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Xianghui Cao

Bio: Xianghui Cao is an academic researcher from Southeast University. The author has contributed to research in topics: Wireless network & Wireless sensor network. The author has an hindex of 28, co-authored 128 publications receiving 2597 citations. Previous affiliations of Xianghui Cao include Zhejiang University & Illinois Institute of Technology.


Papers
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Journal ArticleDOI
TL;DR: This paper proposes and evaluates a new distributed estimation and collaborative control scheme for industrial control systems with WSANs and shows that the proposed method effectively achieves control objectives and maintains robust against inaccurate system parameters.
Abstract: Wireless sensor and actuator networks (WSANs) bring many benefits to industrial automation systems. When a control system is integrated by a WSAN, and particularly if the network scale is large, distributed communication and control methods are quite necessary. However, unreliable wireless and multihop communications among sensors and actuators cause challenges in designing such systems. This paper proposes and evaluates a new distributed estimation and collaborative control scheme for industrial control systems with WSANs. Extensive results show that the proposed method effectively achieves control objectives and maintains robust against inaccurate system parameters. We also discuss how to dynamically extend the scale of a WSAN with only local adjustments of sensors and actuators.

283 citations

Journal ArticleDOI
TL;DR: This paper develops a CC scheme in which control decisions are made based on global information and a DC scheme which enables distributed actuators to make control decisions locally and proposes a method for reducing packet-loss rate.
Abstract: This paper considers joint problems of control and communication in wireless sensor and actuator networks (WSANs) for building-environment control systems. In traditional control systems, centralized control (CC) and distributed control (DC) are two major approaches. However, little work has been done in comparing the two approaches in joint problems of control and communication, particularly in WSANs serving as components of control loops. In this paper, we develop a CC scheme in which control decisions are made based on global information and a DC scheme which enables distributed actuators to make control decisions locally. We also develop methods that enable wireless communications among system devices compatible with the control strategies, and propose a method for reducing packet-loss rate. We compare the two schemes using simulations in many aspects. Simulation results show that the DC can achieve a comparable control performance of the CC, while the DC is more robust against packet loss and has lower computational complexity than the CC. Furthermore, the DC has shorter actuation latency than the CC under certain conditions.

185 citations

Journal ArticleDOI
TL;DR: A scalable hybrid MAC protocol, which consists of a contention period and a transmission period, is designed for heterogeneous M2M networks and analytical and simulation results demonstrate the effectiveness of the proposed hybridMAC protocol.
Abstract: A robust and resilient medium access control (MAC) protocol is crucial for numerous machine-type devices to concurrently access the channel in a machine-to-machine (M2M) network. Simplex (reservation- or contention-based) MAC protocols are studied in most literatures which may not be able to provide a scalable solution for M2M networks with large number of heterogeneous devices. In this paper, a scalable hybrid MAC protocol, which consists of a contention period and a transmission period, is designed for heterogeneous M2M networks. In this protocol, different devices with preset priorities (hierarchical contending probabilities) first contend the transmission opportunities following the convention-based $p$ -persistent carrier sense multiple access (CSMA) mechanism. Only the successful devices will be assigned a time slot for transmission following the reservation-based time-division multiple access (TDMA) mechanism. If the devices failed in contention at previous frame, to ensure the fairness among all devices, their contending priorities will be raised by increasing their contending probabilities at the next frame. To balance the tradeoff between the contention and transmission period in each frame, an optimization problem is formulated to maximize the channel utility by finding the key design parameters: the contention duration, initial contending probability, and the incremental indicator. Analytical and simulation results demonstrate the effectiveness of the proposed hybrid MAC protocol.

177 citations

Journal ArticleDOI
TL;DR: A new system is designed in detail to perform micro-environmental monitoring taking the advantages of the WSN, and the system platform for data acquisition, validation, processing and visualization is systematically presented.
Abstract: Wireless Sensor Network (WSN) is increasingly popular in the field of micro-environmental monitoring due to its promising capability. However, most systems using WSN for environmental monitoring reported in the literature are developed for specific applications without functions for exploiting user's data processing methods. In this paper, a new system is designed in detail to perform micro-environmental monitoring taking the advantages of the WSN. The application-oriented hardware working style is designed, and the system platform for data acquisition, validation, processing and visualization is systematically presented. Several strategies are proposed to guarantee the system capability in terms of extracting useful information, visualizing events to their authentic time are also described. Moreover, a web-based surveillance subsystem is presented for remote control and monitoring. In addition, the system is extensible for engineers to carry their own data analysis algorithms. Experimental results are to show the path reliability and real-time characteristics, and to display the feasibility and applicability of the developed system into practical deployment.

171 citations

Journal ArticleDOI
TL;DR: Cognitive radio is introduced into the smart grid to improve the communication quality by means of spectrum sensing and channel switching and it is proved that there exists a unique optimal sensing time which yields the maximum tradeoff revenue.
Abstract: Smart grid is widely considered to be the next generation of power grid, where power generation, management, transmission, distribution, and utilization are fully upgraded to improve agility, reliability, efficiency, security, economy, and environmental friendliness. Demand response management (DRM) is recognized as a control unit of the smart grid, with the attempt to balance the real-time load as well as to shift the peak-hour load. Communications are critical to the accuracy and optimality of DRM, and hence at the core of the control performance of the smart grid. In this paper, we introduce cognitive radio into the smart grid to improve the communication quality. By means of spectrum sensing and channel switching, smart meters can decide to transmit data on either an original unlicensed channel or an additional licensed channel, so as to reduce the communication outage. Considering the energy cost taxed by spectrum sensing together with the control performance degradation incurred by imperfect communications, we formulate the sensing-performance tradeoff problem between better control performance and lower communication cost, paving the way towards a green smart grid. The impact of the communication outage on the control performance of DRM is also analyzed, which reduces the profit of power provider and the social welfare of the smart grid, although it may not always decrease the profit of power consumer. By employing the energy detector, we prove that there exists a unique optimal sensing time which yields the maximum tradeoff revenue, under the constraint that the licensed channel is sufficiently protected. Numerical results are provided to validate our theoretical analysis.

155 citations


Cited by
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Christopher M. Bishop1
01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

10,141 citations

01 Nov 1981
TL;DR: In this paper, the authors studied the effect of local derivatives on the detection of intensity edges in images, where the local difference of intensities is computed for each pixel in the image.
Abstract: Most of the signal processing that we will study in this course involves local operations on a signal, namely transforming the signal by applying linear combinations of values in the neighborhood of each sample point. You are familiar with such operations from Calculus, namely, taking derivatives and you are also familiar with this from optics namely blurring a signal. We will be looking at sampled signals only. Let's start with a few basic examples. Local difference Suppose we have a 1D image and we take the local difference of intensities, DI(x) = 1 2 (I(x + 1) − I(x − 1)) which give a discrete approximation to a partial derivative. (We compute this for each x in the image.) What is the effect of such a transformation? One key idea is that such a derivative would be useful for marking positions where the intensity changes. Such a change is called an edge. It is important to detect edges in images because they often mark locations at which object properties change. These can include changes in illumination along a surface due to a shadow boundary, or a material (pigment) change, or a change in depth as when one object ends and another begins. The computational problem of finding intensity edges in images is called edge detection. We could look for positions at which DI(x) has a large negative or positive value. Large positive values indicate an edge that goes from low to high intensity, and large negative values indicate an edge that goes from high to low intensity. Example Suppose the image consists of a single (slightly sloped) edge:

1,829 citations

Journal ArticleDOI
TL;DR: This survey comprehensively explores the means/tariffs that the power utility takes to incentivize users to reschedule their energy usage patterns and outlines the potential challenges and future research directions in the context of demand response.
Abstract: The smart grid is widely considered to be the informationization of the power grid. As an essential characteristic of the smart grid, demand response can reschedule the users’ energy consumption to reduce the operating expense from expensive generators, and further to defer the capacity addition in the long run. This survey comprehensively explores four major aspects: 1) programs; 2) issues; 3) approaches; and 4) future extensions of demand response. Specifically, we first introduce the means/tariffs that the power utility takes to incentivize users to reschedule their energy usage patterns. Then we survey the existing mathematical models and problems in the previous and current literatures, followed by the state-of-the-art approaches and solutions to address these issues. Finally, based on the above overview, we also outline the potential challenges and future research directions in the context of demand response.

761 citations

Journal ArticleDOI
TL;DR: An overview of recent advances on security control and attack detection of industrial CPSs is presented, and robustness, security and resilience as well as stability are discussed to govern the capability of weakening various attacks.

663 citations

Journal ArticleDOI
TL;DR: A literature review on recent applications and design aspects of the intelligent reflecting surface (IRS) in the future wireless networks, and the joint optimization of the IRS’s phase control and the transceivers’ transmission control in different network design problems, e.g., rate maximization and power minimization problems.
Abstract: This paper presents a literature review on recent applications and design aspects of the intelligent reflecting surface (IRS) in the future wireless networks. Conventionally, the network optimization has been limited to transmission control at two endpoints, i.e., end users and network controller. The fading wireless channel is uncontrollable and becomes one of the main limiting factors for performance improvement. The IRS is composed of a large array of scattering elements, which can be individually configured to generate additional phase shifts to the signal reflections. Hence, it can actively control the signal propagation properties in favor of signal reception, and thus realize the notion of a smart radio environment. As such, the IRS’s phase control, combined with the conventional transmission control, can potentially bring performance gain compared to wireless networks without IRS. In this survey, we first introduce basic concepts of the IRS and the realizations of its reconfigurability. Then, we focus on applications of the IRS in wireless communications. We overview different performance metrics and analytical approaches to characterize the performance improvement of IRS-assisted wireless networks. To exploit the performance gain, we discuss the joint optimization of the IRS’s phase control and the transceivers’ transmission control in different network design problems, e.g., rate maximization and power minimization problems. Furthermore, we extend the discussion of IRS-assisted wireless networks to some emerging use cases. Finally, we highlight important practical challenges and future research directions for realizing IRS-assisted wireless networks in beyond 5G communications.

642 citations