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Energy Optimized Task Mapping for Reliable and Real-Time Networked Systems

Mo, Lei ; Zhou, Qi ; Kritikakou, Angeliki ; Cao, Xianghui

ACM transactions on sensor networks, 2023-11, Vol.19 (4), p.1-26 [Periódico revisado por pares]

New York, NY: ACM

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Título:
Energy Optimized Task Mapping for Reliable and Real-Time Networked Systems
Autor: Mo, Lei ; Zhou, Qi ; Kritikakou, Angeliki ; Cao, Xianghui
Assuntos: Computer Science ; Computer systems organization ; Embedded Systems ; Networking and Internet Architecture ; Networks ; Networks / Network services ; Software and its engineering ; Software and its engineering / Software organization and properties ; Theory of computation ; Theory of computation / Design and analysis of algorithms ; Theory of computation / Design and analysis of algorithms / Online algorithms ; Theory of computation / Design and analysis of algorithms / Online algorithms / Online learning algorithms ; Theory of computation / Design and analysis of algorithms / Online algorithms / Online learning algorithms / Scheduling algorithms ; Theory of computation / Theory and algorithms for application domains ; Theory of computation / Theory and algorithms for application domains / Machine learning theory ; Theory of computation / Theory and algorithms for application domains / Machine learning theory / Reinforcement learning ; Theory of computation / Theory and algorithms for application domains / Machine learning theory / Reinforcement learning / Sequential decision making
É parte de: ACM transactions on sensor networks, 2023-11, Vol.19 (4), p.1-26
Descrição: Energy efficiency, real-time response, and data transmission reliability are important objectives during networked systems design. This paper aims to develop an efficient task mapping scheme to balance these important but conflicting objectives. To achieve this goal, tasks are triplicated to enhance reliability and mapped on the wireless nodes of the networked systems with Dynamic Voltage and Frequency Scaling (DVFS) capabilities to reduce energy consumption while still meeting real-time constraints. Our contributions include the mathematical formulation of this task mapping problem as mixed-integer programming that balances node energy consumption, enhancing data reliability, under real-time and energy constraints. Compared with the State-of-the-Art (SoA), a joint-design problem is considered in this paper, where DVFS, task triplication, task allocation, and task scheduling are optimized concurrently. To find the optimal solution, the original problem is linearized, and a decomposition-based method is proposed. The optimality of the proposed method is proved rigorously. Furthermore, a heuristic based on the greedy algorithm is designed to reduce the computation time. The proposed methods are evaluated and compared through a series of simulations. The results show that the proposed triplication-based task mapping method on average achieves 24.84% runtime reduction and 28.62% energy saving compared to the SoA methods.
Editor: New York, NY: ACM
Idioma: Inglês

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Energy Optimized Task Mapping for Reliable and Real-Time Networked Systems

Mo, Lei ; Zhou, Qi ; Kritikakou, Angeliki ; Cao, Xianghui

New York, NY: ACM

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