Article
Engineering, Electrical & Electronic
Long Cheng, Linghe Kong, Yu Gu, Jianwei Niu, Ting Zhu, Cong Liu, Shahid Mumtaz, Tian He
Summary: In this work, a collision-free convergecast protocol named iCore is proposed for low-duty-cycle WSNs to minimize data collisions and improve channel utilization. iCore utilizes dynamic forwarding technique and optimization algorithms to reduce end-to-end latency and maintain high delivery ratio and energy efficiency in various convergecast scenarios.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2022)
Article
Computer Science, Information Systems
Anastassia Gharib, Mohamed Ibnkahla
Summary: This article proposes a node embedding with security resource allocation (NESRA) clustering algorithm for mobile ICWSNs, allocating security resources to sensor nodes in three steps to achieve efficient ICWSN operation, data security, and timely data access to mobile users.
IEEE INTERNET OF THINGS JOURNAL
(2022)
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
Computer Science, Information Systems
Tien-Dung Nguyen, Duc-Tai Le, Van-Vi Vo, Moonseong Kim, Hyunseung Choo
Summary: This article studies the minimum time aggregation scheduling problem in duty-cycled sensor networks, proposing the collision-resistant dynamic (CORD) scheduling approach. The CORD method can dynamically change data receivers in order to reduce aggregation time in any scenario. Results show a significant improvement in aggregation time with comparable time complexity to state-of-the-art methods.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Hardware & Architecture
Sahar Ahmadi Khah, Ali Barati, Hamid Barati
Summary: This paper presents a dynamic and multi-level key management method for wireless sensor networks. The method utilizes a MAC-based authentication mechanism and divides the network into different levels and clusters. The proposed approach achieves efficient key establishment and rekeying processes while minimizing energy consumption and communication overhead.
Article
Automation & Control Systems
Hao Fu, Lei Deng, Baoping Tang, Chunhua Zhao, Yi Huang
Summary: This article proposes a time-space incentives control algorithm to dynamically improve the topology equilibrium for wireless sensor networks used in mechanical vibration monitoring systems. Multiple relevant parameters that influence the network topology are designed and adopted, and two calculation methods are devised to determine the parameter weights. A static evaluation model is constructed to measure the performance of the network topology in the space dimension. Based on this model, the proposed algorithm dynamically adjusts the network topology by changing the transmission power of each node considering the comprehensive evaluation value.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Electrical & Electronic
Kezhong Liu, Yuting Ma, Mozi Chen, Kehao Wang, Kai Zheng, Xuming Zeng
Summary: This article proposes an efficient emergency evacuation algorithm for dynamic hazardous ship indoor environment, which minimizes the total dynamic typical delay for each passenger while meeting the deadline for ship capsizing. It constructs a 3-D topological model based on ship interior layout and analyzes the roll motion of a damaged passenger ship. An adaptive navigation algorithm is presented to provide a hazard-avoid path and optimize the navigation success ratio.
IEEE SENSORS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Mohammad Moltafet, Markus Leinonen, Marian Codreanu, Nikolaos Pappas
Summary: This article presents a status update system where multiple sensors transmit information about random processes to a sink. By optimizing the sampling action, transmit power allocation, and sub-channel assignment, the trade-off between power consumption and information freshness is achieved. A dynamic control algorithm and a sub-optimal solution are proposed and their performance is evaluated through numerical results.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Yadong Gong, Xiaoyun Guo, Guoming Lai
Summary: In this article, a centralized energy-efficient clustering (CEEC) protocol is proposed to enhance energy efficiency in wireless sensor networks (WSNs) through node energy balancing schemes. The CH-rotation approach is used for intracluster energy balancing, while four sequential algorithms are suggested for intercluster energy balancing. Simulation results demonstrate that the CEEC protocol outperforms classical clustering mechanisms in terms of network lifetime, energy consumption, and network throughput.
IEEE SENSORS JOURNAL
(2023)
Article
Automation & Control Systems
Liwei An, Guang-Hong Yang
Summary: This article investigates a data-based distributed sensor scheduling algorithm for a wireless sensor network, which allows multiple sensor nodes to monitor different linear systems and transmit measured information over a shared wireless channel. Through the introduction of a distributed minimum subset extraction mechanism, the algorithm provides an approximate solution to minimize the H(infinity) performance index of the closed-loop system without requiring system parameter knowledge. Under sufficiently rich disturbances, the algorithm converges to the exact optimal solution.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Computer Science, Information Systems
Niayesh Gharaei, Yasser D. Al-Otaibi, Suhail Ashfaq Butt, Sharaf Jameel Malebary, Sabit Rahim, Gul Sahar
Summary: By optimizing the moving trajectory and charging time of the wireless mobile charger, the proposed schemes remarkably enhance the network performance in terms of different evaluation metrics, improving energy efficiency and network lifetime.
IEEE SYSTEMS JOURNAL
(2021)
Article
Computer Science, Information Systems
Ye Yuan, Wei Yi, Wan Choi
Summary: In this article, a cost-aware dynamic sensor scheduling (CADSS) framework is proposed for wireless sensor networks (WSNs) with multiple tasks. CADSS provides a comprehensive task utility evaluation methodology for self-organized WSNs by minimizing system cost and maintaining desired task qualities. The effectiveness of CADSS is verified by applying it to a multitarget tracking (MTT) application.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Multidisciplinary Sciences
Xiuwu Yu, Ying Li, Yong Liu, Hao Yu
Summary: The ACRFD algorithm effectively balances the energy consumption of wireless sensor networks and prolongs the network lifetime while ensuring the real-time performance of data transmission by defining the forward transmission area of the node and introducing the cuckoo search algorithm.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2022)
Article
Computer Science, Information Systems
Kun Wang, Lei Wang, Mohammad S. Obaidat, Chi Lin, Muhammad Alam
Summary: This article proposes a charging scheduling scheme called Partial Charge to prolong the lifetime of wireless sensor networks and enhance system performance. By determining the appropriate ratio for partially charging nodes, prioritizing core nodes for service, and excluding nodes that cannot be saved, the proposed scheme outperforms competing schemes in terms of service time, survival rate, and waiting queue size according to simulation experiments.
IEEE SYSTEMS JOURNAL
(2021)
Article
Computer Science, Information Systems
Riheng Jia, Xiuling Zhang, Yanju Feng, Tianliang Wang, Jianfeng Lu, Zhonglong Zheng, Minglu Li
Summary: This study developed a deep Q-learning approach for long-term energy collection in self-sustainable sensor networks. Simulation results showed that sensors can intelligently learn to select the best energy collection location, and investigated the impact of system parameters on algorithm performance.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Yubal Barrios, Alfonso Rodriguez, Antonio Sanchez, Arturo Perez, Sebastian Lopez, Andres Otero, Eduardo de la Torre, Roberto Sarmiento
Article
Computer Science, Information Systems
Rodrigo Marino, Cristian Wisultschew, Andres Otero, Jose M. Lanza-Gutierrez, Jorge Portilla, Eduardo de la Torre
Summary: This article presents a machine learning-based methodology for fault detection in continuous processes, using a hybrid feature selection approach to select the most representative sensors and achieve high-quality fault identification. The proposed technique follows a distributed approach, overcoming limitations of centralized methods. Experimental results show that the methodology provides state-of-the-art detection quality for TEP fault-detection, with significantly lower latency and feature usage compared to other implementations. The scalability of the framework allows for optimal implementation selection based on application needs.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Engineering, Electrical & Electronic
Rodrigo Marino, Sergio Quintero, Andres Otero, Jose M. Lanza-Gutierrez, Miguel Holgado
Summary: This research presents a new methodology for real-time fluid characterization using machine learning techniques, integrating multi-dimensional photonic sensors into chemical processes in line with the Industry 4.0 paradigm. The method also includes a novel feature selection strategy that significantly reduces energy consumption while maintaining detection accuracy.
IEEE SENSORS JOURNAL
(2021)
Article
Computer Science, Hardware & Architecture
Rafael Zamacola, Andres Otero, Eduardo de la Torre
Summary: In this study, a dynamically multi-grain reconfigurable and scalable overlay architecture is built using reconfigurable SRAM-based FPGAs, allowing for real-time reconfiguration of the overlay composition, adjustment of overlay size to free up resources, and adaptation to variable computation demands. The overlay utilizes two different dynamic partial reconfiguration granularities - medium grain for composing processing elements and fine grain for mapping applications onto the overlay. The overlay has been successfully integrated into an SoC and an automated toolchain is proposed for offloading computing-intensive parts to hardware.
JOURNAL OF SYSTEMS ARCHITECTURE
(2021)
Article
Engineering, Electrical & Electronic
Cristian Wisultschew, Alejandro Perez, Andres Otero, Gabriel Mujica, Jorge Portilla
Summary: The shift of computing from the cloud to the edge of the Internet of Things is influencing deep learning applications. Moving intelligence closer to the point of need has advantages in terms of performance, power consumption, security, and privacy. However, dealing with massive data generated by data sources such as LIDAR sensors becomes challenging for edge devices, especially when heavy processing algorithms like deep neural networks are selected. This work demonstrates the feasibility of processing point cloud-based sensors at the edge using deep neural networks, thanks to new devices with high computing capacity and reduced power consumption. Evaluation of different edge processing architectures shows that neural accelerators with integrated host CPUs provide the best trade-off between power consumption and performance, making them an ideal solution for IoT applications at the edge level.
IEEE SENSORS JOURNAL
(2022)
Article
Computer Science, Hardware & Architecture
Alfonso Rodriguez, Andres Otero, Marco Platzner, Eduardo de la Torre
Summary: Current edge computing systems in complex application scenarios require the use of heterogeneous hardware/software platforms to meet changing requirements. However, the lack of unified software-driven programming models limits the efficient deployment of multi-purpose hardware-accelerated solutions. Additionally, edge computing systems face challenges in operating under diverse conditions.
IEEE TRANSACTIONS ON COMPUTERS
(2022)
Article
Computer Science, Information Systems
Remy Castro, Gabriel Mujica, Jorge Portilla
Summary: This research proposes a low-cost rowing propulsion monitoring system based on IoT technology, which can help analyze and optimize the performance of rowers. By integrating various sensing, communication, and data processing technologies, the system provides accurate real-time information and valuable technical support for rowers and coaches to define specific optimization profiles and improvement targets.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Jaime Senor, Jorge Portilla, Gabriel Mujica
Summary: The article discusses the significance of post-quantum cryptography in protecting modern public-key encryption from potential attacks by quantum computers. It evaluates the performance of NTRU in the context of IoT, showing its suitability for wireless sensor networks designed with modern microcontrollers.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Cristian Wisultschew, Rogelio Hernandez, Carlos Pastor, Jorge Portilla
Summary: LiDAR sensors are increasingly popular in IoT object detection due to their ability to provide precise distances, but manually generating data sets for deep learning is time-consuming and costly. This article proposes a method using a 3D simulator to automatically generate point cloud data sets for any LiDAR model, which can simulate custom scenarios for specific application requirements.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Juan Encinas, Alfonso Rodriguez, Andres Otero, Eduardo De la Torre
Summary: This paper applies machine learning techniques to extract predictive models of multiple hardware accelerators' performance, which are used to optimize system configuration under specific timing and power constraints. Additionally, a non-intrusive integrated instrumentation tool is proposed for measuring power consumption and execution performance in FPGA-based systems.
2021 XXXVI CONFERENCE ON DESIGN OF CIRCUITS AND INTEGRATED SYSTEMS (DCIS21)
(2021)
Article
Computer Science, Information Systems
Gabriel Mujica, Javier Henche, Jorge Portilla
Summary: Recent advances in wireless communication, sensing, and processing technologies have enabled new research and innovation opportunities in areas such as Industry 4.0, Smart Cities, and Intelligent Transportation Systems. One particular area of focus is on the railway domain where the concept of Railway Virtual Coupling aims to improve capacity and efficiency through reducing the distance between trains and enhancing communication systems. The implementation of a Solid-State LIDAR based sensing system, coupled with IoT edge hardware and fuzzy clustering approach, has been tested in a real railway scenario to support accurate distance detection and virtual coupling maneuvers.
Article
Computer Science, Information Systems
Cristian Wisultschew, Gabriel Mujica, Jose Manuel Lanza-Gutierrez, Jorge Portilla
Summary: This paper proposes an edge IoT hardware platform implementation for detecting and tracking objects in a railway level crossing scenario, utilizing a low-resolution 3D 16-channel LIDAR as the sensor. The processing element of the system is located as close as possible to the sensor to improve latency, privacy, and avoid bandwidth limitations. A lightweight object detection and tracking algorithm is introduced to handle the large amount of information provided by the LIDAR, enabling real-time specifications to be met.
Article
Computer Science, Information Systems
Rafael Zamacola, Andres Otero, Alberto Garcia, Eduardo De La Torre