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Article
Computer Science, Information Systems
Farhan Amin et al.
Summary: This paper discusses the application of graph signal processing in large-scale data analysis. It provides an overview of the core ideas in GSP and their connection to conventional DSP. Recent developments in basic GSP tools, such as graph filtering and graph learning, are summarized. The effectiveness of graph filtering in big data analytics is demonstrated through example application.
CMC-COMPUTERS MATERIALS & CONTINUA
(2023)
Article
Telecommunications
Muhammad Diyan et al.
Summary: The increasing demand for electrical energy, smart grid, and renewable energy has created opportunities for Electrical Energy Data Management and Processing Systems (EEDMS). However, implementing and maintaining EEDMS is a challenging task, and the heterogeneous energy data generated from residential and commercial sectors pose challenges for standard IoT architecture. In order to overcome these challenges, a scalable multitasking IoT gateway (IoTGW) is proposed, along with a Data Loading and Storing Module (DLSM) that enables a high dynamic distributed framework.
TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES
(2022)
Article
Computer Science, Information Systems
Zhidu Li et al.
Summary: A recommendation-aided edge caching approach is proposed to leverage the time-varying user interest and improve the quality of data services for the Industrial Internet. By dynamically capturing user interests, determining content caching strategies, and optimizing cache hit ratio, this approach aims to provide personalized user experiences.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Ahmed Imteaj et al.
Summary: This article investigates the methods and challenges of training distributed machine learning models in resource-constrained IoT environments, discusses the limitations of existing research, and identifies future research directions.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Yulei Wu et al.
Summary: The Industrial Internet of Things (IIoT) is crucial for the digital transformation of traditional industries towards Industry 4.0. Graph neural networks (GNNs) have shown promise in anomaly detection in IIoT-enabled smart transportation, smart energy, and smart factory. This article provides valuable insights and case studies in utilizing GNNs for anomaly detection in IIoT.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Hardware & Architecture
Jianxiong Guo et al.
Summary: Real-time traffic monitoring is essential in smart cities for understanding traffic conditions and preventing accidents. This article proposes a reliable and efficient traffic monitoring system that integrates blockchain and IoT technologies, crowdsourcing tasks to vehicles. The system includes a lightweight blockchain-based information trading framework and auction mechanism to incentivize vehicle participation and ensure budget constraints. Numerical simulations confirm the reliability and efficiency of the framework and algorithms.
IEEE TRANSACTIONS ON RELIABILITY
(2022)
Article
Chemistry, Analytical
Tung M. Luu et al.
Summary: In this study, a visual pretraining via contrastive predictive model (VPCPM) framework is proposed to overcome the limitations of reward-driven representation learning in vision-based reinforcement learning (RL). By training the convolutional encoder with the supervision of contrastive loss, better representations are learned by perceiving the underlying dynamics through a pair of forward and inverse models. Experimental results show that by initializing the encoders with VPCPM, the performance of state-of-the-art vision-based RL algorithms is significantly improved, surpassing or matching the performance of prior unsupervised methods. The learned representations also generalize successfully to new tasks with similar observation and action spaces.
Review
Computer Science, Information Systems
Jamal Bzai et al.
Summary: This paper classifies and discusses the integration of machine learning and the Internet of Things (IoT) from the perspectives of data, application, and industry. It elaborates on various methods and applications, as well as emerging IoT trends and challenges. The paper emphasizes the importance of machine learning in IoT and explores its positive impact on societal development.
Article
Computer Science, Information Systems
Farhan Amin et al.
Summary: The Internet of Things has the potential to be applied to social networks due to innovative characteristics and solutions. Social network analysis has gained scientific attention and offers revolutionary theories in interconnected networks. This study aims to understand and capture clustering properties in large networks and social networks, proposing a network growth model and a scale-free artificial social network with controllable clustering coefficients.
CMC-COMPUTERS MATERIALS & CONTINUA
(2022)
Proceedings Paper
Computer Science, Theory & Methods
Roman Karlstetter et al.
Summary: Sensor data plays a crucial role in IoT scenarios for online monitoring and long-term data analytics. Summarizing multivariate sensor time series data in windowed aggregations at different resolutions can improve data efficiency. Although different nodes in the edge-to-cloud continuum may have different views on the data, users expect fast response and a unified view regardless of where the query is sent and where the data is stored.
2022 IEEE INTERNATIONAL CONFERENCE ON EDGE COMPUTING & COMMUNICATIONS (IEEE EDGE 2022)
(2022)
Article
Computer Science, Information Systems
Farhan Amin et al.
Summary: The social internet of things (SIoT) is an emerging paradigm that aims to solve the problems of network service discovery, navigability, and service composition by socializing IoT devices and shaping their interconnection into social interactions. We propose an efficient automated query-based service search model based on the local network navigability concept for the SIoT, which leverages social relationships between objects for service discovery.
CMC-COMPUTERS MATERIALS & CONTINUA
(2022)
Review
Engineering, Multidisciplinary
Abid Ali et al.
Summary: The research aims to propose a secure framework for the Internet of Things (IoT) by conducting a systematic literature review. A qualitative model is generated based on the analysis of a large number of articles and reports, providing guidance for IT managers, developers, and IoT users.
Article
Computer Science, Information Systems
Farhan Amin et al.
Summary: This article provides a systematic survey of the most recent studies on the social Internet of things (SIoT), focusing on key aspects such as service composition and discovery, network navigability, architecture and components, platform and tools, and relationship and trust management. It also discusses emerging research areas in network navigability and SIoT datasets. Furthermore, it demonstrates the integration of SIoT with other emerging technologies like IoT, big data, cloud computing, and social network. The article aims to offer comprehensive knowledge about SIoT from multiple perspectives.
Article
Telecommunications
Jianxiong Guo et al.
Summary: With the development of smart cities, a large distributed network has been formed between cities, which raises the challenge of secure and efficient energy trading. In this paper, a blockchain-based multiple energies trading system is proposed, using a smart contract and a new byzantine-based consensus mechanism. The model and algorithms are validated using numerical simulations, demonstrating their correctness and efficiency.
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING
(2022)
Review
Computer Science, Information Systems
Iqbal H. Sarker
Summary: Cities are going through significant technological and operational changes, with data science driving the Fourth Industrial Revolution. Extracting valuable knowledge and insights from city data and building data-driven models are crucial for automating and enhancing city systems. Artificial intelligence, particularly machine learning, plays a vital role in providing deeper understanding of city data and enabling intelligent city services.
INTERNET OF THINGS
(2022)
Article
Computer Science, Information Systems
Gabriel Borrageiro et al.
Summary: We demonstrate the novel application of online transfer learning in digital assets trading and prove the effectiveness of this approach through experiments. Our crypto agent performs well in market prediction and trading, achieving significant returns.
Article
Engineering, Electrical & Electronic
Rana M. Abdul Haseeb-Ur-Rehman et al.
Summary: This article investigates the latest sensor cloud integration frameworks to address challenges in integrating WSN with the cloud. It presents a detailed thematic taxonomy, focusing on service-oriented and client-server architectures. Through qualitative analysis, it examines the relevant features and key aspects of existing frameworks.
IEEE SENSORS JOURNAL
(2021)
Editorial Material
Automation & Control Systems
Francesco Piccialli et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Computer Science, Information Systems
Phoebe Edward et al.
Summary: LoRa technology, based on chirp spread spectrum modulation, has introduced ICS-LoRa modulation to enhance network capacity. Research shows that ICS-LoRa can co-exist and collaborate with standard LoRa networks, providing a capacity gain of approximately 42%.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Automation & Control Systems
Yachuang Feng et al.
Summary: Person reidentification aims to match individuals across multiple camera views, with metric learning-based methods playing important roles but often relying on supervised manners with manual annotations. This paper proposes an unsupervised cross-view metric learning method based on the properties of data distributions, which can extract both shared and view-specific features to improve the accuracy of person reidentification. The experimental results on five cross-view datasets validate the effectiveness of the proposed method.
IEEE TRANSACTIONS ON CYBERNETICS
(2021)
Article
Computer Science, Information Systems
Sisay Tadesse Arzo et al.
Summary: The introduction of IoT and massive machine-type communications has led to an increase in network size and complexity, overwhelming network administrators in designing and managing such networks. Network automation promises to reduce costs by allowing networks to manage themselves. Standardization organizations, such as ETSI, are leading efforts in introducing network automation to improve network management efficiency.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Ghulam Muhammad et al.
Summary: The integration of artificial intelligence (AI) and the Internet of Things (IoT) has great potential in smart healthcare, especially post-COVID-19. A voice pathology detection system within a smart healthcare framework is proposed, utilizing deep learning and neural networks technology to improve accuracy by obtaining signals through microphones and electroglottography devices.
Article
Computer Science, Hardware & Architecture
Shaohuai Shi et al.
Summary: This article presents a quantitative survey of communication optimization techniques for data parallel distributed deep learning, identifying major challenges and classifying solutions at different levels. A comparative study of seven common methods on a 32-GPU cluster with 100Gb/s InfiniBand reveals the difficulties in scaling DL models with low model intensity, and highlights the critical impact of system architecture and scheduling algorithms on performance. Discussions on open issues for further investigation are also provided.
Proceedings Paper
Materials Science, Multidisciplinary
Sufiyan Sajid et al.
Summary: With the evolution of industries towards Industry 4.0, machines have become more complex and require data science techniques and experts for predictive maintenance to reduce failures and quality deviations, thus improving production efficiency and reliability.
MATERIALS TODAY-PROCEEDINGS
(2021)
Article
Computer Science, Information Systems
Xiping Wu et al.
Summary: HLWNets, a combination of LiFi and WiFi networks, offer high-speed data transmission and ubiquitous coverage. The article presents the system design framework, performance metrics, achievements, challenges, and potential applications of HLWNets.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2021)
Article
Computer Science, Information Systems
Akram A. Almohammedi et al.
Summary: This paper focuses on the performance analysis of a steganographic scheme using a 2-D Markov chain model, specifically looking at the WiPad method in relation to the IEEE 802.11p standard. The study considers factors such as wireless padding, non-saturated conditions, and network parameters in modeling the system throughput of the steganographic channel.
Editorial Material
Engineering, Electrical & Electronic
Irena Atov et al.
IEEE COMMUNICATIONS MAGAZINE
(2020)
Article
Chemistry, Analytical
Prince Waqas Khan et al.
Editorial Material
Computer Science, Information Systems
Francesco Piccialli et al.
IEEE INTERNET OF THINGS JOURNAL
(2020)
Review
Computer Science, Cybernetics
Rijk Mercuur et al.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2020)
Article
Computer Science, Information Systems
Julian Eduardo Plazas et al.
IEEE INTERNET OF THINGS JOURNAL
(2020)
Article
Computer Science, Information Systems
Rafael de Amorim Silva et al.
IEEE INTERNET OF THINGS JOURNAL
(2020)
Review
Computer Science, Information Systems
Bhabendu Kumar Mohanta et al.
INTERNET OF THINGS
(2020)
Article
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Farhan Amin et al.
Article
Computer Science, Information Systems
Li Li et al.
Article
Computer Science, Information Systems
Yuanzhao Gao et al.
Review
Computer Science, Information Systems
Zahrah A. Almusaylim et al.
Article
Chemistry, Analytical
Farhan Amin et al.
Article
Computer Science, Information Systems
Karen R. Sollins
IEEE INTERNET OF THINGS JOURNAL
(2019)
Article
Computer Science, Information Systems
Stephen D. Liang
IEEE INTERNET OF THINGS JOURNAL
(2019)
Review
Chemistry, Multidisciplinary
Farhan Amin et al.
APPLIED SCIENCES-BASEL
(2019)
Review
Computer Science, Information Systems
Venketesh Palanisamy et al.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2019)
Article
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Nadia Chaabouni et al.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2019)
Article
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Mehdi Mohammadi et al.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2018)
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Rajiv Ranjan et al.
IEEE CLOUD COMPUTING
(2018)
Article
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IEEE SENSORS JOURNAL
(2018)
Review
Computer Science, Artificial Intelligence
Ashish Ghosh et al.
CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY
(2018)
Proceedings Paper
Computer Science, Theory & Methods
Zainab Alansari et al.
EMERGING TECHNOLOGIES IN COMPUTING, ICETIC 2018
(2018)
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Igor Kotenko et al.
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Mohsen Marjani et al.
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Komal Batool et al.
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(2017)
Proceedings Paper
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Harald Foidl et al.
LEVERAGING APPLICATIONS OF FORMAL METHODS, VERIFICATION AND VALIDATION: DISCUSSION, DISSEMINATION, APPLICATIONS, ISOLA 2016, PT II
(2016)
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Maria Rita Palattella et al.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2013)
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Luigi Atzori et al.
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J.L. Cole
