Energy efficient scheduling for parallel applications on mobile clusters
Cluster Computing
Utility-based scheduling for grid computing under constraints of energy budget and deadline
Computer Standards & Interfaces
Energy constrained resource allocation optimization for mobile grids
Journal of Parallel and Distributed Computing
Energy-aware grid resource scheduling: model and algorithm
International Journal of Computer Applications in Technology
Energy efficient resource management in mobile grid
Mobile Information Systems
Towards Adaptive Power-Aware Scheduling for Real-Time Tasks on DVS-Enabled Heterogeneous Clusters
GREENCOM-CPSCOM '10 Proceedings of the 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing
Tradeoffs between energy consumption and QoS in mobile grid
The Journal of Supercomputing
Rolling-horizon scheduling for energy constrained distributed real-time embedded systems
Journal of Systems and Software
Adaptive energy-efficient scheduling for real-time tasks on DVS-enabled heterogeneous clusters
Journal of Parallel and Distributed Computing
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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 concentrate 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 paper, 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 Energy- Aware Task Allocation), is developed to find an optimal allocation that minimizes overall energy consumption while confining the length of schedule to an ideal range. Experimental results show that BEATA significantly improves the performance of embedded systems in terms of energy-saving and schedule length over an existing allocation scheme.