Energy-Efficient Dynamic and Adaptive State-Based Scheduling (EDASS) Scheme for Wireless Sensor Networks

Today is the era of super-connectivity, where real-world things connect, gather real-time data from their surroundings and disseminate the recorded data into the environment. The users can access services without understanding the basic composite structure of heterogeneous devices and hybrid IoT infrastructure. Data is collected, managed, and processed by minute and plug-able sensors for the IoT paradigm. Due to the resource-constrained nature of these sensors, massive and recurrent tasks create congestion in the network and drain the energy of sensors. Sending unnecessary and redundant data packets is life-threatening and affects the availability of other resources. This paper proposes a novel scheme, an “Energy-Efficient Dynamic and Adaptive State-based Scheduling” (EDASS) for Wireless Sensor Network. The suggested method switches nodes between states dynamically and adapts to new states based on the contents of sensed data packets. Four distinct states of energy are derived from a combination of internal modules of the sensor. The typical sequence of operation is abruptly changed, and all sensors become active when a new event occurs. EDASS decreases energy consumption by 29% in live nodes, 41% in message overhead and 33% in the cluster head selection process. At the same time, the average delay in EDASS increases from 1.26 ms to 1.39 ms due to control message overhead.