Battery-Aware Real-Time Task Scheduling in Wireless Sensor Networks

Authors:
Seungki Hong;Daeyoung Kim;Jae-eon Kim
Affiliations:
Information and Communications University;Information and Communications University;Information and Communications University
Venue:
RTCSA '05 Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications
Year:
2005

Citing 0
Cited 2

Energy budgeting for battery-powered sensors with a known task schedule

Proceedings of the 2006 IEEE/ACM international conference on Computer-aided design
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Abstract

Since the lifetime of a battery directly impacts the lifetime of sensor networks, one of the key considerations in the design of sensor networks is the ability to maximize battery lifetime. In this paper, we present (1) a task modeling methodology and (2) a battery-aware real-time task scheduling technique for sensor networks. The task modeling is achieved based on task classification in terms of the usage of resources on a micro-sensor system. For exploiting the recovery effect of battery, the battery-aware task scheduling algorithm composed of three phases is designed to maximize the lifetime of a battery while meeting the timing constraint of each task.