Abstract
Energy efficiency is considered as a critical requirement for wireless sensor networks. As more wireless sensor nodes are equipped with multi-cores, there are emerging needs for energy-efficient real-time scheduling algorithms. The T-L plane-based scheme is known to be an optimal global scheduling technique for periodic real-time tasks on multi-cores. Unfortunately, there has been a scarcity of studies on extending T-L plane-based scheduling algorithms to exploit energy-saving techniques. In this paper, we propose a new T-L plane-based algorithm enabling energy-efficient real-time scheduling on multi-core sensor nodes with dynamic power management (DPM). Our approach addresses the overhead of processor mode transitions and reduces fragmentations of the idle time, which are inherent in T-L plane-based algorithms. Our experimental results show the effectiveness of the proposed algorithm compared to other energy-aware scheduling methods on T-L plane abstraction.
Highlights
A wireless sensor network (WSN) consists of spatially-distributed autonomous sensors to measure/monitor various conditions and transmit the collected data using wireless communications.WSNs are considered as a promising approach, enabling a wide spectrum of applications, such as area surveillance, traffic flow measurement, object tracking, and environment monitoring.Due to the emerging demands for advanced applications, such as video sensor networks with image sensors and smart cameras, single-core embedded wireless sensor nodes face high-performance computation challenges
It is anticipated that more processors for high-end embedded systems will be equipped with Voltage frequency scaling (VFS) and dynamic power management (DPM) [6,11]
We present a new T-L plane-based scheduling algorithm for DPM-enabled multi-processors, which considers mode transition overhead and reduces fragmentations of the idle time
Summary
A wireless sensor network (WSN) consists of spatially-distributed autonomous sensors to measure/monitor various conditions and transmit the collected data using wireless communications. We propose new events and associated algorithms to enable better energy management for multi-core sensor nodes operating with a T-L plane-based scheduling algorithm. The previous technique [7] was generalized to prefetch the tokens originally scheduled to the future planes, as well as the very one, and execute them during an idle interval whose length is too short to switch the processor into sleep mode. These efforts reduce the fragmented idle time durations and increase the chance of longer idle blocks where the sensor processors can be placed into sleep mode.
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