Article
Construction & Building Technology
Xiaopeng Zhu, Yuanyuan Zhu, Lei Li, Sian Pan, Muhammad Usman Tariq, Mian Ahmad Jan
Summary: The widespread use of sensor-based applications in healthcare has led to the development of Internet of Health Things (IoHT) that improves patient safety, staff morale, and operational efficiency. Edge-fog computing has made significant progress recently, but still faces challenges in handling various IoHT settings. The proposed edge-fog computing framework efficiently manages real-time data related to glioma and automatic detection of diseases related to glial cells surrounding nerve cells.
SUSTAINABLE CITIES AND SOCIETY
(2021)
Article
Computer Science, Hardware & Architecture
Bassem Sellami, Akram Hakiri, Sadok Ben Yahia, Pascal Berthou
Summary: This paper introduces energy-aware and low-latency computing task scheduling algorithms for a Software-Defined Fog-IoT Network. By using deep reinforcement learning techniques, the proposed algorithms optimize task assignment and scheduling, achieving better energy efficiency and reducing end-to-end latency. Extensive experiments and simulations show that the proposed solution outperforms other deep learning algorithms, saving up to 87% energy compared to other approaches and reducing task assignment time delay by up to 50%.
Article
Computer Science, Theory & Methods
Bassem Sellami, Akram Hakiri, Sadok Ben Yahia
Summary: IoT edge technology provides cloud computing services for topology and location-sensitive distributed computing, but faces challenges such as security issues, energy consumption, and instability due to service decentralization. This paper introduces a novel Blockchain-based Deep Reinforcement Learning approach to address energy-aware task scheduling and offloading in IoT networks.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Computer Science, Information Systems
Prithi Samuel, Arumugham Vinothini, Jayashree Kanniappan
Summary: The increasing number of IoT devices presents challenges for communication. Traditional cloud computing model is not efficient for IoT tasks due to latency. This study proposes using mobile edge computing and fog concept to process IoT tasks independently. The POA-A1DCNN-LSTM algorithm is utilized to optimize energy consumption and task delay, improving the total utility of MEC servers.
COMPUTER COMMUNICATIONS
(2023)
Article
Computer Science, Hardware & Architecture
Shabnam Shadroo, Amir Masoud Rahmani, Ali Rezaee
Summary: This article discusses the inefficiency of cloud-based infrastructure in meeting the needs of IoT and introduces a two-phase scheduling algorithm based on deep learning. The algorithm shows that feature extraction using deep learning can improve clustering, reducing the missed rate of tasks and costs in the cloud and fog.
Review
Computer Science, Information Systems
Zahra Jalali Khalil Abadi, Najme Mansouri, Mahshid Khalouie
Summary: Despite its advantages, cloud computing can be a poor choice due to slow response times, leading to the need for fog computing. Scheduling tasks in a fog environment presents a major challenge, as IoT clients require timely execution, lower-cost services, and secure operations. This paper reviews scheduling algorithms proposed by various researchers in fog environments, compares simulation tools for developers, and discusses open issues and future research directions.
COMPUTER SCIENCE REVIEW
(2023)
Article
Chemistry, Analytical
JongBeom Lim
Summary: Internet of Things applications are popular due to their lightweight nature and usefulness. This paper proposes a latency-aware task scheduling method based on artificial intelligence in small-scale fog computing environments, which reduces latency and improves efficiency.
Review
Computer Science, Theory & Methods
Bushra Jamil, Humaira Ijaz, Mohammad Shojafar, Kashif Munir, Rajkumar Buyya
Summary: This article focuses on the task scheduling problem in the resource-limited, heterogeneous, dynamic, and uncertain fog computing environment. The article presents a systematic, comprehensive, and detailed approach by comparing different scheduling algorithms, optimization metrics, and evaluation tools. The goals of this survey article include reviewing the fog computing and IoE paradigms, delineating the optimization metric, reviewing, classifying, and comparing existing scheduling algorithms, rationalizing the scheduling algorithms, and discussing future research directions.
ACM COMPUTING SURVEYS
(2022)
Article
Computer Science, Information Systems
Hamza Baniata, Ahmad Anaqreh, Attila Kertesz
Summary: Cloud Computing (CC) deployment has become popular across various fields, and task scheduling in complex scenarios like smart cities is challenging, where Blockchain and Ant Colony Optimization can improve efficiency. Fog Computing further enhances task execution, while ensuring privacy of system components.
INFORMATION PROCESSING & MANAGEMENT
(2021)
Article
Computer Science, Hardware & Architecture
Posham Bhargava Reddy, Chapram Sudhakar
Summary: The edge-fog-cloud computing system consists of three layers: edge or IoT layer, fog layer, and cloud layer. Tasks with different characteristics can be scheduled to run at the appropriate layer based on their computation or communication demands. A scheduling algorithm based on the osmotic approach is proposed to minimize execution time, meet task deadlines, and maximize resource utilization at the fog layer. The algorithm outperforms traditional random and round-robin task offloading algorithms in terms of performance.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Computer Science, Information Systems
Eyhab Al-Masri, Alireza Souri, Habiba Mohamed, Wenjun Yang, James Olmsted, Olivera Kotevska
Summary: This article proposes a cooperative energy-aware resource allocation and scheduling strategy based on the TOPSIS multi-criteria decision-making method. The method achieves load balancing by allocating and scheduling virtual machine resources and considers energy efficiency as an optimization objective. Experimental results show that the proposed approach outperforms existing algorithms in terms of energy savings and execution time.
INTERNET OF THINGS
(2023)
Article
Computer Science, Information Systems
Rishika Mehta, Jyoti Sahni, Kavita Khanna
Summary: Fog integrated Cloud Computing is a distributed computing paradigm where fog nodes and cloud resources cooperate to provide computational and storage services. Task scheduling is a challenging issue in fog integrated cloud systems. This work proposes a decentralized heuristic algorithm for scheduling real-time IoT applications with tolerable latency constraints. Performance evaluation shows that the algorithm improves response time by 11% on average compared to other state-of-the-art policies.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Review
Computer Science, Theory & Methods
Raj Mohan Singh, Lalit Kumar Awasthi, Geeta Sikka
Summary: This study provides a comprehensive taxonomic review and analysis of recent metaheuristic scheduling techniques in cloud and fog environments. It includes evaluation criteria, scheduling objectives, a taxonomy of scheduling algorithms, and rigorous evaluation of existing literature. The study also focuses on the performance of hybrid algorithms.
ACM COMPUTING SURVEYS
(2023)
Article
Automation & Control Systems
Lokman Altin, Haluk Rahmi Topcuoglu, Fikret Sadik Gurgen
Summary: This study presents a multi-objective task scheduling model and algorithm for fog computing, incorporating two task clustering mechanisms to reduce data transfer costs. Empirical evaluations validate the effectiveness of the proposed algorithm and the importance of the integrated extensions.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Telecommunications
Naseem Adnan Alsamarai, Osman Nuri Ucan, Oras Fadhil Khalaf
Summary: With the increasing number of IoT devices and the massive amounts of data generated every minute, some IoT applications require real-time services and low latency to meet the term 'Data Never Sleeps.' Cisco has proposed fog computing as an expansion of cloud computing to provide processing, storage, and services with minimum delays. This study presents a novel task scheduling algorithm, called the bandwidth-deadline algorithm, that focuses on the makespan and tasks' deadline satisfaction time. Experimental results show that our algorithm outperforms current algorithms in terms of makespan and deadline satisfaction.
WIRELESS PERSONAL COMMUNICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
V. D. Ambeth Kumar, S. Sharmila, Abhishek Kumar, A. K. Bashir, Mamoon Rashid, Sachin Kumar Gupta, Waleed S. Alnumay
Summary: Postpartum haemorrhage (PPH) is a significant and potentially fatal complication of childbirth worldwide. This research proposes an automation system using wearable devices to predict the risk of PPH in pregnant women by measuring various parameters. Based on the predicted risk, medical attention is provided through an Internet of Things infrastructure.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Moinak Maiti, Uttam Ghosh
Summary: The present study evaluates the current status of the Internet of Things (IoT) in fintech ecology comprehensively. It finds that while the concept of communication between devices and financial technology is not new, limited research has been conducted on IoT in fintech. The study also identifies that the increasing demand for blockchain, internet, mobile network, cloud storage, and IoT devices among organizations is driving the development of IoT in fintech.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Chemistry, Multidisciplinary
Uttam Ghosh, Vikash Kumar, Gajendra Singh, Tushar Kanti Chakraborty
Summary: In order to find more effective and safer anticoagulants, researchers used in silico structure-based design to discover new peptide-based thrombin inhibitors. The study demonstrated that tetrahydrofuran amino acid (TAA) based cyclic tetrapeptides (CTPs) can inhibit thrombin protein by interacting with Asp189 residue. This research synthesized and analyzed the conformation of TAA containing cyclic tetrapeptides, and studied their docking with thrombin protein using molecular docking.
Article
Green & Sustainable Science & Technology
Sanjoy Choudhury, Ashish Kumar Luhach, Joel J. P. C. Rodrigues, Mohammed AL-Numay, Uttam Ghosh, Diptendu Sinha Roy
Summary: Energy efficient ICT infrastructure is crucial for sustainable development in smart cities. This research tackles the virtual machine (VM) placement problem using a genetic algorithm (GA) to optimize data center efficiency and reduce energy usage and maintenance time.
Article
Computer Science, Information Systems
Debashis Das, Sourav Banerjee, Pushpita Chatterjee, Uttam Ghosh, Utpal Biswas
Summary: Blockchain technology has the potential to enhance the security and interoperability of intelligent transportation systems (ITSs). It can be applied to data exchange and smart contracts, but it also faces challenges such as scalability and computational power requirements.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Engineering, Multidisciplinary
Senthil Murugan Nagarajan, Ganesh Gopal Devarajan, Amin Salih Mohammed, T. V. Ramana, Uttam Ghosh
Summary: This paper proposes an IoT-based healthcare cyber-physical system that achieves maximum task execution and minimum execution cost through efficient resource utilization and cost-effective task scheduling at the fog and cloud levels. By considering data from social media networking and drug reviews for analysis and applying different feature extraction methods, the system outperforms existing techniques and algorithms in terms of performance.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Article
Engineering, Multidisciplinary
Li Zhang, Jianbo Xu, Pandi Vijayakumar, Pradip Kumar Sharma, Uttam Ghosh
Summary: This work introduces the federated learning mechanism into deep learning of medical models in IoT-based healthcare systems, with the application of cryptographic primitives to protect local models and prevent inference of private medical data. The quality of datasets owned by different participants is considered as the main factor for measuring the contribution rate of local model to the global model, rather than the size of datasets commonly used in deep learning.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Manash Kumar Mondal, Riman Mandal, Sourav Banerjee, Monali Sanyal, Uttam Ghosh, Utpal Biswas
Summary: Real-time monitoring using camera-trapping technology is important in saving endangered wildlife. This article focuses on the design and development of a fog-assisted tiger alarming framework that detects tigers in the corridor and delivers systematic alerts to villagers, reducing the conflict between humans and tigers. The proposed fog-based model successfully reduces latency and network usage compared to the traditional cloud-based model.
Article
Chemistry, Organic
Vipin Kumar Singh, Uttam Ghosh, Tushar Kanti Chakraborty
Summary: The structural motif of an indole-fused azabicyclo[3.3.1]nonane is commonly found in biologically significant indole-based natural products. A radical-based strategy was successfully employed to construct this complex ring system, utilizing a SmI2-mediated radical cyclization protocol. The modular approach developed in this study can be further expanded to synthesize various alkaloids with desired functionalities on the indole-fused N-bridged ring system.
ORGANIC & BIOMOLECULAR CHEMISTRY
(2023)
Article
Computer Science, Cybernetics
Ganesh Gopal Devarajan, Senthil Murugan Nagarajan, Sardar Irfanullah Amanullah, S. A. Sahaaya Arul Mary, Ali Kashif Bashir
Summary: Social networking websites are the best platforms for news dissemination, but they also lead to the spread of fake news. Traditional detection methods focus on content analysis, while current researchers explore the social features of news. We propose an AI-assisted fake news detection model using deep natural language processing. The model includes four layers: publisher layer, social media networking layer, enabled edge layer, and cloud layer. Our model achieves an average accuracy of 99.72% and an F1 score of 98.33%, outperforming existing methods, based on evaluation using three datasets (Buzzface, FakeNewsNet, and Twitter).
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2023)
Proceedings Paper
Computer Science, Hardware & Architecture
Deborsi Basu, Uttam Ghosh, Raja Datta
Summary: This study proposes a holistic infrastructure deployment framework for 5G and beyond communication networks, with virtualized Software-Defined Networking (vSDN) as the core, aiming to address the connectivity challenges faced by developing countries through advanced technological solutions.
PROCEEDINGS OF THE 24TH INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING AND NETWORKING, ICDCN 2023
(2023)
Proceedings Paper
Computer Science, Hardware & Architecture
Debashis Das, Sourav Banerjee, Kousik Dasgupta, Pushpita Chatterjee, Uttam Ghosh, Utpal Biswas
Summary: This study proposes a blockchain-enabled SDN framework to address security and privacy issues in 5G networks. By using Software Defined Network (SDN) and Network Function Virtualization (NFV), the proposed framework can enhance network transparency, data security, and user privacy.
PROCEEDINGS OF THE 24TH INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING AND NETWORKING, ICDCN 2023
(2023)
Article
Engineering, Civil
Sourav Banerjee, Debashis Das, Pushpita Chatterjee, Benjamin Blakely, Uttam Ghosh
Summary: The notion of an intelligent transportation system (ITS) aims to enhance the performance of transportation networks. This paper proposes a sustainable safety management framework by integrating blockchain, which introduces AI-enabled vehicle smart devices and smart contracts to improve the sustainability and safety of the transportation system.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Multidisciplinary Sciences
Soumya Ranjan Nayak, Janmenjoy Nayak, Utkarsh Sinha, Vaibhav Arora, Uttam Ghosh, Suresh Chandra Satapathy
Summary: This paper presents a unique lightweight deep learning-based approach for diagnosing COVID-19 using X-ray radiographs of the chest, achieving high accuracy and robustness.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2023)
Article
Construction & Building Technology
Gabriele Bernardini, Tiago Miguel Ferreira, Pilar Baquedano Julia, Rafael Ramirez Eudave, Enrico Quagliarini
Summary: This research offers a methodology for combined spatiotemporal flood risk assessment, considering hazard, physical vulnerability, user exposure, and vulnerability. It adopts a mesoscale approach and investigates indoor and outdoor users' exposure and vulnerability, using the Analytical Hierarchy Process to combine risk factors.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Ying Liu, Chunli Chu, Ruijun Zhang, Shaoqing Chen, Chao Xu, Dongliang Zhao, Chunchun Meng, Meiting Ju, Zhi Cao
Summary: This study investigates the effects of increasing road, wall, and roof albedo on mitigating the urban heat island (UHI) effect in different areas of Tianjin. The results reveal that increasing road albedo is more effective in fringe areas, while increasing wall and roof albedo is more effective in central areas. The temperature changes induced by albedo changes also show seasonal characteristics.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Xisheng Lin, Yunfei Fu, Daniel Z. Peng, Chun-Ho Liu, Mengyuan Chu, Zengshun Chen, Fan Yang, Tim K. T. Tse, Cruz Y. Li, Xinxin Feng
Summary: This study employed computational fluid dynamics and neural network models to investigate and predict pollutant dispersion in urban environments, providing valuable insights for designing effective strategies to mitigate the impacts of hazardous pollutants.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Dipanjan Nag, Arkopal Kishore Goswami
Summary: Future-oriented urban planning should continue to focus on the principles of accessible and walkable cities. The perception of people is crucial for developing better urban walking infrastructure, but current evaluation tools often neglect the "perceived" features of the walking network. This study used conjoint analysis to evaluate users' perception of link and network attributes, revealing the importance of considering both in improving the walking environment.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Yongxin Su, Tao Zhang, Mengyao Xu, Mao Tan, Yuzhou Zhang, Rui Wang, Ling Wang
Summary: This study proposes an optimization method for household integrated demand response (HIDR) by combining rough knowledge and a dueling deep Q-network (DDQN), aiming to address uncertainties in a household multi-energy system (HMES). The simulation results demonstrate that the proposed method outperforms rule-based methods and DDQN in terms of energy cost savings.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Sijia Sun, S. F. A. Batista, Monica Menendez, Yuanqing Wang, Shuang Zhang
Summary: This paper comprehensively analyzes the energy consumption characteristics of electric buses (EBs) and diesel buses (DBs) on different bus lane configurations and operational conditions. The study shows that EBs consume less energy in suburban areas when using regular lanes, while both EBs and DBs save substantial energy when operating on dedicated bus lanes in downtown areas. Notably, shared-use bus lanes have the highest energy consumption.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Shangshang Shen, Dan Yan, Xiaojie Liu
Summary: This study developed a comprehensive theoretical framework for evaluating, diagnosing, and optimizing multi-functional urban agriculture. The framework was applied in Xiamen, China to identify the obstacles that impede its coordinated development and propose optimized modes for its development. Results showed that urban agriculture in Xiamen exhibits sound social function, moderate economic function, and poor ecological function.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Oluwafemi E. Adeyeri, Akinleye H. Folorunsho, Kayode I. Ayegbusi, Vishal Bobde, Tolulope E. Adeliyi, Christopher E. Ndehedehe, Akintomide A. Akinsanola
Summary: This study examines the impact of land cover, vegetation health, climatic forcings, elevation heat loads, and terrain characteristics on land surface temperature distribution over West Africa. The random forest model performs the best in downscaling predictands. The southern regions consistently exhibit healthy vegetation, while areas with unhealthy vegetation coincide with hot land surface temperature clusters. Positive Normalized Difference Vegetation Index trends in the Sahel highlight rainfall recovery and subsequent greening. Southwest winds cause the upwelling of cold waters, resulting in low land surface temperatures in southern West Africa. Considering LVCET factors is crucial for prioritizing greening initiatives and urban planning.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Yuchi Cao, Yan Li, Shouyun Shen, Weiwei Wang, Xiao Peng, Jiaao Chen, Jingpeng Liao, Xinyi Lv, Yifan Liu, Lehan Ma, Guodian Hu, Jinghuan Jiang, Dan Sun, Qingchu Jiang, Qiulin Liao
Summary: The study reveals significant disparities in urban green equity, with high property price areas having better access to green spaces than low property price areas. Landscape and greening have the most significant impact on urban green space differentiation.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Shaobo Sun, Kui Shan, Shengwei Wang
Summary: Economizer control is an important measure for energy savings in air-conditioning systems during moderate seasons. Humidity measurement uncertainties have a significant impact on enthalpy-based economizer control, and an uncertainty-tolerant control strategy is proposed to mitigate these effects.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Ding Mao, Peng Wang, Yi-Ping Fang, Long Ni
Summary: This study analyzes the structure, function, operation, and failure characteristics of district heating networks (DHNs) and proposes vulnerability analysis methods. The effectiveness of these methods is validated through application to a DHN in a Chinese city. The study finds that the heat source connectivity efficiency loss rate effectively characterizes topological and functional vulnerability. It also reveals that controllable DHNs have higher functional vulnerability under large area failure scenarios.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Hamid Karimi, Saeed Hasanzadeh, Hedayat Saboori
Summary: This paper presents a stochastic and cooperative approach for the operation of a cluster of interconnected multi-energy systems. The proposed model investigates the interaction among energy systems and integrates hydrogen and water systems into the overall energy structure. The model studies the performance of energy system agents in decentralized and cooperative scheduling.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Zhiyu Yan, Xiaogang Guo, Zilong Zhao, Luliang Tang
Summary: This study proposes a novel framework for fine-grained information extraction and dynamic spatial-temporal awareness in disaster-stricken areas based on social media data. The framework utilizes deep learning modules to extract location and water depth information from text and images, and analyzes the spatio-temporal distribution characteristics. The results show that the fusion of text and image-based information can enhance the perception of flood processes.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
M. A. Pans, G. Claudio, P. C. Eames
Summary: This study simulated and optimized a speculative district heating system in an existing urban area in Loughborough, UK. The system used only renewable heat sources and thermal energy storage to address the mismatch between heat generation and demand. The study assessed the impact of long-term storage volume and charging temperature on system cost and energy efficiency.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Jianmei Zhong, Wei Zhang, Xiaoli Wang, Jinsheng Zhan, Tao Xia, Lingzhi Xie, Xiding Zeng, Kun Yang, Zhangyu Li, Ruiwen Zou, Zepu Bai, Qing Wang, Chenyang Zhang
Summary: This study aims to propose a suitable air distribution design and reduce the energy consumption of the BSL-4 laboratory. It analyzes the diffusion characteristics of aerosols, infection risk under different air distributions, and ventilation parameters. The results show that the proposed energy-saving operation strategy can reduce the energy consumption of the laboratory by 15-30%.
SUSTAINABLE CITIES AND SOCIETY
(2024)