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arXiv 2025年

作者： Pan, Wenxuan Yang, Yang Chen, Mingzhe Wei, Dong Guo, Caili Mao, Shiwen Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Department of Electrical and Computer Engineering the Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Wireless Engineering Research and Education Center Auburn University AuburnAL36849 United States

Floor plans can provide valuable prior information that helps enhance the accuracy of indoor positioning systems. However, existing research typically faces challenges in efficiently leveraging floor plan information and applying it to complex indoor layouts. To fully exploit information from floor plans for positioning, we propose a floor plan-assisted fusion positioning algorithm (FP-BP) using Bluetooth low energy (BLE) and pedestrian dead reckoning (PDR). In the considered system, a user holding a smartphone walks through a positioning area with BLE beacons installed on the ceiling, and can locate himself in real time. In particular, FP-BP consists of two phases. In the offline phase, FP-BP programmatically extracts map features from a stylized floor plan based on their binary masks, and constructs a mapping function to identify the corresponding map feature of any given position on the map. In the online phase, FP-BP continuously computes BLE positions and PDR results from BLE signals and smartphone sensors, where a novel grid-based maximum likelihood estimation (GML) algorithm is introduced to enhance BLE positioning. Then, a particle filter is used to fuse them and obtain an initial estimate. Finally, FP-BP performs post-position correction to obtain the final position based on its specific map feature. Experimental results show that FP-BP can achieve a real-time mean positioning accuracy of 1.19 m, representing an improvement of over 28% compared to existing floor plan-fused baseline algorithms. Copyright © 2025, The Authors. All rights reserved.

关键词： Photomapping

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Federated learning for task and resource allocation in wireless high altitude balloon networks

arXiv

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arXiv 2020年

作者： Wang, Sihua Chen, Mingzhe Yin, Changchuan Saad, Walid Hong, Choong Seon Cui, Shuguang Vincent Poor, H. Beijing Laboratory of Advanced Information Network Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing100876 China Department of Electrical Engineering Princeton University PrincetonNJ08544 United States Wireless@VT Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24060 United States Department of Computer Science and Engineering Kyung Hee University Korea Republic of Chinese University of Hong Kong Shenzhen518172 China Department of Electrical Engineering Princeton University PrincetonNJ08544 United States

In this paper, the problem of minimizing energy and time consumption for task computation and transmission is studied in a mobile edge computing (MEC)-enabled balloon network. In the considered network, each user needs to process a computational task in each time instant, where high-altitude balloons (HABs), acting as flying wireless base stations, can use their powerful computational abilities to process the tasks offloaded from their associated users. Since the data size of each user's computational task varies over time, the HABs must dynamically adjust the user association, service sequence, and task partition scheme to meet the users' needs. This problem is posed as an optimization problem whose goal is to minimize the energy and time consumption for task computing and transmission by adjusting the user association, service sequence, and task allocation scheme. To solve this problem, a support vector machine (SVM)-based federated learning (FL) algorithm is proposed to determine the user association proactively. The proposed SVM-based FL method enables each HAB to cooperatively build an SVM model that can determine all user associations without any transmissions of either user historical associations or computational tasks to other HABs. Given the prediction of the optimal user association, the service sequence and task allocation of each user can be optimized so as to minimize the weighted sum of the energy and time consumption. Simulations with real data of city cellular traffic from the OMNILab at Shanghai Jiao Tong University show that the proposed algorithm can reduce the weighted sum of the energy and time consumption of all users by up to 16.1% compared to a conventional centralized method. Copyright © 2020, The Authors. All rights reserved.

关键词： Support vector machines

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Analysis of Memory Capacity for Deep Echo State Networks

arXiv

引用

arXiv 2019年

作者： Liu, Xuanlin Chen, Mingzhe Yin, Changchuan Saad, Walid Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China Wireless@VT Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA United States

—In this paper, the echo state network (ESN) memory capacity, which represents the amount of input data an ESN can store, is analyzed for a new type of deep ESNs. In particular, two deep ESN architectures are studied. First, a parallel deep ESN is proposed in which multiple reservoirs are connected in parallel allowing them to average outputs of multiple ESNs, thus decreasing the prediction error. Then, a series architecture ESN is proposed in which ESN reservoirs are placed in cascade that the output of each ESN is the input of the next ESN in the series. This series ESN architecture can capture more features between the input sequence and the output sequence thus improving the overall prediction accuracy. Fundamental analysis shows that the memory capacity of parallel ESNs is equivalent to that of a traditional shallow ESN, while the memory capacity of series ESNs is smaller than that of a traditional shallow ESN. In terms of normalized root mean square error, simulation results show that the parallel deep ESN achieves 38.5% reduction compared to the traditional shallow ESN while the series deep ESN achieves 16.8% reduction. Copyright © 2019, The Authors. All rights reserved.

关键词： Network architecture

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Optimization Model for Designing Multiple Virtualized Campus Area Networks Coordinating with Wide Area Networks

Optimization Model for Designing Multiple Virtualized Campus...

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作者： Kurimoto, Takashi Urushidani, Shigeo Oki, Eiji Information System Architecture Science Research Division National Institute of Informatics Tokyo101-8430 Japan Department of Communication and Computer Engineering Graduate School of Informatics Kyoto University Kyoto606-8501 Japan

We propose an optimization model for designing multiple network functions virtualization (NFV)-based campus area networks (CANs). Organizations, such as universities and research institutions have their own campus information and communication technology equipment, but many would like to move this equipment to NFV and cloud data centers for improving reliability and resiliency. However, NFV-based CAN is not affordable for them, because costs are higher with a cloud. One solution is for multiple organizations to procure NFV and cloud data center resources together. By doing so, their individual costs of using these resources will be reduced. To make progress on this approach, there are planning issues to resolve when choosing optimal NFV and cloud data center locations. The proposed model minimizes the total network costs incurred by the organizations, including the wide area network cost and data synchronization costs for recovery from faults at data centers and the various subcampus network configurations of legacy CANs. The model is formulated and analyzed by using mixed integer linear programming. The effect of cost minimization is evaluated in a ladder network and an actual network, SINET5, and it is found that the costs can be reduced by up to 63%. The calculation times of this model under practical conditions are short and the model will be useful in practice. It is also shown that the cost of fault recovery can be suppressed. These results will encourage organizations to deploy NFV-based CANs. © 2004-2012 IEEE.

关键词： Network function virtualization

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Usability Evaluation for User Interface Design of Student Support system: Mixed Method Study

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IOP Conference Series: Materials Science and Engineering 2020年第1期803卷

作者： Ahmed AL-sa'di Rasmus Rasmus Bugge Skammelsen Qiang Ji Yufeng Xiang Bhogadi Aakarsh Sathishkumar Kuppusamy Department of Information system UUNZ Institute of Business Auckland New Zealand Department of Architecture Design and Media Technology Aalborg University Aalborg Denmark Department of Computer Science Auckland University of Technology Auckland New Zealand

The efficiency of a website depends on how usable the UI user interface, (UI) is and how well it is structured. The aim of this research was to try and understand the issues with the Arion system. Arion is the student information system used by Auckland University of Technology. We conducted three experimental studies to examine the usability and to improve the user experience of student who use Arion. Three main methods were used namely; survey, open card sorting and situated co-inquiry. The survey was used to inform the study and collect more information about users. The open card sorting used to redesign the navigation menu for the system. Then the Situated co-inquiry used to discover the user's current unexpected or unforeseen ideas, which may be helpful for future research.

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The architecture of onboard intellectual control system for autonomous researching devices 3

The architecture of onboard intellectual control system for ...

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3rd Russian-Pacific Conference on computer Technology and Applications, RPC 2018

作者： Kabak Il'Ya, S. Sheptunov Sergey, A. Solomentsev Jury, M. Sukhanova Nataly, V. Sannikov Aleksandr, S. Nakhushev Rakhim, S. MSTU 'Stankin' Computer Control Architecture Sub-Department Moscow Russia Institute for Design and Technological Informatics of RAS Moscow Russia MSTU 'Stankin' Information Technogy and Computer System SUB-Departament Moscow Russia Institute for Design Technological Informatics of Russian Moscow Russia

ISBN: (纸本)9781538675311

The goal of science is the new knowledge mining and data processing. There are some fields of activity in which there is impossible for man to be presented (for example, in space and world ocean). The autonomous researching devices are needed for knowledge acquisition in these fields of activity. The architecture of the on-board control system for the autonomous device was designed. The control system was designed with realization on the module principles, used algorithm and intelligent modules. © 2018 IEEE.

关键词： Control systems

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Validation of the Proposed Fault Injection, Test and Hardness Analysis for Combinational Data-Flow Verilog HDL Designs Under the RASP-FIT Tool

Validation of the Proposed Fault Injection, Test and Hardnes...

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IEEE International Symposium on Dependable, Autonomic and Secure Computing (DASC)

作者： Abdul Rafay Khatri Ali Hayek Josef Börscök Department of Computer Architecture and System Programming University of Kassel Kassel Germany Universitat Kassel Kassel Hessen DE

Owing to the condensed size of components in digital designs on the FPGA, it is difficult to guarantee an acceptable degree of reliability due to soft-errors. These designs are mostly available in Hardware Description Languages (HDL) at various abstraction levels, e.g. gate-level, data-flow, and behavioural. Fault Injection (FI) is a well-known technique to assess the dependability of such designs. Broadly, FI techniques for FPGA-based designs are categorized into emulation and simulation-based techniques. Simulation-Based FI (SBFI) tools work on hardware models of designs and help designers to test and verify designs at an early phase of the FPGA design & development flow. Testing, dependability analysis, and fault simulation applications require a faulty model of the original design during fault injection campaign. Therefore, we require a tool which can automatically generate the faulty model of the original design written at any abstraction levels and perform fault injection testing and dependability analysis. In this paper, a fault injection tool (RASP-FIT) is presented, which consists of an automatic code modifier (fault injection algorithm), fault injection control unit and result analyser. Previously, the tool is used for code-modification, test and hardness analysis for gate-level designs. In this paper, an enhancement of a code modifier along with result analyser techniques are applied to the data-flow benchmark designs and presented.

关键词： Circuit faults Tools Hardware design languages Logic gates Benchmark testing Prototypes

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A Management Model for Low Powered Wireless Personal Area Networks

A Management Model for Low Powered Wireless Personal Area Ne...

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IEEE International Symposium on World of Wireless Mobile and Multimedia Networks (WoWMoM)

作者： Yekta Türk Ali Akman Turk Telekom Mobile Access System Architecture Department Istanbul Turkey Computer Engineering Department Maltepe University Istanbul Turkey

ISBN: (纸本)9781538647264

Most of the researchers are investigating Internet of Things (IoT) to obtain information about our environment to control and act on it with the analysis of collected big data. An important topic with IoT is to manage the vast number of devices. In this demo, we demonstrate a management model in order to detect faults, analyze network and improve performance and connectivity in low powered mesh networks. The model can take actions when necessary and visualize those actions and the state of different managed objects. For building the proposed model, we have modified a well-known network management protocol to use for management data access and have performed fault and performance analysis in terms of values of counters collected from the interfaces. Our demonstrations indicate that the usage of the proposed method can perform well in limited bandwidth networks. At the same time, some security and device firmware related features are also added to the management system.

关键词： Protocols Performance evaluation Data visualization Bandwidth Databases Data models Security

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Federated Deep Learning for Immersive Virtual Reality over Wireless Networks

Federated Deep Learning for Immersive Virtual Reality over W...

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IEEE Global Communications Conference

作者： Mingzhe Chen Omid Semiari Walid Saad Xuanlin Liu Changchuan Yin Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China Department of Electrical Engineering Princeton University Princeton NJ USA The Future Network of Intelligence Institute The Chinese University of Hong Kong Shenzhen China Department of Electrical and Computer Engineering University of Colorado Colorado Springs CO USA Bradley Department of Electrical and Computer Engineering Wireless@VT Virginia Tech Blacksburg VA USA

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

In this paper, the problem of enhancing the virtual reality (VR) experience for wireless users is investigated by minimizing the occurrence of breaks in presence (BIPs) that can detach the users from their virtual world. To measure the BIPs for wireless VR users, a novel model that jointly considers the VR applications, transmission delay, VR video quality, and users' awareness of the virtual environment is proposed. In the developed model, the base stations (BSs) transmit VR videos to the wireless VR users using directional transmission links so as to increase the data rate of VR users, thus, reducing the number of BIPs for each user. Therefore, the mobility and orientation of VR users must be considered when minimizing BIPs, since the body movements of a VR user may result in blockage of its wireless link. The BIP problem is formulated as an optimization problem which jointly considers the predictions of users' mobility patterns, orientations, and their BS association. To predict the orientation and mobility patterns of VR users, a distributed learning algorithm based on the machine learning framework of deep echo state networks (ESNs) is proposed. The proposed algorithm uses concept from federated learning to enable multiple BSs to locally train their deep ESNs using their collected data and cooperatively build a learning model to predict the entire users' mobility patterns and orientations. Using these predictions, the user association policy that minimizes BIPs is derived. Simulation results demonstrate that the developed algorithm reduces the users' BIPs by up to 16% and 26%, respectively, compared to centralized ESN and deep learning algorithms.

关键词： Wireless communication Wireless sensor networks Delays Uplink Downlink Prediction algorithms Machine learning

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Data Correlation-Aware Resource Management in Wireless Virtual Reality (VR): An Echo State Transfer Learning Approach

arXiv

引用

arXiv 2019年

作者： Chen, Mingzhe Saad, Walid Yin, Changchuan Debbah, Mérouane Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing100876 China Wireless@VT Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA United States Mathematical and Algorithmic Sciences Lab Huawei France R and D Paris

Providing seamless connectivity for wireless virtual reality (VR) users has emerged as a key challenge for future cloud-enabled cellular networks. In this paper, the problem of wireless VR resource management is investigated for a wireless VR network in which VR contents are sent by a cloud to cellular small base stations (SBSs). The SBSs will collect tracking data from the VR users, over the uplink, in order to generate the VR content and transmit it to the end-users using downlink cellular links. For this model, the data requested or transmitted by the users can exhibit correlation, since the VR users may engage in the same immersive virtual environment with different locations and orientations. As such, the proposed resource management framework can factor in such spatial data correlation, so as to better manage uplink and downlink traffic. This potential spatial data correlation can be factored into the resource allocation problem to reduce the traffic load in both uplink and downlink. In the downlink, the cloud can transmit 360 contents or specific visible contents (e.g., user field of view) that are extracted from the original 360 contents to the users according to the users' data correlation so as to reduce the backhaul traffic load. In the uplink, each SBS can associate with the users that have similar tracking information so as to reduce the tracking data size. This data correlation-Aware resource management problem is formulated as an optimization problem whose goal is to maximize the users' successful transmission probability, defined as the probability that the content transmission delay of each user satisfies an instantaneous VR delay target. To solve this problem, a machine learning algorithm that uses echo state networks (ESNs) with transfer learning is introduced. By smartly transferring information on the SBS's utility, the proposed transfer-based ESN algorithm can quickly cope with changes in the wireless networking environment due to users' conten

关键词： Virtual reality

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