Energy-efficient scheduling based clustering approach for wireless sensor networks of IoT

Several Internet of Things (IoT) applications employ Wireless Sensor Networks (WSNs) in monitoring such as health-care, environment, transportation, agriculture, etc. These applications will produce a significant amount of data, which will pose a big challenge in the Big Data age. Scheduling is one of the energy-efficient mechanisms that can be used to deal with such a large volume of data. In this paper, an Energy-efficient Scheduling based Clustering Approach (ESCA) for Wireless Sensor Networks (WSNs) of IoT is proposed. ESCA works into rounds. each round composed of two periods. The first period consists of three steps: data collection, compressed transmission, and scheduling-based clustering. The scheduling algorithm plans the schedule for the WSN in the first period of each round for all the periods in the round. The second period consists of collection and compressed transmission. The active sensor nodes will only collect and transmit compressed data to the sink in the second period of each round. The simulation results based on real sensed data of the sensor network show that the proposed ESCA technique can reduce transmitted data up to 78.65% and decrease the energy consumption up to 98.13% in comparison with another method.