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Your search keyword '"Dai, Xiaotian"' showing total 10 results
Start Over Author "Dai, Xiaotian" Publisher ieee
10 results on '"Dai, Xiaotian"'

4. Toward an Analysable, Scalable, Energy-Efficient I/O Virtualization for Mixed-Criticality Systems.

Author

Jiang, Zhe, Dai, Xiaotian, Dong, Pan, Wei, Ran, Yang, Dawei, Audsley, Neil C., and Guan, Nan

Subjects
*ENERGY management, *TASK analysis
Abstract

In mixed-criticality systems (MCSs), timely handling of I/O operations is a key for the system being successfully implemented and appropriately functioned. The I/O system for an MCS must simultaneously enable different features, including isolation/separation, timing-predictability, performance, scalability, and energy-efficiency. Moreover, such an I/O system also requires to manage I/O resource in an adaptive manner to facilitate efficient yet safe resource sharing among components of different criticality levels. Existing approaches cannot achieve all of these requirements simultaneously. This article presents a mixed-criticality I/O management framework, termed MCS-IOV. MCS-IOV is based on hardware-assisted virtualization, which provides temporal and spatial isolation and prohibits fault propagation with limited extra overhead. MCS-IOV extends a real-time I/O virtualization system, by supporting the concept of mixed criticalities and customized interfaces for schedulers, which offers good timing predictability and scalability. Finally, we introduce an energy management framework for MCS-IOV, ensuring the power-efficiency of the design. The MCS-IOV is the first systematical solution that fulfills all the requirements as a mixed-criticality I/O system. [ABSTRACT FROM AUTHOR]

Published
2022
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8. Nonintrusive load monitoring based on particle swarm optimization

Author

Yi Guo, Dai Xiaotian, Xia Liu, XiaoLan Wang, and Qi Fu

Subjects
Fitness function, Training set, Computer science, 020209 energy, Nonintrusive load monitoring, Particle swarm optimization, Initialization, 02 engineering and technology, 010501 environmental sciences, 01 natural sciences, Power (physics), Control theory, Distortion, 0202 electrical engineering, electronic engineering, information engineering, 0105 earth and related environmental sciences
Abstract

This paper improves a nonintrusive load monitoring (NILM) algorithm based on Particle Swarm Optimization (PSO). The initialization part of PSO is optimized, and the algorithm consumption time is reduced when the accuracy is guaranteed. At the same time, the distortion power is introduced into the fitness function, and two new parameters are added to constrain the optimal solution. In order to verify the algorithm, load disaggregation tests were performed on eight commonly used household appliances. The experimental result results show that the average accuracy rate is 95.6% and the highest accuracy rate is 98.8% without a large amount of training data.

Published
2019

10. Discretization and stabilization of energy-based controller for period switching control and flexible scheduling

Author

Tafrishi, Seyed Amir, Dai, Xiaotian, Hirata, Yasuhisa, Burns, Alan, Tafrishi, Seyed Amir, Dai, Xiaotian, Hirata, Yasuhisa, and Burns, Alan

Abstract

Emerging advanced control applications, with increased complexity in software but limited computing resources, suggest that real-time controllers should have adaptable designs. These control strategies also should be designed with consideration of the run-time behavior of the system. One of such research attempts is to design the controller along with the task scheduler, known as control-scheduling co-design, for more predictable timing behavior as well as surviving system overloads. Unlike traditional controller designs, which have equal-distance sampling periods, the co-design approach increases the system flexibility and resilience by explicitly considering timing properties, for example using an event-based controller or with multiple sampling times (non-uniform sampling and control). Within this context, we introduce the first work on the discretization of an energy-based controller that can switch arbitrarily between multiple periods and adjust the control parameters accordingly without destabilizing the system. A digital controller design based on this paradigm for a DC motor with an elastic load as an example is introduced and the stability condition is given based on the proposed Lyapunov function. The method is evaluated with various computer-based simulations which demonstrate its effectiveness.

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