A control-theoretic approach to dynamic voltage scheduling

Varma, Ankush; Ganesh, Brinda; Sen, Mainak; Choudhury, Suchismita Roy; Srinivasan, Lakshmi; Bruce, J.G.

doi:10.1145/951741.951744

Cited by 16 publications

(17 citation statements)

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“…In the control community, in contrast, it is typically used in control system design, as will be shown later in Section 6. Varma et al [37] have used a similar method called nqPID to predict CPU workload in dynamic voltage scaling systems. It proved quite effective and insensitive to parameter changes.…”

Section: Dealing With Packet Loss On Actuatorsmentioning

confidence: 99%

Wireless Sensor/Actuator Network Design for Mobile Control Applications

Xia

Tian

et al. 2007

Sensors

143

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Wireless sensor/actuator networks (WSANs) are emerging as a new generation of sensor networks. Serving as the backbone of control applications, WSANs will enable an unprecedented degree of distributed and mobile control. However, the unreliability of wireless communications and the real-time requirements of control applications raise great challenges for WSAN design. With emphasis on the reliability issue, this paper presents an application-level design methodology for WSANs in mobile control applications. The solution is generic in that it is independent of the underlying platforms, environment, control system models, and controller design. To capture the link quality characteristics in terms of packet loss rate, experiments are conducted on a real WSAN system. From the experimental observations, a simple yet efficient method is proposed to deal with unpredictable packet loss on actuator nodes. Trace-based simulations give promising results, which demonstrate the effectiveness of the proposed approach.

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Section: Dealing With Packet Loss On Actuatorsmentioning

confidence: 99%

Wireless Sensor/Actuator Network Design for Mobile Control Applications

Xia

Tian

et al. 2007

Sensors

143

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“…[45][46][47][48][49] Wu et al 45 that utilizes processors runtime statistics and an online learning algorithm to estimate the best suited voltage and frequency setting at any given point in time for multi-tasking systems. [45][46][47][48][49] Wu et al 45 that utilizes processors runtime statistics and an online learning algorithm to estimate the best suited voltage and frequency setting at any given point in time for multi-tasking systems.…”

Section: Dynamic Frequency Scalingmentioning

confidence: 99%

“…There are many works on power management mechanism that use DVFS technique. [45][46][47][48][49] Wu et al 45 propose a runtime with dynamic compilation voltage and frequency optimizer to improve energy efficiency. Varma et al 46 investigate the use of feedback loops for DVFS and consider system utilization for decision making.…”

Section: Dynamic Frequency Scalingmentioning

confidence: 99%

“…[45][46][47][48][49] Wu et al 45 propose a runtime with dynamic compilation voltage and frequency optimizer to improve energy efficiency. Varma et al 46 investigate the use of feedback loops for DVFS and consider system utilization for decision making. Kondo 47 propose an algorithm for improving the total instruction throughput, fairness, and energy efficiency of single chip multiprocessors.…”

Section: Dynamic Frequency Scalingmentioning

confidence: 99%

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Power and performance optimization in FPGA‐accelerated clouds

Tesfatsion

Proaño

Tomás

et al. 2018

Concurrency and Computation

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Energy management has become increasingly necessary in data centers to address all energy-related costs, including capital costs, operating expenses, and environmental impacts.Heterogeneous systems with mixed hardware architectures provide both throughput and processing efficiency for different specialized application types and thus have a potential for significant energy savings. However, the presence of multiple and different processing elements increases the complexity of resource assignment. In this paper, we propose a system for efficient resource management in heterogeneous clouds. The proposed approach maps applications' requirement to different resources reducing power usage with minimum impact on performance. A technique that combines the scheduling of custom hardware accelerators, in our case, Field-Programmable Gate Arrays (FPGAs) and optimized resource allocation technique for commodity servers, is proposed. We consider an energy-aware scheduling technique that uses both the applications' performance and their deadlines to control the assignment of FPGAs to applications that would consume the most energy. Once the scheduler has performed the mapping between a VM and an FPGA, an optimizer handles the remaining VMs in the server, using vertical scaling and CPU frequency adaptation to reduce energy consumption while maintaining the required performance. Our evaluation using interactive and data-intensive applications compare the effectiveness of the proposed solution in energy savings as well as maintaining applications performance, obtaining up to a 32% improvement in the performance-energy ratio on a mix of multimedia and e-commerce applications.

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“…Many studies consider the control theoretic method to increase feedback task-based DVS performance. [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Feedback Fuzzy-PI Control dynamic voltage scaling for real-time control tasks

Cho

Lee

Jeon

et al. 2009

2009 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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Many industrial controller use real-time OS as control systems have become more complex and control many targets. Thus, as CPU frequency increases, so power consumption increases. Dynamic Voltage/Frequency Scaling is an important issue to consider the power awareness problem in real-time scheduling of embedded systems. The DVS technique is important to control tasks in embedded systems, since DVS, efficiency changes controller performance. If control performance increases, then power consumption increases. That is, if power consumption decreases, then control performance decreases. High control performance and low power consumption are important. Much research has been conducted to solve this problem. In this paper, we propose the feedback Fuzzy-PI Control DVS method to control tasks in real-time embedded systems. Then, we explain the hard real-time mechanism in the feedback Fuzzy-PI Control method for control tasks. Simulation shows the task-based feedback Fuzzy-PI Control DVS performance and Missed Deadline Rate.

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A control-theoretic approach to dynamic voltage scheduling

Cited by 16 publications

References 0 publications

Wireless Sensor/Actuator Network Design for Mobile Control Applications

Wireless Sensor/Actuator Network Design for Mobile Control Applications

Power and performance optimization in FPGA‐accelerated clouds

Feedback Fuzzy-PI Control dynamic voltage scaling for real-time control tasks

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