Article
Engineering, Civil
Deepak Saluja, Rohit Singh, Nitin Saluja, Suman Kumar
Summary: This paper proposes a novel scheme to improve the connectivity of mobile vehicular networks by using a hybrid mmWave and microwave scheme at the medium access control (MAC) layer. A computational model is derived to evaluate the connectivity for the proposed scheme and compared with existing schemes. The analysis shows that the proposed hybrid scheme significantly improves the connectivity performance in mobile vehicular networks and provides parameter analysis for practical implementation in 5G/6G technologies.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Xincheng Li, Xinchun Yin, Jianting Ning
Summary: In this paper, a secure and trustworthy announcement dissemination scheme is proposed for location-based service (LBS) application in Vehicular ad hoc network (VANET). The scheme utilizes blockchain and smart contract technologies to generate and disseminate traffic-related messages in VANET, and vehicles generate trustworthy announcements with the help of neighbor vehicles. Experimental results demonstrate the robustness and efficiency of the proposed scheme.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Hardware & Architecture
Abhilasha Sharma, Lalit Kumar Awasthi
Summary: With the increase in urban traffic density, the accident rate and its consequences have become a serious problem. Sharing real-time event information among vehicles can minimize the accident rate. However, due to the unique characteristics of vehicles, disseminating real-time event information through a reliable path is challenging. To address this issue, a Software Defined Network (SDN) based vehicular network model and a heuristic based reliable path selection (HRPS) algorithm have been proposed. These ensure real-time dissemination of event information in urban environments and minimize the impact of dynamic obstacles.
Article
Physics, Multidisciplinary
Yuan-Hao Xu, Hao-Jie Wang, Zhong-Wen Lu, Mao-Bin Hu
Summary: This paper presents a coupled epidemic-awareness-mobility model on multiplex networks, incorporating the dissemination of awareness through information links and the spread of epidemics through human mobility. The results show that information dissemination greatly affects the epidemic threshold and the final recovery density. The study also highlights the role of hub nodes and the impact of information transmission rate and mobility rate on epidemic containment.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2023)
Article
Engineering, Civil
Mi Yang, Bo Ai, Ruisi He, Chao Shen, Miaowen Wen, Chen Huang, Jianzhi Li, Zhangfeng Ma, Liang Chen, Xue Li, Zhangdui Zhong
Summary: Scenario identification is crucial in maintaining effective and reliable operation of vehicular communications. This paper introduces a machine-learning-based scenario identification model for intelligent vehicular communications, achieving high accuracy in identifying typical scenarios such as urban areas, highways, tunnels, and vehicle obstructions.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Engineering, Civil
Amritpal Singh, Gagangeet Singh Aujla, Rasmeet Singh Bali
Summary: With the increasing demand for online services and multimedia applications, the traffic on the underlying network infrastructure has significantly increased. Software-defined Networking (SDN) offers flexible network control to meet strict latency requirements. Intent-based network has emerged as a new solution to bridge the gap between business needs and network delivery potential.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Computer Science, Information Systems
Xuefei Zhang, Wenbo Xia, Xiaochen Wang, Junjie Liu, Qimei Cui, Xiaofeng Tao, Ren Ping Liu
Summary: This article investigates the impact of mobility on block propagation in vehicular ad hoc networks (VANETs) and analyzes the single-block propagation time and multiblock competitive propagation time. The research findings show that higher mobility and more moving vehicles can speed up block propagation, and the propagation capabilities of moving nodes contribute to the reduction of forking in blockchain consensus.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Telecommunications
Hussein Al-Omaisi, Elankovan A. Sundararajan, Raed Alsaqour, Nor Fadzilah Abdullah, Maha Abdelhaq
Summary: VANETs, as a leading technology in intelligent transportation systems for data dissemination, face challenges in high dynamics, prompting the introduction of the promising V-NDN model. The comprehensive survey in this article introduces V-NDN data dissemination solutions, a new taxonomy, qualitative comparison, and unified performance evaluation metrics, aiming to address open problems and guide future-oriented solutions.
VEHICULAR COMMUNICATIONS
(2021)
Article
Computer Science, Hardware & Architecture
Guangbing Xiao, Haibo Zhang, Zhiyi Huang, Yawen Chen
Summary: This paper proposes a decentralized cooperative broadcasting protocol for Vehicle-to-Vehicle (V2V) communication, which allows vehicles to piggyback received messages in their routine broadcasts to help others recover lost traffic information. By introducing a bitmap data structure to record the receiving status of each vehicle, the protocol enables efficient detection of lost messages, estimation of wireless link quality, and achieves high reliability in message delivery.
Article
Engineering, Electrical & Electronic
Zhirui Liang, Robert Mieth, Yury Dvorkin
Summary: This paper proposes a modified cGAN model to generate statistically credible net load scenarios for power systems, conditioned by given labels (e.g., seasons), that are stressful to system operations and dispatch decisions. The proposed OA-cGAN internalizes a DC optimal power flow model and seeks to maximize operating cost by generating worst-case data. The model is trained and tested using historical net load forecast errors.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Computer Science, Information Systems
Amit Kumar Goyal, Gaurav Agarwal, Arun Kumar Tripathi, Vikas Goel, Girish Sharma, Kueh Lee Hui, Mangal Sain
Summary: VANET, a subclass of MANET, provides reliable and low-cost solutions for transportation systems in areas such as traffic management and safety. This paper focuses on the security and cost of intra domain mobility handoff in VANET, introducing authentication costs to evaluate total packet delivery costs. The proposed scheme aims to secure handover processes with slight cost variations.
Article
Automation & Control Systems
Yubin Wang, Yixian Liu, Qiang Yang
Summary: This article develops a generation and forecasting approach using Wasserstein generative adversarial network (WGAN) for the characterization of operational uncertainties in integrated energy systems (IES). The proposed solution efficiently generates high-quality IES operational scenarios without explicit statistical assumptions, and can be integrated into a constrained optimization problem for scenario forecasting.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Information Systems
Yang Yang, Haiyan Liu, Jianlin Zhou
Summary: In the COVID-19 pandemic, information dissemination and epidemic transmission on social networking platforms interact with each other. Controlling the information dissemination rate, epidemic recovery rate, and the probability of individuals taking preventive behaviors can suppress the spread of the epidemic.
CMC-COMPUTERS MATERIALS & CONTINUA
(2021)
Article
Engineering, Electrical & Electronic
Zipeng Li, Lin Xiang, Xiaohu Ge
Summary: This paper discusses real-time information dissemination based on the Age of Information in vehicular social networks, proposing a mathematical framework and conducting joint optimization, with results showing that the new scheme can significantly reduce the average peak NAoI by up to 96%.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Multidisciplinary Sciences
Yafei Zhang, Lin Wang, Jonathan J. H. Zhu, Xiaofan Wang
Summary: This research shows that the spatial dissemination of COVID-19 can be explained by a local diffusion process in the mobility network, indicating the effectiveness of disease prevention and control measures. It also highlights the potential social consequences of COVID-19 outbreaks in different areas. During the epidemic control period, there were significant reductions in human mobility and changes in the structure of the mobility network to contain the spread of the virus.
JOURNAL OF THE ROYAL SOCIETY INTERFACE
(2022)
Article
Computer Science, Information Systems
Pau Ferrer-Cid, Jose M. Barcelo-Ordinas, Jorge Garcia-Vidal
Summary: The article compares two techniques based on structured data, one based on statistical methods and the other on signal smoothness, as well as a baseline technique that does not rely on measured signal data. The results show that the signal smoothness-based technique performs better than the other two on datasets measuring O-3, NO2, and PM10, and when used together with Laplacian interpolation, it is near optimal compared to linear regression. Additionally, in heterogeneous networks, the reconstruction accuracy is similar to in-situ calibrated sensors, increasing the robustness of the network against sensor failures.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Multidisciplinary Sciences
Jose M. Barcelo-Ordinas, Pau Ferrer-Cid, Jorge Garcia-Vidal, Mar Viana, Ana Ripoll
Summary: The H2020 CAPTOR project deployed three testbeds in Spain, Italy, and Austria with low-cost sensors for measuring tropospheric ozone. The project aimed to raise public awareness through citizen science. Each testbed was supported by an NGO to decide on awareness-raising strategies based on country-specific needs.
Article
Computer Science, Hardware & Architecture
Pau Ferrer-Cid, Jose M. Barcelo-Ordinas, Jorge Garcia-Vidal
Summary: This study proposes a graph-based data reconstruction framework for post-processing applications in low-cost air pollution sensor networks. The results demonstrate that this framework outperforms traditional methods in missing value imputation, signal reconstruction, and data fusion.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2022)
Article
Chemistry, Analytical
Pau Ferrer-Cid, Julio Garcia-Calvete, Aina Main-Nadal, Zhe Ye, Jose M. Barcelo-Ordinas, Jorge Garcia-Vidal
Summary: The use of low-cost sensors in conjunction with high-precision instrumentation for air pollution monitoring has shown promising results in recent years. However, the quality of the data collected by these sensors has been a major challenge. This paper explores the trade-offs between sensor sampling, calibration quality, and power consumption, and finds that the sampling strategy directly affects the estimation of air pollution quality.
Article
Engineering, Multidisciplinary
Pau Ferrer-Cid, Jose M. Barcelo-Ordinas, Jorge Garcia-Vidal
Summary: The presence of low-cost sensors in sensor networks highlights the importance of detecting and localizing outliers. Researchers propose a Volterra graph-based outlier detection mechanism, which successfully identifies and locates abnormal measurements in air pollution sensor networks using graph signal processing techniques.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2022)
Article
Environmental Sciences
J. Rovira, J. A. Paredes-Ahumada, J. M. Barcelo-Ordinas, J. Garcia-Vidal, C. Reche, Y. Sola, P. L. Fung, T. Petaja, T. Hussein, M. Viana
Summary: This study proposes a machine learning approach to develop a black carbon (BC) proxy using air pollution datasets as input. The results show that the proposed BC proxy, based on support vector regression (SVR) and random forest (RF), demonstrates a high degree of correlation and low error in estimating BC concentrations. The performance of the model varies depending on seasonality and time of day, with new particle formation events impacting model accuracy. The study concludes that the model can serve as a BC proxy, especially in environments where traffic is the main source of ultrafine particles.
ENVIRONMENTAL RESEARCH
(2022)
Article
Chemistry, Analytical
Emiliano Lopez, Carlos Vionnet, Pau Ferrer-Cid, Jose M. Barcelo-Ordinas, Jorge Garcia-Vidal, Guillermo Contini, Jorge Prodolliet, Jose Maiztegui
Summary: This paper describes the design of a datalogger device based on open-source hardware platforms to measure water table levels and soil moisture data. Open-source IoT hardware platforms are emerging as an attractive alternative to commercial instruments, offering flexibility and low cost.
Article
Engineering, Electrical & Electronic
Xhensilda Allka, Pau Ferrer-Cid, Jose M. M. Barcelo-Ordinas, Jorge Garcia-Vidal
Summary: In this article, two algorithms are proposed to denoise and calibrate low-cost sensors used in IoT monitoring platforms. The first method, TPB-D, achieves signal denoising by projecting the daily signals of the sensor onto a subspace generated by reference instruments. The second method, TPB-C, corrects and calibrates the daily sensor signals by linear mapping with regularization based on the subspace produced by the reference database.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Computer Science, Information Systems
Gabriel O. Ferreira, Chiara Ravazzi, Fabrizio Dabbene, Giuseppe C. Calafiore, Marco Fiore
Summary: This paper reviews the literature on network traffic prediction and serves as a tutorial on the topic. It analyzes works based on autoregressive moving average models and artificial neural networks approaches. The paper provides a complete presentation of the mathematical foundations of each technique and performs numerical experiments based on real data sets to compare the different approaches. The code is also made publicly available for readers to access a wide range of forecasting tools.
Article
Computer Science, Information Systems
Chuanhao Sun, Kai Xu, Marco Fiore, Mahesh K. Marina, Yue Wang, Cezary Ziemlicki
Summary: This article introduces a model called APPSHOT that generates high-fidelity city-scale snapshots of service-level mobile traffic. Based on the original characterization of service-level mobile traffic data, APPSHOT employs a conditional generative adversarial network design and other innovative mechanisms. Experiments show that APPSHOT can generate realistic service-level network loads and supports service-oriented networking studies.
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
(2022)
Article
Computer Science, Information Systems
Stefanos Bakirtzis, Kehai Qiu, Ian Wassell, Marco Fiore, Jie Zhang
Summary: The topic of indoor outdoor detection (IOD) is gaining popularity. Existing models have limitations in scalability and accuracy. This article proposes treating IOD as a multivariate time-series classification problem and explores the performance of deep learning models. A new DL model is introduced that outperforms existing models in accuracy and computational cost.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Pau Ferrer-Cid, Jose M. Barcelo-Ordinas, Jorge Garcia-Vidal
Summary: Air pollution monitoring platforms are crucial in preventing and mitigating pollution. Recent advances in graph signal processing allow for the description and analysis of air pollution monitoring networks through graphs. This article proposes a signal reconstruction framework for air pollution data and compares different methods on actual datasets. The results show the superiority of kernel-based graph signal reconstruction methods, as well as the challenges in scaling with a large number of low-cost sensors in the monitoring network.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Multidisciplinary Sciences
Pau Ferrer-Cid, Jose M. Barcelo-Ordinas, Jorge Garcia-Vidal
Summary: Recently, there has been increasing research on monitoring air pollution using low-cost sensors and improving sensor data quality through machine learning techniques. This paper presents a dataset from two self-built low-cost air pollution nodes deployed at an official air quality reference station in Barcelona, Spain. The dataset includes four months of data from five electrochemical sensors as well as temperature and relative humidity data. The availability of high-resolution sensor time series is crucial for analyzing sensor sampling strategies, signal filtering, and calibration of low-cost sensors.
Article
Computer Science, Information Systems
Panagiota Katsikouli, Diego Madariaga, Aline Carneiro Viana, Alberto Tarable, Marco Fiore
Summary: Mobile device tracking technologies based on various positioning systems have made location data collection ubiquitous. In this paper, we propose DUCTI LOC, a location sampling mechanism that profiles users and adaptively adjusts the position tracking frequency to their mobility. DUCTI LOC is energy efficient and provides a control knob to balance accuracy and energy usage.
Article
Multidisciplinary Sciences
Inaki Ucar, Marco Gramaglia, Marco Fiore, Zbigniew Smoreda, Esteban Moro
Summary: This study investigates the digital usage gap using a dataset of 3.7 billion mobile traffic records in a major European country. It reveals significant geographical unevenness in mobile service usage, especially in news, social media, and video streaming, and links this diversity with income, educational attainment, and inequality. The results suggest that the socio-economic status of an area can be accurately inferred from aggregated data traffic, highlighting the importance of understanding the digital usage divide for socio-economic issues.
JOURNAL OF THE ROYAL SOCIETY INTERFACE
(2021)
