.