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126th ASEE Annual Conference and Exposition: Charged Up for the Next 125 Years, ASEE 2019

作者： Rahouti, Mohamed Xiong, Kaiqi Department of Electrical Engineering University of South Florida Tampa33620 United States Cyber Florida University of South Florida Tampa33620 United States Department of Mathematics and Statistics University of South Florida Tampa33620 United States Intelligent Computer Networking and Security Lab University of South Florida Tampa33620 United States

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Understanding global environment for network innovations (GENI) and software-defined networking (SDN) for computer networking and security education 126

Understanding global environment for network innovations (GE...

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126th ASEE Annual Conference and Exposition: Charged Up for the Next 125 Years, ASEE 2019

Hands-on modules and experiments are considered essential and fundamental components in cyber security curriculums. However, because of the significant increase in student enrollments in both online and face-to-face courses, universities face various challenges mainly related to financial support and computing resources that could be limited. To overcome such key challenges, universities have been considering alternative solutions to solve resource issues and allow students to practice real-world lab experiments through a virtual environment such as the Global Environment for Network Innovations (GENI). GENI is a real-world, repeatable, programmable, at-scale, virtual infrastructure for experiments in a variety of computer science areas such as networking, security, and distributed computing sponsored by National Science Foundation (NSF). Furthermore, Software-Defined networking (SDN) has been a core technology in cloud computing and other cyber-physical systems where SDN facilitates network management and enables network programmability and efficient network configuration to improve network performance, monitoring, and security. In this paper, we will demonstrate our great efforts in the development of GENI and SDN learning and experimental modules for computer networking and security courses in order to achieve the goal of our funded NSF project. Specifically, we will first present our methodology for the design of our modules and then give the detail of GENI and SDN modules including GENI account setup and resource reservation, measurement tool labs, as well as SDN labs for network traffic management and the detection and mitigation of several well-known security attacks, such as Denial of Service Attacks (DoS), Distributed Denial of Service Attacks (DDoS), phishing attacks, and Domain Generation Algorithm (DGA) malware detection. Those learning and experimental modules have been developed at different levels to meet the need of different types of students. Final

关键词： Software defined networking

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Intelligent spectrum learning for wireless networks with reconfigurable intelligent surfaces

arXiv

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arXiv 2021年

作者： Yang, Bo Cao, Xuelin Huang, Chongwen Yuen, Chau Qian, Lijun Renzo, Marco Di Engineering Product Development Pillar Singapore University of Technology and Design Singapore487372 Singapore Zhejiang Provincial Key Lab of information processing communication and networking Zhejiang University No.38 Zheda Road Hangzhou310007 China Department of Electrical and Computer Engineering CREDIT Center Prairie View A&M University Texas A&M University System Prairie ViewTX77446 United States Université Paris-Saclay CNRS CentraleSupélec Laboratoire des Signaux et Systèmes 3 Rue Joliot-Curie Gif-sur-Yvette91192 France

Reconfigurable intelligent surface (RIS) has become a promising technology for enhancing the reliability of wireless communications, which is capable of reflecting the desired signals through appropriate phase shifts. However, the intended signals that impinge upon an RIS are often mixed with interfering signals, which are usually dynamic and unknown. In particular, the received signal-to-interference-plus-noise ratio (SINR) may be degraded by the signals reflected from the RISs that originate from non-intended users. To tackle this issue, we introduce the concept of intelligent spectrum learning (ISL), which uses an appropriately trained convolutional neural network (CNN) at the RIS controller to help the RISs infer the interfering signals directly from the incident signals. By capitalizing on the ISL, a distributed control algorithm is proposed to maximize the received SINR by dynamically configuring the active/inactive binary status of the RIS elements. Simulation results validate the performance improvement offered by deep learning and demonstrate the superiority of the proposed ISL-aided approach. Copyright © 2021, The Authors. All rights reserved.

关键词： Convolutional neural networks

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DynoBrace: Stability Control of Ankle Joint Using a Mobile App Controlled Smart Brace Device

DynoBrace: Stability Control of Ankle Joint Using a Mobile A...

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2018 IEEE MIT Undergraduate Research Technology Conference, URTC 2018

作者： Norbaka, Kendra A. Rishmany, Allison M. O'Hara, Joseph J. Filippone, Paul V. Yu, Chen-Hsiang Kiapour, Ali Wentworth Institute of Technology Department of Biomedical Engineering United States Wentworth Institute of Technology Department of Computer Science and Networking United States

ISBN: (纸本)9781538693742

Ankle joint injuries and instability are becoming the most common injury involving the musculoskeletal system. People's lifestyles consist of a variety of activities which would involve stretching and tearing of the three outer ligaments of the foot. Almost 2.15 per 1000 persons, in the general population, per year will experience some form of ankle joint sprain or injury. Although in many cases the patients go on to heal without long term consequences, some may go on to develop chronic ankle instability overtime. As the ankle heals, different braces are introduced to the patient. The constant stiffness that passive braces impose on the patient can negatively affect the gait cycle and the overall motion of the ankle joint over time. Ankle joint instability is a debilitating condition incorporating recurrent sprains, persistent pain and repeated instances of giving way. Wearable ankle braces or assistive devices are intended to provide stability to the injured joint and help the user to get back to the normal lifestyle while the joint is healing and recovering its normal function. Although such devices have been shown to be useful, many limitations interfere with user's lifestyle by preventing them to pursue occupational or normal day activities due to joint impairment. Lengthy recovery time due to lack of the joint's natural activity is an example of such limitation. Controlled and limited exercise and mobility is important during recovery to improve the function in the nerves in the joint, increase stability, and decrease the patient's recovery time. This paper discusses a dynamic wearable smart brace developed and designed to improve the function and preserve the anatomical range of motion of the ankle joint in adults who suffer from ankle joint injury or instability. This paper illustrates the design of the DynoBrace, a smart, adaptive and dynamic brace that uses Micro-Electro-Mechanical Systems (MEMS) technology integrated with the help of a user-friendly mobile

关键词： Stability

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Resource allocation for wireless-powered iot networks with short packet communication

Resource allocation for wireless-powered iot networks with s...

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作者： Chen, Jie Zhang, Lin Liang, Ying-Chang Kang, Xin Zhang, Rui National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of China Chengdu611731 China Center for Intelligent Networking and Communications University of Electronic Science and Technology of China Chengdu611731 China Department of Electrical and Computer Engineering National University of Singapore Singapore119077 Singapore

Internet-of-Things (IoT) is a promising technology to connect massive machines and devices in the future communication networks. In this paper, we study a wireless-powered IoT network (WPIN) with short packet communication (SPC), in which a hybrid access point (HAP) first transmits power to the IoT devices wirelessly, then the devices in turn transmit their short data packets achieved by finite blocklength codes to the HAP using the harvested energy. Different from the long packet communication in conventional wireless network, SPC suffers from transmission rate degradation and a significant packet error rate. Thus, conventional resource allocation in the existing literature based on Shannon capacity achieved by the infinite blocklength codes is no longer optimal. In this paper, to enhance the transmission efficiency and reliability, we first define effective-Throughput and effective-Amount-of-information as the performance metrics to balance the transmission rate and the packet error rate, and then jointly optimize the transmission time and packet error rate of each user to maximize the total effective-Throughput or minimize the total transmission time subject to the users' individual effective-Amount-of-information requirements. To overcome the non-convexity of the formulated problems, we develop efficient algorithms to find high-quality suboptimal solutions for them. The simulation results show that the proposed algorithms can achieve similar performances as that of the optimal solution via exhaustive search, and outperform the benchmark schemes. © 2002-2012 IEEE.

关键词： Resource allocation

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Scaling Law Based D2D Wireless Ad-Hoc Networks in the Finite Blocklength Regime

Scaling Law Based D2D Wireless Ad-Hoc Networks in the Finite...

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IEEE Global Communications Conference

作者： Xi Zhang Qixuan Zhu H. Vincent Poor Department of Electrical and Computer Engineering Networking and Information Systems Laboratory Texas A&M University College Station TX USA Department of Electrical Engineering Princeton University Princeton NJ USA

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

A device-to-device (D2D) wireless ad hoc network architecture enables dynamic self-organizing communications among mobile users who can directly exchange information with their peers without a pre-determined network infrastructure. Moreover, finite blocklength coding (FBC) is the promising candidate technique to support time sensitive multimedia wireless networks services, where mobile users transmit short packets to upper-bound the transmission delay of video/audio traffic. The scaling law technique models the maximum D2D channel capacity as a function of the density of mobile users. Recent studies have integrated D2D wireless ad hoc networks with FBC theory to further improve the performance of 5G wireless ad hoc networks. However, how to model and analyze the capacity of D2D wireless ad hoc networks under the finite blocklength regime is not well understood and has not been thoroughly studied. To overcome these challenges, applying the scaling law technique, we derive upper-bounds on the coding rate of each D2D channel and the number of time slots needed to complete all D2D transmissions. Combining the D2D channel's coding rate with the number of time slots needed for all D2D transmissions, we derive the maximum aggregate throughput for wireless ad hoc networks with all mobile users using D2D communications while mitigating interference. We also develop a model where each D2D channel follows the Nakagami-m distribution, under which we derive the average aggregate throughput and its upper-bound. Finally, we evaluate our derived results in the D2D wireless ad hoc networks over finite blocklength regime through numerical analyses.

关键词： Device-to-device communication Mobile ad hoc networks Encoding Throughput Wireless communication Aggregates

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Confidence-Regulated Generative Diffusion Models for Reliable AI Agent Migration in Vehicular Metaverses

arXiv

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arXiv 2025年

作者： Kang, Yingkai Kang, Jiawen Wen, Jinbo Zhang, Tao Yang, Zhaohui Niyato, Dusit Zhang, Yan School of Automation Guangdong University of Technology Guangzhou510006 China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing210016 China School of Cyberspace Science and Technology Beijing Jiaotong University Beijing100044 China College of Information Science and Electronic Engineering Zhejiang Provincial Key Lab of information processing communication and networking Zhejiang University Hangzhou310007 China College of Computing and Data Science Nanyang Technological University Singapore Department of Informatics University of Oslo the Simula Research Laboratory Norway

Vehicular metaverses are an emerging paradigm that merges intelligent transportation systems with virtual spaces, leveraging advanced digital twin and Artificial Intelligence (AI) technologies to seamlessly integrate vehicles, users, and digital environments. In this paradigm, vehicular AI agents are endowed with environment perception, decision-making, and action execution capabilities, enabling real-time processing and analysis of multi-modal data to provide users with customized interactive services. Since vehicular AI agents require substantial resources for real-time decision-making, given vehicle mobility and network dynamics conditions, the AI agents are deployed in RoadSide Units (RSUs) with sufficient resources and dynamically migrated among them. However, AI agent migration requires frequent data exchanges, which may expose vehicular metaverses to potential cyber attacks. To this end, we propose a reliable vehicular AI agent migration framework, achieving reliable dynamic migration and efficient resource scheduling through cooperation between vehicles and RSUs. Additionally, we design a trust evaluation model based on the theory of planned behavior to dynamically quantify the reputation of RSUs, thereby better accommodating the personalized trust preferences of users. We then model the vehicular AI agent migration process as a partially observable markov decision process and develop a Confidence-regulated Generative Diffusion Model (CGDM) to efficiently generate AI agent migration decisions. Numerical results demonstrate that the CGDM algorithm significantly outperforms baseline methods in reducing system latency and enhancing robustness against cyber attacks. Copyright © 2025, The Authors. All rights reserved.

关键词： Markov processes

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Optimal QoS-Driven Power Allocation for Energy Harvesting Wireless Ad-Hoc Networks Using FBC

Optimal QoS-Driven Power Allocation for Energy Harvesting Wi...

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IEEE Global Communications Conference

作者： Xi Zhang Jingqing Wang H. Vincent Poor Department of Electrical and Computer Engineering Networking and Information Systems Laboratory Texas A&M University College Station TX USA Department of Electrical Engineering Princeton University Princeton NJ USA

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

In the last few decades, the statistical delay-bounded quality-of-service (QoS) technique has been proposed and investigated to support delay-bounded 5G multimedia wireless services In addition, energy harvesting (EH) based systems, which enable mobile devices to harvest energy from various external sources, have been designed to address the energy scarcity problem. Researchers have recently integrated EH based systems with short-packet communications for their potential benefits of small payloads and low latency to support reliable multimedia data transmissions. Under the short delay requirements for the low-latency 5G multimedia wireless services, it is not ideal to apply the traditional Shannon capacity for modeling the data rate under the error-rate bounded in the non-asymptotic regime. Accordingly, researchers have developed the finite wireless data transmission rate in the non-asymptotic regime. However, it is challenging to determine the convexity of the effective-capacity maximization problem subject to the statistical delay-bounded and error-rate bounded QoS constraints due to the complexity of analyzing the maximization problem in the non-asymptotic regime. To overcome these challenges, we design the EH based cross-layer optimization scheme in supporting the statistical delay-bounded and error-rate bounded QoS requirements in the finite blocklength regime in the following steps. First, we characterize the EH based system models under finite blocklength coding (FBC). Second, we derive and analyze the convexity of the e-effective capacity maximization problem for our proposed EH scheme in the finite blocklength regime. Finally, we conduct several simulation evaluations which validate our proposed EH scheme under the statistical delay-bounded and error-rate bounded QoS constraints in the finite blocklength regime.

关键词： Quality of service Ad hoc networks Wireless communication Data communication Error probability Energy harvesting 5G mobile communication

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Minimum-Energy and Error-Rate for URLLC Networks Over Nakagami-m Channels: A Finite-Blocklength Analysis

Minimum-Energy and Error-Rate for URLLC Networks Over Nakaga...

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IEEE Global Communications Conference

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

The fifth generation (5G) wireless networks aim at providing a wide range of time-sensitive multimedia services and applications to satisfy users' stringent requirements on delay-bounded quality of service (QoS). One of the important requirements for 5G multimedia wireless networks is to efficiently support the ultra-reliable and low-latency communications (URLLC). Finite blocklength coding (FBC) is a promising candidate technique to support URLLC services, where mobile users transmit short packets to upper-bound the transmission delay of multimedia traffic. In this paper, we model and analyze the packet-block error rate for URLLC under the Nakagami-m fading channel in the finite blocklength regime. Then, we derive the minimum energy per bit for data transmissions in the Nakagami-m fading channel under the constraint of block error rate. To derive closed-form expressions for the minimum energy per bit, we obtain achievability and converse bounds on the minimum energy per bit, and show that these two bounds are equal to each other. Finally, we evaluate our derived minimum energy per bit in the finite blocklength regime through numerical analyses, and compare it with those under the Rayleigh fading channel and the wideband approximation, validating our derived analytical results.

关键词： Fading channels Error analysis Decoding Wireless networks Encoding Antennas 5G mobile communication

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Teaching DevOps and Cloud Based Software engineering in University Curricula

Teaching DevOps and Cloud Based Software Engineering in Univ...

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IEEE International Conference on e-Science and Grid Computing

作者： Yuri Demchenko Zhiming Zhao Jayachander Surbiryala Spiros Koulouzis Zeshun Shi Xiaofeng Liao Jelena Gordiyenko University of Amsterdam System and Networking Lab Amsterdam The Netherlands Department of Electrical Engineering and Computer Science University of Stavanger Stavanger Norway Agile Telecom

ISBN: (数字)9781728124513

ISBN: (纸本)9781728124520

This paper presents recommendations on the design and pilot implementation of the DevOps and Cloud based Software Development curricula for computer Science and Software engineering masters. The central part of proposed approach is the Body of Knowledge in the DevOps technologies for Software engineering (DevOpsSE BoK) that defines a set Knowledge Areas and Knowledge Units required for SE professionals to work efficiently as DevOps engineer or application developer. Defining DevOpsSE-BoK provides a basis for defining required professional competences and skills and allows consistent curricula structuring and profiling. The paper also reports on the experience of the first course run on 2018/2019 academic year at the University of Amsterdam. The paper presents the structure of the course and explains what instructional methodologies have been used for course development, such as project based learning that facilitates the students' team based skills both in mastering Agile development process and skills sharing. The paper provides a short summary of the generally used DevOps definitions, concepts, models and tools, specifically focusing on the cloud based DevOps tools for software development, deployment and operation that allows the main DevOps principle of continuous development and continuous improvement which are critical for modern agile data driven companies.

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