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Reliable Task Offloading for Vehicular Fog Computing under Information Asymmetry and Information Uncertainty

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Reliable Task Offloading for Vehicular Fog Computing under I...

作者： Zhou, Zhenyu Liao, Haijun Zhao, Xiongwen Ai, Bo Guizani, Mohsen State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Electrical and Electronic Engineering North China Electric Power University Beijing China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China Department of Computer Science and Engineering Qatar University Doha Qatar

Vehicular fog computing has emerged as a cost-efficient solution for task processing in vehicular networks. However, how to realize effective server recruitment and reliable task offloading under information asymmetry and uncertainty remains a critical challenge. In this paper, we adopt a two-stage task offloading framework to address this challenge. First, we propose a convex-concave-procedure-based contract optimization algorithm for server recruitment, which aims to maximize the expected utility of the operator with asymmetric information. Then, a low-complexity and stable task offloading mechanism is proposed to minimize the total network delay based on the pricing-based matching. Furthermore, we extend the work to the scenario of information uncertainty and develop a matching-learning-based task offloading mechanism, which takes both occurrence awareness and conflict awareness into consideration. Simulation results demonstrate that the proposed algorithm can effectively motivate resource sharing and guarantee bounded deviation from the optimal performance without the global information. © 2019 IEEE.

关键词： Fog computing

Nonlinear Virtual Inertia control of WTGs for Enhancing Primary Frequency Response and Suppressing Drive-Train Torsional Oscillations

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arXiv 2020年

作者： Liu, Bi Huang, Qi Zhao, Junbo Milano, Federico Zhang, Yingchen Sichuan Provincial Key Lab of Power System Wide-area Measurement and Control University of Electronic Science and Technology of China Chengdu Sichuan611731 China Department of Electrical and Computer Engineering Mississippi State University StarkvilleMS39762 United States School of Electrical and Electronic Engineering University College Dublin Dublin Ireland National Renewable Energy Laboratory GoldenCO80401 United States

Virtual inertia controllers (VICs) for wind turbine generators (WTGs) have been recently developed to compensate the reduction of inertia in power systems. However, VICs can induce low frequency torsional oscillations of the drive train of WTGs. This paper addresses this issue and develops a new nonlinear VIC based on objective holographic feedbacks theory. This approach allows transforming the original nonlinear control into a completely controllable system of Brunovsky’s type. Simulation results under various scenarios demonstrate that the proposed method outperforms existing VICs in terms of suppression of low frequency drive-train torsional oscillations, enhancement of system frequency nadir as well as fast and smooth recovery of WTG rotor speed to the original MPP point before the disturbance. The proposed method is also able to coordinate multiple WTGs. Copyright © 2020, The Authors. All rights reserved.

关键词： Frequency response

Max-min energy balance in wireless-powered hierarchical fog-cloud computing networks

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Max-min energy balance in wireless-powered hierarchical fog-...

作者： Liu, Jingxian Xiong, Ke Ng, Derrick Wing Kwan Fan, Pingyi Zhong, Zhangdui Letaief, Khaled Ben School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China Beijing Key Laboratory of Traffic Data Analysis and Mining Beijing Jiaotong University Beijing100044 China School of Electrical Engineering and Telecommunications UNSW Sydney SydneyNSW2052 Australia Department of Electronic Engineering Tsinghua University Beijing100084 China Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Beijing Engineering Research Center of High-Speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing100044 China Hong Kong Peng Cheng Laboratory Shenzhen518055 China

This paper investigates the wireless-powered hierarchical fog-cloud computing networks, where multiple energy-constrained users harvest energy from a hybrid access point (HAP) firstly and then use their harvested energy to offload their computation tasks to fog/cloud servers via the HAP or compute their tasks locally. To pursue multi-user fairness, an optimization problem is formulated to maximize the minimal energy balance among all users by jointly optimizing time assignments, computation central processing unit (CPU) frequencies, and the computing mode selection. Since the problem is mixed-integer combinatorial non-convex, which is intractable, a generalized Benders decomposition (GBD)-based method is proposed, which guarantees the globally optimal solution. To release the high computational complexity of the proposed GBD-based method, a penalized successive convex approximation (P-SCA)-based algorithm is designed as an alternative to obtain a suboptimal solution with low computational complexity. Numerical results show that among different optimizable factors in the system, computing mode selection is the dominant one on affecting the system performance. Moreover, for each user, local computing is a better choice, if it is with relatively poor channel gain and small local computing delay. Otherwise, fog/cloud computing may be a better choice. Additionally, for the users with relatively high channel gains, if their local computing delays are less than those selecting fog computing, cloud computing should be a better choice. © 2002-2012 IEEE.

关键词： Energy transfer

Effect of long-term fluorination on surface electrical performance of ethylene propylene rubber

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High Voltage 2019年第4期4卷 339-344页

作者： Rujia Men Zhipeng Lei Tao Han Davide Fabiani Chuanyang Li Simone Vincenzo Suraci Jian Wang Shanxi Key Laboratory of Mining Electrical Equipment and Intelligent Control College of Electrical and Power EngineeringTaiyuan University of TechnologyTaiyuan 030024People's Republic of China Department of Electrical Electronicand Information Engineering‘Guglielmo Marconi’University of BolognaViale Risorgimento 2Bologna 40136Italy Key Laboratory of Smart Grid of Education Ministry School of Electrical and Information Engineering Tianjin UniversityTianjin 300072People's Republic of China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power UniversityChangping DistrictBeijing 102206People's Republic of China

To investigate the effect of fluorination on surface electrical performance of ethylene propylene rubber(EPR),four pieces of EPR specimens are prepared and fluorinated for different duration ranging from 120 min to 480 *** surface morphology and element compositions of experimental specimens are *** surface potential decay and complex permittivity are *** tracking discharge property and the erosion properties after tracking test are *** surface charge transport and electrical property tailoring mechanism are *** results show that when the fluorination duration is from 120 min to 360 min,the surface morphology gradually becomes flat and compact with time,and the surface resistance to electrical tracking is *** an excessive fluorination with the duration of 480 min leads to a significant increase in surface conductivity and a weakening in the resistance to electrical tracking,which is mainly due to a change in surface *** recommended fluorination duration for an optimised surface property is between 240 and 360 min for EPR specimen.

关键词： electrical propylene rubber

Improving sum-rate of cell-free massive MIMO with expanded compute-and-forward

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arXiv 2021年

作者： Zhang, Jiayi Zhang, Jing Ng, Derrick Wing Kwan Jin, Shi Ai, Bo The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-Speed Railway System Beijing Jiaotong University Beijing100044 China The School of Electrical Engineering and Telecommunications University of New South Wales NSW2052 Australia The National Mobile Communications Research Laboratory Southeast University Nanjing210096 China The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen China

Cell-free massive multiple-input multiple-output (MIMO) employs a large number of distributed access points (APs) to serve a small number of user equipments (UEs) via the same time/frequency resource. Due to the strong macro diversity gain, cell-free massive MIMO can considerably improve the achievable sum-rate compared to conventional cellular massive MIMO. However, the performance of cell-free massive MIMO is upper limited by inter-user interference (IUI) when employing simple maximum ratio combining (MRC) at receivers. To harness IUI, the expanded compute-and-forward (ECF) framework is adopted. In particular, we propose power control algorithms for the parallel computation and successive computation in the ECF framework, respectively, to exploit the performance gain and then improve the system performance. Furthermore, we propose an AP selection scheme and the application of different decoding orders for the successive computation. Finally, numerical results demonstrate that ECF frameworks outperform the conventional CF and MRC frameworks in terms of achievable sum-rate. Copyright © 2021, The Authors. All rights reserved.

关键词： Power control

Performance of different threshold estimation methods on SEMG wavelet de-noising in prolonged fatigue identification

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Performance of different threshold estimation methods on SEM...

2018 IEEE EMBS Conference on Biomedical engineering and Sciences, IECBES 2018

作者： Jamaluddin, Fauzani N Ahmad, Siti A Mohd Noor, Samsul Bahari Hassan, Wan Zuha Wan Shair, E.F. Malaysia Control System and Signal Processing Group Australia Department of Electrical and Electronic Engineering Faculty of Engineering Universiti Putra Malaysia Serdang Malaysia

ISBN: (纸本)9781538624715

Surface electromyography (SEMG) signals are widely used in fatigue identification. Fatigue after high intensity exercise and sports training needs to be balanced with rest to allow biochemical reactions during sports activity to return to a normal level. Inadequate rest leads to prolonged fatigue (PF) conditions such as musculoskeletal disorder, unexplained lethargy and performance decrement. Continuous sports training under these conditions may lead to injury. Fatigue identification at this stage is crucial since changes in amplitude and frequency of SEMG may determine whether the player is under normal fatigue (NF) or PF condition. During data collection, there are many interferences and noises which can reduce signal to noise ratio (SNR) of SEMG and affect PF detection. This paper pre-processed SEMG signals using Stationary Wavelet Transform (SWT) ‘db’ 45 with different threshold (Th) estimation techniques of de-noising such as RigRSURE, HeurSURE, minimax, universal threshold and a new estimation of threshold method which is based on a baseline of SEMG decomposition details. Naïve Bayes classification results using time and frequency features indicate that the new estimation of threshold method have the highest accuracy (98%), compared to RigRSURE (85%), HuerSURE (68%), Universal Threshold (74%) and minimax (76%). © 2018 IEEE

关键词： Signal to noise ratio

Determination of weak squeezed vacuum state through photon statistics measurement

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arXiv 2021年

作者： Zuo, Guanhua Zhang, Yuchi Li, Jing Zhu, Shiyao Guo, Yanqiang Zhang, Tiancai State Key Laboratory of Quantum Qptics and Quantum Optics Devices Collaborative Innovation Center of Extreme Optics Institute of Opto-Electronics Shanxi University Taiyuan030006 China College of Physics and Electronic Engineering Shanxi University Taiyuan030006 China Department of Physics Zhejiang University Hangzhou310027 China Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province College of Physics and Optoelectronics Taiyuan University of Technology Taiyuan030600 China

Weak squeezed vacuum light, especially resonant to the atomic transition, plays an important role in quantum storage and generation of various quantum sources. However, the general homodyne detection (HD) cannot determine weak squeezing due to the low signal to noise ratio and the limited resolution of the HD system. Here we provide an alternative method based on photon statistics measurement to determine the weak squeezing of the squeezed vacuum light generated from an optical parametric oscillator working far below the threshold. The approach is established the relationship between the squeezing parameter and the second-order degree of coherence. The theoretical analysis agrees well with the experiment results. The advantage of this method is that it provides a feasible and reliable experimental measure to determine the weak squeezing with high precision and the measurement is independent on the detection efficiency. This method can be used to measure other quantum features for various quantum states with extremely weak non-classicality. Copyright © 2021, The Authors. All rights reserved.

关键词： Optical parametric oscillators

Energy Efficient Predictive control for Vapor Compression Refrigeration Cycle systems

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IEEE/CAA Journal of Automatica Sinica 2018年第5期5卷 953-960页

作者： Xiaohong Yin Shaoyuan Li the School of Automation and Electronic Engineering Qingdao University of Science and TechnologyQingdao 266042China the Department of Automation Shanghai Jiao Tong Universityand the Key Laboratory of System Control and Information ProcessingMinistry of Education of ChinaShanghai 200240China

Abstract--Vapor compression refrigeration cycle （VCC） system is a high dimensional coupling thermodynamic system for which the controller design is a great challenge. In this paper, a model predictive control based energy efficient control strategy which aims at maximizing the system efficiency is proposed. Firstly, according to the mass and energy conservation law, an analysis on the nonlinear relationship between superheat and cooling load is carried out, which can produce the maximal effect on the system performance. Then a model predictive control （MPC） based controller is developed for tracking the calculated setting curve of superheat degree and pressure difference based on model identified from data which can be obtained from an experimental rig. The proposed control strategy maximizes the coefficient of performance （COP） which depends on operating conditions, in the meantime, it meets the changing demands of cooling capacity. The effectiveness of the control performance is validated on the experimental rig. Index Terms--Cooling load, model predictive control （MPC）, superheat, vapor compression refrigeration cycle （VCC）.

关键词： Cooling load model predictive control(MPC) superheat vapor compression refrigeration cycle(VCC)

Model-driven beamforming neural networks

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arXiv 2020年

作者： Xia, Wenchao Zheng, Gan Wong, Kai-Kit Zhu, Hongbo Jiangsu Key Laboratory of Wireless Communications Engineering Research Center of Health Service System Based on Ubiquitous Wireless Networks Ministry of Education Nanjing University of Posts and Telecommunications Nanjing210003 China Wolfson School of Mechanical Electrical and Manufacturing Engineering Loughborough University LeicestershireLE11 3TU United Kingdom Department of Electronic and Electrical Engineering University College London LondonWC1E 7JE United Kingdom

Beamforming is evidently a core technology in recent generations of mobile communication networks. Nevertheless, an iterative process is typically required to optimize the parameters, making it ill-placed for real-time implementation due to high complexity and computational delay. Heuristic solutions such as zero-forcing (ZF) are simpler but at the expense of performance loss. Alternatively, deep learning (DL) is well understood to be a generalizing technique that can deliver promising results for a wide range of applications at much lower complexity if it is sufficiently trained. As a consequence, DL may present itself as an attractive solution to beamforming. To exploit DL, this article introduces general data- and model-driven beamforming neural networks (BNNs), presents various possible learning strategies, and also discusses complexity reduction for the DL-based BNNs. We also offer enhancement methods such as training-set augmentation and transfer learning in order to improve the generality of BNNs, accompanied by computer simulation results and testbed results showing the performance of such BNN solutions. Copyright © 2020, The Authors. All rights reserved.

关键词： Beamforming