Energy-Aware Scheduling for Real-Time Systems

Bambagini, Mario; Marinoni, Mauro; Aydın, Hakan; Buttazzo, Giorgio

doi:10.1145/2808231

Cited by 146 publications

(87 citation statements)

References 76 publications

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“…Simulation is then set to run in five processor speed level: 0.6, 0.7, 0.8, 0.9 and 1.0. Speed level below 0.5 is not tested because it is not energy efficient (Bambagini et al, 2016) and increases the risk of missing deadline.…”

Section: Simulationmentioning

confidence: 99%

Energy performance evaluation for dynamic frequency scaling on rate monotonic and earliest deadline first scheduling algorithm

Sabri¹

2018

Int. j. adv. appl. sci.

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Dynamic Voltage and Frequency Scaling (DVFS) algorithm is widely used to reduce processor's energy consumption in mixed-criticality systems. Existing works show that there are more DVFS algorithms were developed based on Earliest Deadline First (EDF) scheduling scheme compared to Rate Monotonic (RM) scheduling scheme. To understand the reason why EDF is prevalent for DVFS algorithms, simulation can be done to get the power consumption of both scheduling schemes. However, there is no simulation tools available dedicated for this purpose. This research aims to investigate power consumption of both scheduling schemes under different processor speed levels using SimSo simulator. The processor's utilization and schedulability are determined using a set of task in SimSo. Power consumption for Least Common Multiple of tasks period is then calculated based on the proposed power model. The result shows that EDF performs better than RM and able to reduce 30% of energy at processor speed of 0.7. In addition, the capability of SimSo to be used in DVFS algorithm creation also had been observed. It is found that SimSo can be used for further research with additional codes.

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Section: Simulationmentioning

confidence: 99%

Energy performance evaluation for dynamic frequency scaling on rate monotonic and earliest deadline first scheduling algorithm

Sabri¹

2018

Int. j. adv. appl. sci.

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“…E.g. energy and temporal constraints [99], fault tolerance and temporal constraints [68], security and temporal constraints [100], system and environment states and priority of tasks [101], etc. Furthermore, a recommended method of multithreading multi-agent scheduling was proposed to search the efficient and fast solution of complex problems in real-time featuring rapid dynamic changes and uncertainty [98].…”

Section: Vandv On Real-time Schedulabilitymentioning

confidence: 99%

A Comprehensive Technological Survey on Dependable Self-Managing CPS: The Decade of Researches on Correctness and Dependability

Zhou¹,

Hou²,

Zhang³

et al. 2017

Preprint

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Though Cyber Physical Systems (CPS) become very popular in last the decade, dependability of CPS is still a critical issue and related survey is rare. We try to spell out the jigsaw of technologies and figure out the technical trends of dependable self-managing CPS. This survey first recalls the motivation and the similar concepts. By analyzing four generic architectures, we summarize the common characteristics and related assurance technologies, and propose a more generic environment-in-loop processing flow of CPS and a formal interaction flow between physical space and cyber space. Further, the similarity between correctness and dependability is formally analyzed and the new five research questions of dependable self-managing CPS are presented. Then we review the critical technologies and related correctness verification & validation (V&V) methods, the architectures for dependable self-managing CPS. Further, the detail dependability management and V&V technologies are surveyed, which covers the areas of running-time fault management methods and whole life cycle V&V technologies, maintenance and available tool sets. For holistic CPS development, Modeling techniques and MDE (model driven engineering) based V&V methods are analyzed in detail. Then we complete the jigsaw of technologies and figure out the missing part. Further, we propose the technical challenges and the further direction. To our best knowledge, this is the first comprehensive survey on dependable self-managing CPS development and evaluation.

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“…DPM and DVFS are also studied in the real-time research area [10,24,25]. Bambagini et al present a survey paper that discusses various energy-aware scheduling algorithms for real-time mobile systems [24].…”

Section: Dpm/dvfsmentioning

confidence: 99%

An Adaptive and Integrated Low-Power Framework for Multicore Mobile Computing

Choi

Jung

Choi

et al. 2017

Mobile Information Systems

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Employing multicore in mobile computing such as smartphone and IoT (Internet of Things) device is a double-edged sword. It provides ample computing capabilities required in recent intelligent mobile services including voice recognition, image processing, big data analysis, and deep learning. However, it requires a great deal of power consumption, which causes creating a thermal hot spot and putting pressure on the energy resource in a mobile device. In this paper, we propose a novel framework that integrates two well-known low-power techniques, DPM (Dynamic Power Management) and DVFS (Dynamic Voltage and Frequency Scaling) for energy efficiency in multicore mobile systems. The key feature of the proposed framework is adaptability. By monitoring the online resource usage such as CPU utilization and power consumption, the framework can orchestrate diverse DPM and DVFS policies according to workload characteristics. Real implementation based experiments using three mobile devices have shown that it can reduce the power consumption ranging from 22% to 79%, while affecting negligibly the performance of workloads.

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Energy-Aware Scheduling for Real-Time Systems

Cited by 146 publications

References 76 publications

Energy performance evaluation for dynamic frequency scaling on rate monotonic and earliest deadline first scheduling algorithm

Energy performance evaluation for dynamic frequency scaling on rate monotonic and earliest deadline first scheduling algorithm

A Comprehensive Technological Survey on Dependable Self-Managing CPS: The Decade of Researches on Correctness and Dependability

An Adaptive and Integrated Low-Power Framework for Multicore Mobile Computing

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