Solving Energy-Latency Dilemma: Task Allocation for Parallel Applications in Heterogeneous Embedded Systems

Parallel applications with energy and low-latency constraints are emerging in various networked embedded systems like digital signal processing, vehicle tracking, and infrastructure monitoring. However, conventional energy-driven task allocation schemes for a cluster of embedded nodes only concentrated on energy-saving when making allocation decisions. Consequently, the length of the schedules could be very long, which is unfavorable or in some situations even not tolerated. In this project, we address the issue of allocating a group of parallel tasks on a heterogeneous embedded system with an objective of energy-saving and short-latency. A novel task allocation strategy, or BEATA (Balanced EnergyAware Task Allocation), is developed to find an optimal allocation that minimizes overall energy consumption while confining the length of schedule to an ideal range. The rest of the proposal is organized as follows. In the next section we describe the motivation of this research. In Section 3, we propose the project summary. Project details are presented in Section 4. Section 5 concludes the proposal with summary and future directions.