Adaptive Online Scheduling for Asymmetric Wireless Sensor Networks

Abstract

Increasing onboard processing capabilities of sensors enable self-organization in wireless sensor networks to dynamically adapt to ad-hoc topologies and to react to task or network changes. Such self-organization, however, comes at a cost of additional energy consumption of the sensor nodes with already limited power resources. Energy limitations of sensor nodes in unattended environments require a trade-off between power consumption and topology maintenance. In this paper we present our adaptive online scheduling (AOS) protocol that exploits application based data flow characteristics to reduce power consumption during self-organization. Data flow characteristics is used to govern route selection, and to formulate a collision-free transmission schedule that enables risk-free sleeping time. Our simulation results suggest that AOS's transmission schedule provides more than 50% energy savings in steady state in comparison to SMACS