Article
Engineering, Electrical & Electronic
Kechen Zheng, Xiaoying Liu, Biao Wang, Haifeng Zheng, Kaikai Chi, Yuan Yao
Summary: This paper investigates energy management in a wireless-powered communication network and proposes a method to dynamically adjust energy transfer mechanism based on the energy states and geographic locations of sensor nodes. By comparing the energy harvesting and data transmission ranges, the network topology is divided into two cases for throughput analysis, which ultimately proves the existence of an optimal energy threshold, enhancing the achievable throughput.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Automation & Control Systems
Wei Chen, Zidong Wang, Derui Ding, Xiaojian Yi, Qing-Long Han
Summary: This article discusses the problem of distributed state estimation over wireless sensor networks, introduces a new distributed state estimator, and systematically discusses the probability distribution of energy level. Furthermore, the optimal estimator gain is derived by minimizing the trace of the estimation error covariance, and the convergence of the minimized upper bound of the expected estimation error covariance is analyzed.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Computer Science, Information Systems
Claudio Battiloro, Paolo Di Lorenzo, Paolo Banelli, Sergio Barbarossa
Summary: The study focuses on decentralized estimation of time-varying signals at a fusion center with energy harvesting sensors transmitting data over rate-constrained links. Dynamic strategies are proposed for selecting radio parameters, sampling sets, and harvested energy at each node. Stochastic optimization tools are used for adaptive optimization without prior knowledge of channel statistics. Numerical results validate the approach for decentralized signal estimation under communication and energy constraints typical of Internet-of-Things scenarios.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Engineering, Multidisciplinary
Amit Grover, R. Mohan Kumar, Mohit Angurala, Mehtab Singh, Anu Sheetal, R. Maheswar
Summary: The paper proposes a new rate aware congestion control (RACC) mechanism in WSNs to improve congestion and achieve better QoS parameters like throughput and packet delivery ratio. The RACC has shown significant improvements over existing techniques in terms of various parameters like throughput, packet delivery ratio, and routing overhead.
ALEXANDRIA ENGINEERING JOURNAL
(2022)
Article
Energy & Fuels
Otim Patricia Angwech, Attahiru S. Alfa, B. T. J. Maharaj
Summary: Wireless sensor networks face challenges in energy management, and energy harvesting is proposed as an alternative to traditional battery sources. This study investigates the performance of individual nodes and addresses the issue of threshold management in the energy buffer. The results show a trade-off between threshold and leakage rate.
Article
Telecommunications
Deivanai Gurusamy, Galane Diriba
Summary: This paper describes a water quality monitoring system using energy-harvesting wireless sensor networks, which extends the system's life with a solar energy harvesting circuit. The system shows promising results in field tests and operates continuously without power outages.
WIRELESS PERSONAL COMMUNICATIONS
(2022)
Article
Computer Science, Theory & Methods
Jie Wan, Ji Chen
Summary: A reasonable relay selection algorithm for energy collection wireless sensor networks is proposed, which optimizes cooperation probability and selects optimal node based on multiple criteria to save energy consumption and prolong network lifetime significantly.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Computer Science, Information Systems
Tongxin Zhu, Jianzhong Li, Hong Gao, Yingshu Li
Summary: A novel network called battery-free wireless sensor network (BF-WSN) is proposed to overcome the limitations of battery-powered wireless sensor networks. In BF-WSNs, battery-free sensor nodes harvest energy from the environment instead of relying on batteries, allowing them to have unlimited energy consumption. However, they still face challenges in terms of energy harvesting rates and capacities. This paper focuses on the Minimum-Latency Aggregation Scheduling problem in BF-WSNs, which is proved to be NP-hard. A Data Aggregation Scheduling algorithm is proposed to address the problem, and theoretical analysis and extensive simulations are conducted to evaluate its performance.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2022)
Article
Engineering, Electrical & Electronic
Huiwen Yang, Mengyu Huang, Yuzhe Li, Subhrakanti Dey, Ling Shi
Summary: This paper investigates remote state estimation with simultaneous wireless information and power transfer (SWIPT). We jointly optimize the transmission power allocations of the remote estimator and sensor and formulate the problem as a Markov decision process. Simulation results are provided to verify the main findings.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2022)
Article
Engineering, Civil
Liangliang Lou, Miao Zhou, Biao Chen, Mingan Lu, Chunlei Zheng, Shiqing Zhang
Summary: The Smart Parking System (SPS) has been effective in solving urban parking problems by utilizing battery-powered Wireless Parking Detectors (WPDs) based on IoT technology. However, the low turnover rates of parking spaces in Shanghai, China result in wasted energy from the collection and processing of redundant sensor data by WPDs. This paper proposes an Energy Harvesting-driven Parking Detection (EHPD) method that uses vehicle-induced seismic signals and wireless energy attenuation to achieve parking detection. Experimental results demonstrate that EHPD can achieve the same functions as existing WPD devices with lower cost and energy consumption.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Information Systems
Shitij Avlani, Dong-Hyun Seo, Baibhab Chatterjee, Shreyas Sen
Summary: This research focuses on the challenges in designing energy-harvested sensor nodes and proposes a perpetually powered sensor node that utilizes energy-information dynamic co-optimization (EICO) to achieve long-range communication and minimize information loss.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Tony Tony, Sieteng Soh, Kwan-Wu Chin, Mihai Lazarescu
Summary: This paper investigates the issue of deriving a TDMA link schedule for rechargeable wireless sensor networks, taking into account energy harvesting time, battery cycle constraints, and battery imperfections. A greedy heuristic is proposed to schedule links based on node energy levels. Simulation results demonstrate that enforcing battery cycle constraints can significantly extend the link schedule.
Article
Automation & Control Systems
Guangmo Yi, Hui Sun, Yake Yang
Summary: In this paper, a malicious attack issue against remote state estimation in cyber-physical systems is investigated. The sensor adopts an acknowledgment-based online power schedule to improve the remote state estimation, but it also increases the risk of being attacked. The attacker can intercept and modify the ACK signals to induce the sensor to make poor decisions while remaining undetected.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2023)
Article
Automation & Control Systems
Ali Forootani, Raffaele Iervolino, Massimo Tipaldi, Subhrakanti Dey
Summary: This paper discusses a remote estimation problem in which multiple dynamical systems are observed by smart sensors. The sensors transmit their local estimates to a remote estimator over channels with packet losses. The paper proposes a method for optimal sensor transmission scheduling by minimizing the estimation error covariance cost while considering transmission constraints. A novel approach based on Least Squares Temporal Difference (LSTD) Approximate Dynamic Programming (ADP) is used to approximate the value function.
Article
Computer Science, Information Systems
Raja Waseem Anwar, Fatma Outay, Kashif Naseer Qureshi, Saleem Iqbal, Kayhan Zrar Ghafoor
Summary: The Internet of Things (IoT) is a groundbreaking technology that enables seamless data exchange between devices, individuals, and processes. However, due to deployment unpredictability, battery-operated nature, and the intricate nature of IoT networks, the energy levels of sensor nodes deplete rapidly, significantly reducing the network's lifespan. This paper introduces a State-based Energy Calculation Scheme (SECS) to address these challenges and improve network performance.
Article
Engineering, Electrical & Electronic
Muddassar Hussain, Nicolo Michelusi
Summary: This paper proposes a learning and adaptation framework for millimeter-wave vehicular networks to enable adaptive beam-tracking and training with low overhead. The dual timescale approach utilizes a deep recurrent variational autoencoder (DR-VAE) and a partially observable Markov decision process (PO-MDP) to optimize beam-training procedures. Numerical results show significant improvements in spectral efficiency and performance compared to traditional methods.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2022)
Article
Computer Science, Hardware & Architecture
Seyyedali Hosseinalipour, Sheikh Shams Azam, Christopher G. Brinton, Nicolo Michelusi, Vaneet Aggarwal, David J. Love, Huaiyu Dai
Summary: This paper proposes a multi-stage hybrid federated learning (MH-FL) method, extending the traditional federated learning topology through the network dimension and considering a multi-layer cluster-based structure. The research results demonstrate the advantages of MH-FL in terms of resource utilization metrics.
IEEE-ACM TRANSACTIONS ON NETWORKING
(2022)
Article
Telecommunications
Bharath Keshavamurthy, Nicolo Michelusi
Summary: The LESSA framework introduces a novel learning-based spectrum sensing and access strategy, achieving a good balance between sensing accuracy and CR throughput by learning the LUs spectrum occupancy model and optimizing the spectrum sensing and access policy. MA-LESSA further extends to a distributed multi-agent setting, improving CR throughput through neighbor discovery and channel access rank allocation.
IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING
(2022)
Article
Anthropology
Caterina Suitner, Leonardo Badia, Damiano Clementel, Laura Iacovissi, Matteo Migliorini, Bruno Gabriel Salvador Casara, Domenico Solimini, Magdalena Formanowicz, Tomaso Erseghe
Summary: This study investigates the psycho-linguistic features of online discourse on climate change, focusing on modifications during the years 2017-2019 resulting from global collective actions. The research aims to understand the emerging connection between digital activism and related psychological processes. By analyzing a semantic network derived from Twitter, the study traces the evolution of the discourse over time and identifies textual indicators of social identity and empowerment. Original proposals are made to identify communities and highlight important semantic contents from a network perspective. The study also explores the projection of the online discourse on climate change towards future developments in pro-environmental campaigns.
Article
Computer Science, Information Systems
Nicolo Michelusi, Gesualdo Scutari, Chang-Shen Lee
Summary: This paper presents distributed algorithms for addressing (strongly convex) composite optimization problems over mesh networks with quantized communications. A black-box model is proposed, transforming linearly convergent distributed algorithms into fixed-point iterates. The algorithmic model includes a novel biased compression (BC) rule on the quantizer design and an adaptive encoding non-uniform quantizer (ANQ) coupled with a communication-efficient encoding scheme. The paper also introduces a unified communication complexity analysis, demonstrating the average number of bits required to achieve a target accuracy for the optimization problem. Numerical results confirm the theoretical findings and show the superior communication cost of algorithms equipped with ANQ.
IEEE TRANSACTIONS ON INFORMATION THEORY
(2022)
Article
Computer Science, Information Systems
Alberto Zancanaro, Giulia Cisotto, Leonardo Badia
Summary: This paper investigates data correlation in remote sensing networks and characterizes it through diverse models quantifying the Value of Information (VoI). The VoI evaluations include the average node-specific Age of Information (AoI), the average cost spent for sending updates, and the AoI of neighbor nodes. The simplification of the representation through including the impact of neighbor nodes within the transition probabilities is shown to provide the same insight in terms of VoI evaluations.
COMPUTER COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Tzu-Hsuan Chou, Nicolo Michelusi, David J. Love, James V. Krogmeier
Summary: 6G operators may use mmWave and sub-THz bands to meet wireless access demand, but sub-THz communication faces new challenges due to wider bandwidths and harsher propagation conditions. This paper proposes a compressed training framework for estimating time-varying sub-THz MIMO-OFDM channels.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Luca Corradini, Dragan Maksimovic
Summary: This article demonstrates that lossless switched-mode power converters may not have a unique steady-state solution, especially odd-order converters. Indeterminate converters can be sensitive to nonideal effects and exhibit undesired voltages or circulating currents with both dc and ac components. The developed mathematical framework and theory provide a systematic assessment of steady-state indeterminacy and explain the behavior of various converter topologies, such as multiphase and multilevel dc-dc converters.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Stefano Cabizza, Giorgio Spiazzi, Luca Corradini
Summary: This article presents the analysis, design, and implementation of a 2 MHz, 12 V, 600 mA, GaN-based active-clamped isolated SEPIC converter (ACISC) supporting full zero-voltage switching (ZVS) throughout the 9-18 V automotive range, and intended to provide isolation and power interface between the 12 V battery and the low-power subnet. Performance comparison with both a 7.2 W GaN-based active-clamped isolated flyback converter (ACIFC) and a commercial flyback converter is also included.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2023)
Article
Chemistry, Analytical
Alberto Zancanaro, Giulia Cisotto, Leonardo Badia
Summary: Recent advancements in technology, such as IoT and ML, have led to a significant increase in data generation in smart environments through WSN. The freshness of this data, measured by AoI, is crucial for anomaly detection and adaptive control. However, current AoI metrics fail to capture the multi-structured nature of the data, and the potential benefits of sensor correlation and ML techniques. By studying correlation effects on AoI under different access scenarios, we show that correlated sensors can improve AoI in concurrent transmissions, and ML can further optimize transmission policies without affecting AoI.
Article
Telecommunications
Bharath Keshavamurthy, Matthew A. Bliss, Nicolo Michelusi
Summary: This work presents a scalable framework for coordinating a swarm of rotary-wing UAVs as cellular relays to improve connectivity and traffic offloading for ground users. It develops a Multiscale Adaptive Energy-conscious Scheduling and Trajectory Optimization framework for a single UAV and extends it to UAV swarms. Numerical evaluations demonstrate the effectiveness of the proposed framework in terms of faster service and improved data payloads.
IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING
(2023)
Article
Telecommunications
Leonardo Badia
Summary: This paper provides an analytical derivation of age of information for a data stream transmitted over an error-prone channel using a selective repeat automatic repeat request for error control. The impact of the error process and/or the round trip time on the resulting age of information is assessed. The analysis allows for generating the complete statistics of AoI. The results highlight the consequences of a mild correlation in the error process, where the error bursts are not significantly longer than the round trip time, causing a decrease in AoI. This can serve as a reference for designing retransmission-based error control that prioritizes information freshness.
IEEE COMMUNICATIONS LETTERS
(2023)
Proceedings Paper
Computer Science, Information Systems
Leonardo Badia, Andrea Zanella, Michele Zorzi
Summary: This paper examines how selfish players can behave efficiently in a slotted ALOHA system with capture effect when driven by the age of information. Using fully analytical derivations, the paper highlights the impact of cost coefficient and capture threshold on achieving efficient allocation, and shows that when the capture effect is relatively strong, the Nash equilibrium of the system can achieve near-optimal performance.
IEEE INFOCOM 2022 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS)
(2022)
Proceedings Paper
Automation & Control Systems
Janko Celikovic, Angel Maria Gomez Arguello, Wisam Al-Hoor, John Kesterson, Siamak Abedinpour, Luca Corradini, Dragan Maksimovic
Summary: This paper presents a novel autotuning method to improve controller performance in mobile device battery chargers. The method uses a comprehensive and simple self-tuning algorithm to maximize bandwidth and ensure stability. By using single-tone injection, single-node measurement, and generating orthogonal components, the algorithm enables the extraction of phase and quadrature projections of the response.
2022 IEEE 23RD WORKSHOP ON CONTROL AND MODELING FOR POWER ELECTRONICS (COMPEL 2022)
(2022)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Elvina Gindullina, Sebastian Mortag, Maxim Dudin, Leonardo Badia
Summary: In this paper, the problem of finding parking spots for intelligent autonomous vehicles in a smart city environment is studied using game theory, and the efficiency of a distributed decision mechanism is evaluated. The research reveals the complexity of identifying efficient solutions and suggests that the overall problem is difficult to solve without compromising the selfish objectives of individual vehicles. Additionally, proposed distributed simulation scenarios aim to capture aspects of competition for further analytical studies.
2021 IEEE 22ND INTERNATIONAL SYMPOSIUM ON A WORLD OF WIRELESS, MOBILE AND MULTIMEDIA NETWORKS (WOWMOM 2021)
(2021)