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Energy harvesting capacity facilitates the perpetual operation of wireless sensor networks. In addition to battery-based systems, harvested energy significantly varies depending on the deployed environment. Therefore, the system must schedule its workload based on current energy reserves and predictions of additional energy. In this case, the efficiency of scheduling is highly sensitive to the energy...
Variable task execution time causes more complexity in task scheduling and thermal management. In this paper, we introduce a discrete probability distribution model to capture the variation of task execution time. And then we propose a slack-time-aware two-phase scheduling framework for parallel applications running on heterogeneous MPSoCs. It exploits slack time among tasks with precedence constraints...
Recent research shows that significant energy of sensor nodes can be saved in wireless sensor networks with a mobile element called Data Mule (DM) for data collection via short-range communications. However, a major performance bottleneck is the increased data delivery latency, so it is critical to optimize the DM motion, including the path and the speed. In this paper, path selection is formulated...
Many stream-based applications have real-time performance requirements for continuous queries over time varying data streams. In order to address this challenge, a real-time continuous query model is presented to process multiple queries with timing constraints. In this model, the execution of one tuple passing through an operator path is modeled as a real-time task instance. A fine-grained scheduling...
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