Energy-Efficient Sensor Activity Scheduling Protocol for Wireless Sensor Networks

Abstract

The power depletion is one of the critical issues in Wireless Sensor Networks (WSNs) since most sensor nodes are provided with limited power irreplaceable / rechargeable batteries. One fundamental way to minimize the power consumption is to exploit the spatial data correlation among the sensor nodes by reducing the number of active nodes especially in the dense sensor network. In this paper, we propose Energy-efficient Sensor Activity Scheduling (ESAS)  protocol for WSNs that periodically choose the best representative set of sensors that will be activated during the sensing phase in the current period. ESAS works into periods.
Each period is composed of three phases: data collection, decision, and sensing. ESAS measures the similarity degree among the sensor data that collected in the first phase and
makes a decision of which sensors stay active during the sensing phase in each period and put the other nodes into lowpower sleep mode with maximum level of accuracy. The simulation results are conducted based on real world datasets provided by Intel Berkeley Research Lab using OMNeT++ network simulator show that the effectiveness of the proposed
ESAS protocol in energy saving and extending the network lifetime.