Energy-aware scheduling of streaming applications on edge-devices in IoT based healthcare
Journal article
Authors | Tariq, Umair Ullah, Ali, Haider, Liu, Lu, Hardy, J., Kazim, M. and Ahmed, Waqar |
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Abstract | The reliance on Network-on-Chip (NoC) based Multiprocessor Systems-on-Chips (MPSoCs) is proliferating in modern embedded systems to satisfy the higher performance requirement of multimedia streaming applications. Task level coarse grained software pipeling also called re-timing when combined with Dynamic Voltage and Frequency Scaling (DVFS) has shown to be an effective approach in significantly reducing energy consumption of the multiprocessor systems at the expense of additional delay. In this paper we develop a novel energy-aware scheduler considering tasks with conditional constraints on Voltage Frequency Island (VFI) based heterogeneous NoC-MPSoCs deploying re-timing integrated with DVFS for real-time streaming applications. We propose a novel task level re-timing approach called R-CTG and integrate it with non linear programming based scheduling and voltage scaling approach referred to as ALI-EBAD. The R-CTG approach aims to minimize the latency caused by re-timing without compromising on energy-efficiency. Compared to R-DAG, the state-of-the-art approach designed for traditional Directed Acyclic Graph (DAG) based task graphs, R-CTG significantly reduces the re-timing latency because it only re-times tasks that free up the wasted slack. To validate our claims we performed experiments on using 12 real benchmarks, the results demonstrate that ALI-EBAD out performs CA-TMES-Search and CA-TMES-Quick task schedulers in terms of energy-efficiency. |
Keywords | Task analysis; Streaming media; Medical services |
Year | 2021 |
Journal | IEEE Transactions on Green Communications and Networking |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
ISSN | 2473-2400 |
Digital Object Identifier (DOI) | https://doi.org/10.1109/tgcn.2021.3056479 |
Web address (URL) | https://ieeexplore.ieee.org/document/9344830 |
https://dora.dmu.ac.uk/handle/2086/21144 | |
hdl:10545/625637 | |
Output status | Published |
Publication dates | 02 Feb 2021 |
Publication process dates | |
Deposited | 05 Mar 2021, 14:54 |
Accepted | 02 Jan 2021 |
Contributors | Central Queensland University, Sydney, Australia., University of Derby, University of Leicester, De Montfort University and UET, Taxila, Pakistan |
File | File Access Level Restricted |
File | File Access Level Restricted |
File | License File Access Level Open |
https://repository.derby.ac.uk/item/92qy3/energy-aware-scheduling-of-streaming-applications-on-edge-devices-in-iot-based-healthcare
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