Synthesis and Optimization of Digital Circuits
Synthesis and Optimization of Digital Circuits
Adaptive Online Data Compression
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
Impact of Data Compression on Energy Consumption of Wireless-Networked Handheld Devices
ICDCS '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
Energy-balanced task allocation for collaborative processing in wireless sensor networks
Mobile Networks and Applications
An energy efficient model for monitoring and detecting atrial fibrillation in wearable computing
Proceedings of the 7th International Conference on Body Area Networks
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Energy consumption is a critical parameter in wireless healthcare systems which consist of battery operated devices such as sensors and local aggregators. The system battery lifetime depends on the allocation of processing, sensing, and communication tasks to devices of the system. In this paper, we optimize the battery life of a wireless healthcare system by efficiently assigning tasks to the available resources. There are several dynamically changing characteristics in the system, such as task parameters (processing complexity, arrival rate, and output data), each device's available battery capacity, varying wireless channel conditions, and network load. Our dynamic task assignment algorithm, "DynAHeal" adapts to such changing conditions, and improves the battery life. Our experiments show that the task assignment given by DynAHeal improves the overall system lifetime under varying dynamic conditions on an average 60% relative to sending all the data for processing to the base station, and 35% with respect to an optimal static design time assignment.