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The Caching and Pricing Strategy for Information-Centric Networking with Advertisers’Participation

China Communications 2024年第3期21卷 283-295页

作者： Zheng Quan Yan Wenliang Wu Rong Tan Xiaobin Yang Jian Yuan Liu Xu Zhenghuan Laboratory for Future Networks Department of AutomationUniversity of Science and Technology of ChinaHefei 230026China Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefei 230088China Institute of Advanced Technology University of Science and Technology of ChinaHefei 230088China Suzhou Nuclear Power Research Institute Suzhou 215004China National Engineering Laboratory for Public Safety Risk Perception and Control by Big Data(NEL-PSRPC) China Academy of Electronics and Information Technology of CETCBeijing 100041China

As users’access to the network has evolved into the acquisition of mass contents instead of IP addresses,the IP network architecture based on end-to-end communication cannot meet users’***,the Information-Centric Networking(ICN)came into *** a technical point of view,ICN is a promising future network *** and customizing a reasonable pricing mechanism plays a positive role in promoting the deployment of *** current research on ICN pricing mechanism is focused on paid ***,we study an ICN pricing model for free content,which uses game theory based on Nash equilibrium to *** this work,advertisers are considered,and an advertiser model is established to describe the economic interaction between advertisers and ICN *** solution can formulate the best pricing strategy for all ICN entities and maximize the benefits of each *** extensive analysis and numerical results show that the proposed pricing framework is significantly better than existing solutions when it comes to free content.

关键词： advertisers cache free content Information-Centric Networking pricing strategy

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Fault Tolerant Property of Interdependent Networks 12

Fault Tolerant Property of Interdependent Networks

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12th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, QR2MSE 2022

作者： Li, Xifeng Bi, Dongjie Peng, Libiao Tang, Yu Xie, Yongle Xu, Juan School of Automation Engineering University of Electronic Science and Technology of China Chengdu China Faculty of Artificial Intelligence and Big Data Yibin University Yibin China

ISBN: (纸本)9781839538360

Recent years have witnessed a surge of extensive study upon the robustness of a system consisting of interdependent networks. Both the mechanism of cascading failures and the corresponding recovery strategies, which means to heal malfunction of a system before it runs completely into collapse, are two key issues in the field of robustness analysis of interdependent networks. An essential question that has always been ignored is how to design a fault tolerance scheme to buffer against cascading failures. In order to deeply understand the relationship between the fault-tolerance assignment and the robustness of interdependent networks, we propose a cascading failure model with the consideration of the fault tolerance property of the nodes in interdependent networks, where the node are specified different fault tolerant capacity according to their degree values. By theoretical and numerical studies, it is found that the robustness of a system can be improved significantly if the high-degree nodes are assigned high fault tolerant capacity. However, robustness of a system can be hampered if the high degree nodes are assigned low fault tolerant capacity. Our results prove that the fault tolerance assignment scheme of the nodes has great impacts on the robustness of interdependent networks and provide important thoughts to reinforce reliability of the interdependent systems by the proper allocation of fault tolerant capacity. © 2022 IEEE.

关键词： Fault tolerance

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Observer-Based Control for a New Stochastic Maximum Power Point Tracking for Photovoltaic Systems With Networked Control System

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IEEE Transactions on Fuzzy Systems 2023年第6期31卷 1870-1884页

作者： Aslam, Muhammad Shamrooz Tiwari, Prayag Pandey, Hari Mohan Band, Shahab S. Guangxi University of Science and Technology School of Automation Liuzhou545006 China Halmstad University School of Information Technology Halmstad301 18 Sweden Bournemouth University Data Science and Artificial Intelligence Department of Information and Computing PooleBH12 United Kingdom National Yunlin University of Science and Technology Future Technology Research Center College of Future Douliou64002 Taiwan

This study discusses the new stochastic maximum power point tracking control approach toward the photovoltaic cells (PCs). A PC generator is isolated from the grid, resulting in a direct current microgrid that can provide changing loads. In the course of the nonlinear systems through the time-varying delays, we proposed networked control systems beneath an event-triggered approach basically in the fuzzy system. In this scenario, we look at how random, variable loads impact the PC generator's stability and efficiency. The basic premise of this article is to load changes and the value matching to a Markov chain. PC generators are complicated nonlinear systems that pose a modeling problem. Transforming this nonlinear PC generator model into the Takagi-Sugeno (T - S) fuzzy model is another option. The T - S fuzzy model is presented in a unified framework, for which 1) the fuzzy observer based on this premise variables can be used for approximately in the infinite states to the present system, 2) the fuzzy observer-based controller can be created using the same premises being the observer, and 3) to reduce the impact of transmission burden, an event-triggered method can be investigated. Simulation in the PC generator model for the real-time climate data obtained in China demonstrates the importance of our method. In addition, by using a new Lyapunov-Krasovskii functional for combining with the allowed weighting matrices incorporating mode-dependent integral terms, the developed model can be stochastically stable and achieves the required performances. Based on the tensor-product (T-P) transformation, a new depiction of the nonlinear system is derived in two separate steps in which an adequate controller input is guaranteed in the first step and an adequate vertex polytope is ensured in the second step. To present the potential of our proposed method, we simulate it for PC generators. © 1993-2012 IEEE.

关键词： Linear matrix inequalities

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Optimal Prescribed-Time Control based Reactive Planning System for Quadruped Robot Navigation

Optimal Prescribed-Time Control based Reactive Planning Syst...

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IEEE International Conference on Robotics and automation (ICRA)

作者： Shaohang Xu Wentao Zhang Chin Pang Ho Lijun Zhu School of Artificial Intelligence and Automation Huazhong University of Science and Technology China School of Data Science City University of Hong Kong HKSAR

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In this paper, we propose a reactive planning system for quadruped robots based on prescribed-time control. The navigation of the quadruped robot is fundamentally depicted as omnidirectional movements, while a feedback control law is formulated to address any deviations the robot may encounter. In particular, our proposed feedback control system is theoretically proven to achieve convergence within a predefined finite time that is specified by the user. To further compute the optimal convergent time and the local goal state, we present a high-level planning node encompassing terrain-aware kinodynamic search and spatiotemporal trajectory optimization, which can generate collision-free, smooth, and efficient trajectories. The effectiveness of our proposed framework is validated through both numerical simulation and real-robot experiments in indoor and outdoor environments, including scenarios with cluttered obstacles, slopes, and external disturbances.

关键词： Navigation Numerical simulation Control systems Planning Feedback control Spatiotemporal phenomena Quadrupedal robots

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Observer-based Distributed MPC for Collaborative Quadrotor-Quadruped Manipulation of a Cable-Towed Load

Observer-based Distributed MPC for Collaborative Quadrotor-Q...

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IEEE International Conference on Robotics and automation (ICRA)

作者： Shaohang Xu Yian Wang Wentao Zhang Chin Pang Ho Lijun Zhu School of Artificial Intelligence and Automation Huazhong University of Science and Technology China School of Data Science City University of Hong Kong HKSAR

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

This paper presents a collaborative quadrotor-quadruped robot system for the manipulation of a cable-towed payload. In particular, we aim to solve the challenge from the unknown dynamics of the cable-towed payload. To this end, we first propose novel dynamic models for both the quadrotor and the quadruped robot, taking into account the nonlinear robot dynamics and the uncertainties associated with the cable-towed load. Moreover, we design observers for the hybrid interaction between the robots and the payload. Theoretically, the convergence of these observers is analyzed using Lyapunov functions under mild technical assumptions. Finally, we seamlessly integrate the dynamics models and the observers into a distributed Model Predictive Control (MPC) framework with kinematics limitations and collision avoidance constraints. The proposed system is validated through challenging field experiments in indoor and outdoor environments, involving push disturbances, varying and unknown payloads, uneven terrains, etc.

关键词： Uncertainty Collaboration Observers Nonlinear dynamical systems Trajectory Quadrupedal robots Collision avoidance

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Distributionally Robust Chance Constrained Trajectory Optimization for Mobile Robots within Uncertain Safe Corridor

Distributionally Robust Chance Constrained Trajectory Optimi...

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IEEE International Conference on Robotics and automation (ICRA)

作者： Shaohang Xu Haolin Ruan Wentao Zhang Yian Wang Lijun Zhu Chin Pang Ho School of Artificial Intelligence and Automation Huazhong University of Science and Technology China School of Data Science City University of Hong Kong HKSAR

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Safe corridor-based Trajectory Optimization (TO) presents an appealing approach for collision-free path planning of autonomous robots, because its convex formulation can guarantee global optimality. The safe corridor is constructed based on the obstacle map, however, the non-ideal perception induces uncertainty, which is rarely considered in the context of trajectory generation. In this paper, we propose Distributionally Robust Safe Corridor Constraints (DRSCCs) to consider the uncertainty of the safe corridor. Then, we integrate DRSCCs into the trajectory optimization framework using Bernstein basis polynomials. Theoretically, we rigorously prove that the proposed trajectory optimization problem is equivalent to a convex quadratic program, which is computationally efficient to deploy onto real robots. The simulation results show that our method enhances navigation safety by significantly reducing the infeasible motions compared to the baseline. Moreover, the proposed approach is validated through two robotic applications, a micro Unmanned Aerial Vehicle (UAV) and a quadruped robot Unitree A1.

关键词： Uncertainty Navigation Simulation Autonomous aerial vehicles Numerical simulation Polynomials Safety

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Agile and Safe Trajectory Planning for Quadruped Navigation with Motion Anisotropy Awareness

Agile and Safe Trajectory Planning for Quadruped Navigation ...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Wentao Zhang Shaohang Xu Peiyuan Cai Lijun Zhu School of Artificial Intelligence and Automation Huazhong University of Science and Technology China School of Data Science City University of Hong Kong HKSAR

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Quadruped robots demonstrate robust and agile movements in various terrains; however, their navigation autonomy is still insufficient. One of the challenges is that the motion capabilities of the quadruped robot are anisotropic along different directions, which significantly affects the safety of quadruped robot navigation. This paper proposes a navigation framework that takes into account the motion anisotropy of quadruped robots including kinodynamic trajectory generation, nonlinear trajectory optimization, and nonlinear model predictive control. In simulation and real robot tests, we demonstrate that our motion-anisotropy-aware navigation framework could: (1) generate more efficient trajectories and realize more agile quadruped navigation; (2) significantly improve the navigation safety in challenging scenarios. The implementation is realized as an open-source package at https://***/ZWT006/agile_navigation.

关键词： Anisotropic magnetoresistance Three-dimensional displays Navigation Trajectory planning Robot kinematics Planning Safety Quadrupedal robots Robots Trajectory optimization

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KLILO: Kalman Filter based LiDAR-Inertial-Leg Odometry for Legged Robots

KLILO: Kalman Filter based LiDAR-Inertial-Leg Odometry for L...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Shaohang Xu Wentao Zhang Lijun Zhu School of Artificial Intelligence and Automation Huazhong University of Science and Technology China School of Data Science City University of Hong Kong HKSAR

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

This paper presents a Kalman filter based LiDAR-Inertial-Leg Odometry (KLILO) system for legged robots to navigate in challenging environments. In particular, we employ the iterated error-state extended Kalman filter framework on manifolds to fuse measurements from the inertial measurement unit (IMU), LiDAR, joint encoders, and contact force sensors in a tightly coupled manner. To assess the performance of KLILO, we build a dataset that encompasses intricate environments with challenging conditions such as dynamic objects and deformable terrains. The results demonstrate that our algorithm can provide efficient and reliable localization in all tests. It exhibits an average improvement of around 40% in positioning accuracy compared to the baselines. Furthermore, we validate KLILO in a challenging navigation task on a real robot, where the LiDAR encounters ineffective measurements.

关键词： Legged locomotion Laser radar Atmospheric measurements Fuses Measurement uncertainty Kinematics Robot sensing systems Particle measurements Kalman filters Odometry

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Causal Discovery via Conditional Independence Testing with Proxy Variables 41

Causal Discovery via Conditional Independence Testing with P...

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41st International Conference on Machine Learning, ICML 2024

作者： Liu, Mingzhou Sun, Xinwei Qiao, Yu Wang, Yizhou School of Computer Science Peking University China Peking University China Sch. of Data Science Fudan University China Dep. of Automation Shanghai Jiao Tong University China Inst. for Artificial Intelligence Peking University China Nat'l Eng. Research Center of Visual Technology Peking University China Nat'l Key Lab of General Artificial Intelligence Peking University China

Distinguishing causal connections from correlations is important in many scenarios. However, the presence of unobserved variables, such as the latent confounder, can introduce bias in conditional independence testing commonly employed in constraint-based causal discovery for identifying causal relations. To address this issue, existing methods introduced proxy variables to adjust for the bias caused by unobserveness. However, these methods were either limited to categorical variables or relied on strong parametric assumptions for identification. In this paper, we propose a novel hypothesis-testing procedure that can effectively examine the existence of the causal relationship over continuous variables, without any parametric constraint. Our procedure is based on discretization, which under completeness conditions, is able to asymptotically establish a linear equation whose coefficient vector is identifiable under the causal null hypothesis. Based on this, we introduce our test statistic and demonstrate its asymptotic level and power. We validate the effectiveness of our procedure using both synthetic and real-world data. Code is publicly available at https://***/lmz123321/proxy_causal_discovery. Copyright 2024 by the author(s)

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MPFFNet:Semantic Segmentation of Remote Sensing Image Buildings Based on Multipath Feature Fusion 8

MPFFNet:Semantic Segmentation of Remote Sensing Image Buildi...

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8th International Conference on Communication, Image and Signal Processing, CCISP 2023

作者： Dong, Jie Mao, Jingkun Liu, Kun Cheng, Liangyong School of Electrical Engineering and Automation Tianjin University of Technology Tianjin China School of Artificial Intelligence and Data Science Hebei University of Technology Tianjin China Interplanetary Space Technology Development Co. LTD Tianjin China

ISBN: (纸本)9798350305838

The buildings with variable scales and complex background information in remote sensing images often result in missed and misclassified segmentation of buildings. To address this issue, this paper designs an multipath feature fusion network (MPFFNet). MPFFNet has an overall encoding and decoding structure, embedded with an residual depth Inception block(RDI) module to extract multi-scale features. At the same time, MPFFNet uses the multipath residual channel attention (MPRCA) module to expand the Receptive field of the feature map to obtain rich multi-scale context information. The validity of the proposed algorithm is proved on the WHU Buildings data set, with F1 reaching 94.70%, IOU reaching 89.93%, and Recall reaching 94.98%. © 2023 IEEE.

关键词： Buildings

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