DQN approach for adaptive self-healing of VNFs in cloud-native network
- Arulappan, Arunkumar, Mahanti, Aniket, Passi, Kalpdrum, Srinivasan, Thiruvenkadam, Naha, Ranesh, Raja, Gunasekaran
- Authors: Arulappan, Arunkumar , Mahanti, Aniket , Passi, Kalpdrum , Srinivasan, Thiruvenkadam , Naha, Ranesh , Raja, Gunasekaran
- Date: 2024
- Type: Text , Journal article
- Relation: IEEE Access Vol. 12, no. (2024), p. 34489-34504
- Full Text:
- Reviewed:
- Description: The transformation from physical network function to Virtual Network Function (VNF) requires a fundamental design change in how applications and services are tested and assured in a hybrid virtual network. Once the VNFs are onboarded in a cloud network infrastructure, operators need to test VNFs in real-time at the time of instantiation automatically. This paper explicitly analyses the problem of adaptive self-healing of a Virtual Machine (VM) allocated by the VNF with the Deep Reinforcement Learning (DRL) approach. The DRL-based big data collection and analytics engine performs aggregation to probe and analyze data for troubleshooting and performance management. This engine helps to determine corrective actions (self-healing), such as scaling or migrating VNFs. Hence, we proposed a Deep Queue Learning (DQL) based Deep Queue Networks (DQN) mechanism for self-healing VNFs in the virtualized infrastructure manager. Virtual network probes of closed-loop orchestration perform the automation of the VNF and provide analytics for real-time, policy-driven orchestration in an open networking automation platform through the stochastic gradient descent method for VNF service assurance and network reliability. The proposed DQN/DDQN mechanism optimizes the price and lowers the cost by 18% for resource usage without disrupting the Quality of Service (QoS) provided by the VNF. The outcome of adaptive self-healing of the VNFs enhances the computational performance by 27% compared to other state-of-the-art algorithms. © 2013 IEEE.
- Authors: Arulappan, Arunkumar , Mahanti, Aniket , Passi, Kalpdrum , Srinivasan, Thiruvenkadam , Naha, Ranesh , Raja, Gunasekaran
- Date: 2024
- Type: Text , Journal article
- Relation: IEEE Access Vol. 12, no. (2024), p. 34489-34504
- Full Text:
- Reviewed:
- Description: The transformation from physical network function to Virtual Network Function (VNF) requires a fundamental design change in how applications and services are tested and assured in a hybrid virtual network. Once the VNFs are onboarded in a cloud network infrastructure, operators need to test VNFs in real-time at the time of instantiation automatically. This paper explicitly analyses the problem of adaptive self-healing of a Virtual Machine (VM) allocated by the VNF with the Deep Reinforcement Learning (DRL) approach. The DRL-based big data collection and analytics engine performs aggregation to probe and analyze data for troubleshooting and performance management. This engine helps to determine corrective actions (self-healing), such as scaling or migrating VNFs. Hence, we proposed a Deep Queue Learning (DQL) based Deep Queue Networks (DQN) mechanism for self-healing VNFs in the virtualized infrastructure manager. Virtual network probes of closed-loop orchestration perform the automation of the VNF and provide analytics for real-time, policy-driven orchestration in an open networking automation platform through the stochastic gradient descent method for VNF service assurance and network reliability. The proposed DQN/DDQN mechanism optimizes the price and lowers the cost by 18% for resource usage without disrupting the Quality of Service (QoS) provided by the VNF. The outcome of adaptive self-healing of the VNFs enhances the computational performance by 27% compared to other state-of-the-art algorithms. © 2013 IEEE.
Economic model predictive control for microgrid optimization : a review
- Hu, Jiefeng, Shan, Yinghao, Yang, Yong, Parisio, Alessandra, Li, Yong, Amjady, Nima, Islam, Syed, Cheng, Ka, Guerrero, Josep, Rodriguez, Jose
- Authors: Hu, Jiefeng , Shan, Yinghao , Yang, Yong , Parisio, Alessandra , Li, Yong , Amjady, Nima , Islam, Syed , Cheng, Ka , Guerrero, Josep , Rodriguez, Jose
- Date: 2024
- Type: Text , Journal article
- Relation: IEEE Transactions on Smart Grid Vol. 15, no. 1 (2024), p. 472-484
- Full Text:
- Reviewed:
- Description: Microgrids have emerged as a promising solution to integrate distributed energy resources (DERs) and supply reliable and efficient electricity. The operation of a microgrid involves the coordination of different DERs and loads. To date, various control methods have been developed to maximize the overall benefit while satisfying various constraints. Now it is urgently needed to understand and comprehend these approaches to further stimulate the deployment of microgrids. This paper presents an overview for researchers on economic model predictive control (EMPC) methods of microgrids to achieve a variety of objectives such as cost minimization and benefit maximization. The fundamental principle of the EMPC theory is explained in detail. The most popular and important strategies applied to stand-alone microgrids, grid-connected microgrids, residential smart homes, as well as networked microgrids are discussed. Future trends are also highlighted. © 2010-2012 IEEE.
- Authors: Hu, Jiefeng , Shan, Yinghao , Yang, Yong , Parisio, Alessandra , Li, Yong , Amjady, Nima , Islam, Syed , Cheng, Ka , Guerrero, Josep , Rodriguez, Jose
- Date: 2024
- Type: Text , Journal article
- Relation: IEEE Transactions on Smart Grid Vol. 15, no. 1 (2024), p. 472-484
- Full Text:
- Reviewed:
- Description: Microgrids have emerged as a promising solution to integrate distributed energy resources (DERs) and supply reliable and efficient electricity. The operation of a microgrid involves the coordination of different DERs and loads. To date, various control methods have been developed to maximize the overall benefit while satisfying various constraints. Now it is urgently needed to understand and comprehend these approaches to further stimulate the deployment of microgrids. This paper presents an overview for researchers on economic model predictive control (EMPC) methods of microgrids to achieve a variety of objectives such as cost minimization and benefit maximization. The fundamental principle of the EMPC theory is explained in detail. The most popular and important strategies applied to stand-alone microgrids, grid-connected microgrids, residential smart homes, as well as networked microgrids are discussed. Future trends are also highlighted. © 2010-2012 IEEE.
A blockchain-based deep-learning-driven architecture for quality routing in wireless sensor networks
- Khan, Zahoor, Amjad, Sana, Ahmed, Farwa, Almasoud, Abdullah, Imran, Muhammad, Javaid, Nadeem
- Authors: Khan, Zahoor , Amjad, Sana , Ahmed, Farwa , Almasoud, Abdullah , Imran, Muhammad , Javaid, Nadeem
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 31036-31051
- Full Text:
- Reviewed:
- Description: Over the past few years, great importance has been given to wireless sensor networks (WSNs) as they play a significant role in facilitating the world with daily life services like healthcare, military, social products, etc. However, heterogeneous nature of WSNs makes them prone to various attacks, which results in low throughput, and high network delay and high energy consumption. In the WSNs, routing is performed using different routing protocols like low-energy adaptive clustering hierarchy (LEACH), heterogeneous gateway-based energy-aware multi-hop routing (HMGEAR), etc. In such protocols, some nodes in the network may perform malicious activities. Therefore, four deep learning (DL) techniques and a real-time message content validation (RMCV) scheme based on blockchain are used in the proposed network for the detection of malicious nodes (MNs). Moreover, to analyse the routing data in the WSN, DL models are trained on a state-of-the-art dataset generated from LEACH, known as WSN-DS 2016. The WSN contains three types of nodes: sensor nodes, cluster heads (CHs) and the base station (BS). The CHs after aggregating the data received from the sensor nodes, send it towards the BS. Furthermore, to overcome the single point of failure issue, a decentralized blockchain is deployed on CHs and BS. Additionally, MNs are removed from the network using RMCV and DL techniques. Moreover, legitimate nodes (LNs) are registered in the blockchain network using proof-of-authority consensus protocol. The protocol outperforms proof-of-work in terms of computational cost. Later, routing is performed between the LNs using different routing protocols and the results are compared with original LEACH and HMGEAR protocols. The results show that the accuracy of GRU is 97%, LSTM is 96%, CNN is 92% and ANN is 90%. Throughput, delay and the death of the first node are computed for LEACH, LEACH with DL, LEACH with RMCV, HMGEAR, HMGEAR with DL and HMGEAR with RMCV. Moreover, Oyente is used to perform the formal security analysis of the designed smart contract. The analysis shows that blockchain network is resilient against vulnerabilities. © 2013 IEEE.
A blockchain-based deep-learning-driven architecture for quality routing in wireless sensor networks
- Authors: Khan, Zahoor , Amjad, Sana , Ahmed, Farwa , Almasoud, Abdullah , Imran, Muhammad , Javaid, Nadeem
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 31036-31051
- Full Text:
- Reviewed:
- Description: Over the past few years, great importance has been given to wireless sensor networks (WSNs) as they play a significant role in facilitating the world with daily life services like healthcare, military, social products, etc. However, heterogeneous nature of WSNs makes them prone to various attacks, which results in low throughput, and high network delay and high energy consumption. In the WSNs, routing is performed using different routing protocols like low-energy adaptive clustering hierarchy (LEACH), heterogeneous gateway-based energy-aware multi-hop routing (HMGEAR), etc. In such protocols, some nodes in the network may perform malicious activities. Therefore, four deep learning (DL) techniques and a real-time message content validation (RMCV) scheme based on blockchain are used in the proposed network for the detection of malicious nodes (MNs). Moreover, to analyse the routing data in the WSN, DL models are trained on a state-of-the-art dataset generated from LEACH, known as WSN-DS 2016. The WSN contains three types of nodes: sensor nodes, cluster heads (CHs) and the base station (BS). The CHs after aggregating the data received from the sensor nodes, send it towards the BS. Furthermore, to overcome the single point of failure issue, a decentralized blockchain is deployed on CHs and BS. Additionally, MNs are removed from the network using RMCV and DL techniques. Moreover, legitimate nodes (LNs) are registered in the blockchain network using proof-of-authority consensus protocol. The protocol outperforms proof-of-work in terms of computational cost. Later, routing is performed between the LNs using different routing protocols and the results are compared with original LEACH and HMGEAR protocols. The results show that the accuracy of GRU is 97%, LSTM is 96%, CNN is 92% and ANN is 90%. Throughput, delay and the death of the first node are computed for LEACH, LEACH with DL, LEACH with RMCV, HMGEAR, HMGEAR with DL and HMGEAR with RMCV. Moreover, Oyente is used to perform the formal security analysis of the designed smart contract. The analysis shows that blockchain network is resilient against vulnerabilities. © 2013 IEEE.
An agriprecision decision support system for weed management in pastures
- Chegini, Hossein, Naha, Ranesh, Mahanti, Aniket, Gong, Mingwei, Passi, Kalpdrum
- Authors: Chegini, Hossein , Naha, Ranesh , Mahanti, Aniket , Gong, Mingwei , Passi, Kalpdrum
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 92660-92675
- Full Text:
- Reviewed:
- Description: Pastures are a vital source of dairy products and cattle nutrition, and as such, play a significant role in New Zealand's agricultural economy. However, weeds can be a major problem for pastures, making it a challenge for dairy farmers to monitor and control them. Currently, most of the tasks for weed management are done manually, and farmers lack persistent technology for weed control. This motivated us to design, implement, and evaluate a Decision Support System (DSS) to detect weeds in pastures and provide decisions for the cleanup of weeds. Our proposed system uses two primary inputs: weeds and bare patches. We created a synthetic dataset to train a weed detection model and designed a fuzzy inference system to assess a pasture. We also used a neuro-fuzzy system in our DSS to evaluate our fuzzy model and tune its parameters for better functioning and accuracy. Our work aims to assist dairy farmers in better weed monitoring, as well as to provide 2D maps of weed density and yield score, which can be of significant value when no digital and meaningful images of pastures exist. The system can also support farmers in scheduling, recommending prohibitive tasks, and storing historical data for pasture analysis, collaborated by stakeholders. © 2013 IEEE.
- Authors: Chegini, Hossein , Naha, Ranesh , Mahanti, Aniket , Gong, Mingwei , Passi, Kalpdrum
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 92660-92675
- Full Text:
- Reviewed:
- Description: Pastures are a vital source of dairy products and cattle nutrition, and as such, play a significant role in New Zealand's agricultural economy. However, weeds can be a major problem for pastures, making it a challenge for dairy farmers to monitor and control them. Currently, most of the tasks for weed management are done manually, and farmers lack persistent technology for weed control. This motivated us to design, implement, and evaluate a Decision Support System (DSS) to detect weeds in pastures and provide decisions for the cleanup of weeds. Our proposed system uses two primary inputs: weeds and bare patches. We created a synthetic dataset to train a weed detection model and designed a fuzzy inference system to assess a pasture. We also used a neuro-fuzzy system in our DSS to evaluate our fuzzy model and tune its parameters for better functioning and accuracy. Our work aims to assist dairy farmers in better weed monitoring, as well as to provide 2D maps of weed density and yield score, which can be of significant value when no digital and meaningful images of pastures exist. The system can also support farmers in scheduling, recommending prohibitive tasks, and storing historical data for pasture analysis, collaborated by stakeholders. © 2013 IEEE.
Applications of machine learning and deep learning in antenna design, optimization, and selection : a review
- Sarker, Nayan, Podder, Prajoy, Mondal, M., Shafin, Sakib, Kamruzzaman, Joarder
- Authors: Sarker, Nayan , Podder, Prajoy , Mondal, M. , Shafin, Sakib , Kamruzzaman, Joarder
- Date: 2023
- Type: Text , Journal article , Review
- Relation: IEEE Access Vol. 11, no. (2023), p. 103890-103915
- Full Text:
- Reviewed:
- Description: This review paper provides an overview of the latest developments in artificial intelligence (AI)-based antenna design and optimization for wireless communications. Machine learning (ML) and deep learning (DL) algorithms are applied to antenna engineering to improve the efficiency of the design and optimization processes. The review discusses the use of electromagnetic (EM) simulators such as computer simulation technology (CST) and high-frequency structure simulator (HFSS) for ML and DL-based antenna design, which also covers reinforcement learning (RL)-bases approaches. Various antenna optimization methods including parallel optimization, single and multi-objective optimization, variable fidelity optimization, multilayer ML-assisted optimization, and surrogate-based optimization are discussed. The review also covers the AI-based antenna selection approaches for wireless applications. To support the automation of antenna engineering, the data generation technique with computational electromagnetics software is described and some useful datasets are reported. The review concludes that ML/DL can enhance antenna behavior prediction, reduce the number of simulations, improve computer efficiency, and speed up the antenna design process. © 2013 IEEE.
- Authors: Sarker, Nayan , Podder, Prajoy , Mondal, M. , Shafin, Sakib , Kamruzzaman, Joarder
- Date: 2023
- Type: Text , Journal article , Review
- Relation: IEEE Access Vol. 11, no. (2023), p. 103890-103915
- Full Text:
- Reviewed:
- Description: This review paper provides an overview of the latest developments in artificial intelligence (AI)-based antenna design and optimization for wireless communications. Machine learning (ML) and deep learning (DL) algorithms are applied to antenna engineering to improve the efficiency of the design and optimization processes. The review discusses the use of electromagnetic (EM) simulators such as computer simulation technology (CST) and high-frequency structure simulator (HFSS) for ML and DL-based antenna design, which also covers reinforcement learning (RL)-bases approaches. Various antenna optimization methods including parallel optimization, single and multi-objective optimization, variable fidelity optimization, multilayer ML-assisted optimization, and surrogate-based optimization are discussed. The review also covers the AI-based antenna selection approaches for wireless applications. To support the automation of antenna engineering, the data generation technique with computational electromagnetics software is described and some useful datasets are reported. The review concludes that ML/DL can enhance antenna behavior prediction, reduce the number of simulations, improve computer efficiency, and speed up the antenna design process. © 2013 IEEE.
Critical data detection for dynamically adjustable product quality in IIoT-enabled manufacturing
- Sen, Sachin, Karmakar, Gour, Pang, Shaoning
- Authors: Sen, Sachin , Karmakar, Gour , Pang, Shaoning
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 49464-49480
- Full Text:
- Reviewed:
- Description: The IIoT technologies, due to the widespread use of sensors, generate massive data that are key in providing innovative and efficient industrial management, operation, and product quality control processes. The significance of data has prompted relevant research communities and application developers how to harness the values of these data in secure manufacturing. Critical data analysis, identification of critical factors to improve the manufacturing process and critical data associated with product quality have been investigated in the current literature. However, the current works on product quality control are mainly based on static data analysis, where data may change, but there is no way to adjust them dynamically. Thus, they are not applicable for product quality control, at which point their adjustment is instantly required. However, many manufacturing systems exist, like beverages and food, where ingredients must be adjusted instantaneously to maintain product quality. To address this research gap, we introduce a method that identifies the critical data based on their ranking by exploiting three criticality assessment criteria that capture the instantaneous product quality change during manufacturing. These three criteria are - (1) correlation, (2) percentage quality change and (3) sensitivity for the assessment of data criticality. The product quality is estimated using polynomial regression (POLY), SVM, and DNN. The proposed method is validated using wine manufacturing data. Our proposed method accurately identifies critical data, where SVM produces the lowest average production quality prediction error (10.40%) compared with that of POLY (11%) and DNN (14.40%). © 2013 IEEE.
- Authors: Sen, Sachin , Karmakar, Gour , Pang, Shaoning
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 49464-49480
- Full Text:
- Reviewed:
- Description: The IIoT technologies, due to the widespread use of sensors, generate massive data that are key in providing innovative and efficient industrial management, operation, and product quality control processes. The significance of data has prompted relevant research communities and application developers how to harness the values of these data in secure manufacturing. Critical data analysis, identification of critical factors to improve the manufacturing process and critical data associated with product quality have been investigated in the current literature. However, the current works on product quality control are mainly based on static data analysis, where data may change, but there is no way to adjust them dynamically. Thus, they are not applicable for product quality control, at which point their adjustment is instantly required. However, many manufacturing systems exist, like beverages and food, where ingredients must be adjusted instantaneously to maintain product quality. To address this research gap, we introduce a method that identifies the critical data based on their ranking by exploiting three criticality assessment criteria that capture the instantaneous product quality change during manufacturing. These three criteria are - (1) correlation, (2) percentage quality change and (3) sensitivity for the assessment of data criticality. The product quality is estimated using polynomial regression (POLY), SVM, and DNN. The proposed method is validated using wine manufacturing data. Our proposed method accurately identifies critical data, where SVM produces the lowest average production quality prediction error (10.40%) compared with that of POLY (11%) and DNN (14.40%). © 2013 IEEE.
Device agent assisted blockchain leveraged framework for Internet of Things
- Nasrullah, Tarique, Islam, Md Manowarul, Uddin, Md Ashraf, Khan, Md Anisauzzaman, Layek, Md Abu, Stranieri, Andrew, Huh, Eui-Nam
- Authors: Nasrullah, Tarique , Islam, Md Manowarul , Uddin, Md Ashraf , Khan, Md Anisauzzaman , Layek, Md Abu , Stranieri, Andrew , Huh, Eui-Nam
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 1254-1268
- Full Text:
- Reviewed:
- Description: Blockchain (BC) is a burgeoning technology that has emerged as a promising solution to peer-to-peer communication security and privacy challenges. As a revolutionary technology, blockchain has drawn the attention of academics and researchers. Cryptocurrencies have already effectively utilized BC technology. Many researchers have sought to implement this technique in different sectors, including the Internet of Things. To store and manage IoT data, we present in this paper a lightweight BC-based architecture with a modified raft algorithm-based consensus protocol. We designed a Device Agent that executes a novel registration procedure to connect IoT devices to the blockchain. We implemented the framework on Docker using the Go programming language. We have simulated the framework on a Linux environment hosted in the cloud. We have conducted a detailed performance analysis using a variety of measures. The results demonstrate that our suggested solution is suitable for facilitating the management of IoT data with increased security and privacy. In terms of throughput and block generation time, the results indicate that our solution might be 40% to 45% faster than the existing blockchain. © 2013 IEEE.
- Authors: Nasrullah, Tarique , Islam, Md Manowarul , Uddin, Md Ashraf , Khan, Md Anisauzzaman , Layek, Md Abu , Stranieri, Andrew , Huh, Eui-Nam
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 1254-1268
- Full Text:
- Reviewed:
- Description: Blockchain (BC) is a burgeoning technology that has emerged as a promising solution to peer-to-peer communication security and privacy challenges. As a revolutionary technology, blockchain has drawn the attention of academics and researchers. Cryptocurrencies have already effectively utilized BC technology. Many researchers have sought to implement this technique in different sectors, including the Internet of Things. To store and manage IoT data, we present in this paper a lightweight BC-based architecture with a modified raft algorithm-based consensus protocol. We designed a Device Agent that executes a novel registration procedure to connect IoT devices to the blockchain. We implemented the framework on Docker using the Go programming language. We have simulated the framework on a Linux environment hosted in the cloud. We have conducted a detailed performance analysis using a variety of measures. The results demonstrate that our suggested solution is suitable for facilitating the management of IoT data with increased security and privacy. In terms of throughput and block generation time, the results indicate that our solution might be 40% to 45% faster than the existing blockchain. © 2013 IEEE.
Domestic load management with coordinated photovoltaics, battery storage and electric vehicle operation
- Das, Narottam, Haque, Akramul, Zaman, Hasneen, Morsalin, Sayidul, Islam, Syed
- Authors: Das, Narottam , Haque, Akramul , Zaman, Hasneen , Morsalin, Sayidul , Islam, Syed
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 12075-12087
- Full Text:
- Reviewed:
- Description: Coordinated power demand management at residential or domestic levels allows energy participants to efficiently manage load profiles, increase energy efficiency and reduce operational cost. In this paper, a hierarchical coordination framework to optimally manage domestic load using photovoltaic (PV) units, battery-energy-storage-systems (BESs) and electric vehicles (EVs) is presented. The bidirectional power flow of EV with vehicle to grid (V2G) operation manages real-time domestic load profile and takes appropriate coordinated action using its controller when necessary. The proposed system has been applied to a real power distribution network and tested with real load patterns and load dynamics. This also includes various test scenarios and prosumer's preferences e.g., with or without EVs, number of EV owners, number of households, and prosumer's daily activities. This is a combined hybrid system for hierarchical coordination that consists of PV units, BES systems and EVs. The system performance was analyzed with different commercial EV types with charging/ discharging constraints and the result shows that the domestic load demand on the distribution grid during the peak period has been reduced significantly. In the end, this proposed system's performance was compared with the prediction-based test techniques and the financial benefits were estimated. © 2013 IEEE.
- Authors: Das, Narottam , Haque, Akramul , Zaman, Hasneen , Morsalin, Sayidul , Islam, Syed
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 12075-12087
- Full Text:
- Reviewed:
- Description: Coordinated power demand management at residential or domestic levels allows energy participants to efficiently manage load profiles, increase energy efficiency and reduce operational cost. In this paper, a hierarchical coordination framework to optimally manage domestic load using photovoltaic (PV) units, battery-energy-storage-systems (BESs) and electric vehicles (EVs) is presented. The bidirectional power flow of EV with vehicle to grid (V2G) operation manages real-time domestic load profile and takes appropriate coordinated action using its controller when necessary. The proposed system has been applied to a real power distribution network and tested with real load patterns and load dynamics. This also includes various test scenarios and prosumer's preferences e.g., with or without EVs, number of EV owners, number of households, and prosumer's daily activities. This is a combined hybrid system for hierarchical coordination that consists of PV units, BES systems and EVs. The system performance was analyzed with different commercial EV types with charging/ discharging constraints and the result shows that the domestic load demand on the distribution grid during the peak period has been reduced significantly. In the end, this proposed system's performance was compared with the prediction-based test techniques and the financial benefits were estimated. © 2013 IEEE.
Malicious node detection using machine learning and distributed data storage using blockchain in WSNs
- Nouman, Muhammad, Qasim, Umar, Nasir, Hina, Almasoud, Abdullah, Imran, Muhammad, Javaid, Nadeem
- Authors: Nouman, Muhammad , Qasim, Umar , Nasir, Hina , Almasoud, Abdullah , Imran, Muhammad , Javaid, Nadeem
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 6106-6121
- Full Text:
- Reviewed:
- Description: In the proposed work, blockchain is implemented on the Base Stations (BSs) and Cluster Heads (CHs) to register the nodes using their credentials and also to tackle various security issues. Moreover, a Machine Learning (ML) classifier, termed as Histogram Gradient Boost (HGB), is employed on the BSs to classify the nodes as malicious or legitimate. In case, the node is found to be malicious, its registration is revoked from the network. Whereas, if a node is found to be legitimate, then its data is stored in an Interplanetary File System (IPFS). IPFS stores the data in the form of chunks and generates hash for the data, which is then stored in blockchain. In addition, Verifiable Byzantine Fault Tolerance (VBFT) is used instead of Proof of Work (PoW) to perform consensus and validate transactions. Also, extensive simulations are performed using the Wireless Sensor Network (WSN) dataset, referred as WSN-DS. The proposed model is evaluated both on the original dataset and the balanced dataset. Furthermore, HGB is compared with other existing classifiers, Adaptive Boost (AdaBoost), Gradient Boost (GB), Linear Discriminant Analysis (LDA), Extreme Gradient Boost (XGB) and ridge, using different performance metrics like accuracy, precision, recall, micro-F1 score and macro-F1 score. The performance evaluation of HGB shows that it outperforms GB, AdaBoost, LDA, XGB and Ridge by 2-4%, 8-10%, 12-14%, 3-5% and 14-16%, respectively. Moreover, the results with balanced dataset are better than those with original dataset. Also, VBFT performs 20-30% better than PoW. Overall, the proposed model performs efficiently in terms of malicious node detection and secure data storage. © 2013 IEEE.
- Authors: Nouman, Muhammad , Qasim, Umar , Nasir, Hina , Almasoud, Abdullah , Imran, Muhammad , Javaid, Nadeem
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 6106-6121
- Full Text:
- Reviewed:
- Description: In the proposed work, blockchain is implemented on the Base Stations (BSs) and Cluster Heads (CHs) to register the nodes using their credentials and also to tackle various security issues. Moreover, a Machine Learning (ML) classifier, termed as Histogram Gradient Boost (HGB), is employed on the BSs to classify the nodes as malicious or legitimate. In case, the node is found to be malicious, its registration is revoked from the network. Whereas, if a node is found to be legitimate, then its data is stored in an Interplanetary File System (IPFS). IPFS stores the data in the form of chunks and generates hash for the data, which is then stored in blockchain. In addition, Verifiable Byzantine Fault Tolerance (VBFT) is used instead of Proof of Work (PoW) to perform consensus and validate transactions. Also, extensive simulations are performed using the Wireless Sensor Network (WSN) dataset, referred as WSN-DS. The proposed model is evaluated both on the original dataset and the balanced dataset. Furthermore, HGB is compared with other existing classifiers, Adaptive Boost (AdaBoost), Gradient Boost (GB), Linear Discriminant Analysis (LDA), Extreme Gradient Boost (XGB) and ridge, using different performance metrics like accuracy, precision, recall, micro-F1 score and macro-F1 score. The performance evaluation of HGB shows that it outperforms GB, AdaBoost, LDA, XGB and Ridge by 2-4%, 8-10%, 12-14%, 3-5% and 14-16%, respectively. Moreover, the results with balanced dataset are better than those with original dataset. Also, VBFT performs 20-30% better than PoW. Overall, the proposed model performs efficiently in terms of malicious node detection and secure data storage. © 2013 IEEE.
MSCET : a multi-scenario offloading schedule for biomedical data processing and analysis in cloud-edge-terminal collaborative vehicular networks
- Ni, Zhichen, Chen, Honglong, Li, Zhe, Wang, Xiaomeng, Yan, Na, Liu, Weifeng, Xia, Feng
- Authors: Ni, Zhichen , Chen, Honglong , Li, Zhe , Wang, Xiaomeng , Yan, Na , Liu, Weifeng , Xia, Feng
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE/ACM Transactions on Computational Biology and Bioinformatics Vol. 20, no. 4 (2023), p. 2376-2386
- Full Text:
- Reviewed:
- Description: With the rapid development of Artificial Intelligence (AI) and Internet of Things (IoTs), an increasing number of computation intensive or delay sensitive biomedical data processing and analysis tasks are produced in vehicles, bringing more and more challenges to the biometric monitoring of drivers. Edge computing is a new paradigm to solve these challenges by offloading tasks from the resource-limited vehicles to Edge Servers (ESs) in Road Side Units (RSUs). However, most of the traditional offloading schedules for vehicular networks concentrate on the edge, while some tasks may be too complex for ESs to process. To this end, we consider a collaborative vehicular network in which the cloud, edge and terminal can cooperate with each other to accomplish the tasks. The vehicles can offload the computation intensive tasks to the cloud to save the resource of edge. We further construct the virtual resource pool which can integrate the resource of multiple ESs since some regions may be covered by multiple RSUs. In this paper, we propose a Multi-Scenario offloading schedule for biomedical data processing and analysis in Cloud-Edge-Terminal collaborative vehicular networks called MSCET. The parameters of the proposed MSCET are optimized to maximize the system utility. We also conduct extensive simulations to evaluate the proposed MSCET and the results illustrate that MSCET outperforms other existing schedules. © 2004-2012 IEEE.
- Authors: Ni, Zhichen , Chen, Honglong , Li, Zhe , Wang, Xiaomeng , Yan, Na , Liu, Weifeng , Xia, Feng
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE/ACM Transactions on Computational Biology and Bioinformatics Vol. 20, no. 4 (2023), p. 2376-2386
- Full Text:
- Reviewed:
- Description: With the rapid development of Artificial Intelligence (AI) and Internet of Things (IoTs), an increasing number of computation intensive or delay sensitive biomedical data processing and analysis tasks are produced in vehicles, bringing more and more challenges to the biometric monitoring of drivers. Edge computing is a new paradigm to solve these challenges by offloading tasks from the resource-limited vehicles to Edge Servers (ESs) in Road Side Units (RSUs). However, most of the traditional offloading schedules for vehicular networks concentrate on the edge, while some tasks may be too complex for ESs to process. To this end, we consider a collaborative vehicular network in which the cloud, edge and terminal can cooperate with each other to accomplish the tasks. The vehicles can offload the computation intensive tasks to the cloud to save the resource of edge. We further construct the virtual resource pool which can integrate the resource of multiple ESs since some regions may be covered by multiple RSUs. In this paper, we propose a Multi-Scenario offloading schedule for biomedical data processing and analysis in Cloud-Edge-Terminal collaborative vehicular networks called MSCET. The parameters of the proposed MSCET are optimized to maximize the system utility. We also conduct extensive simulations to evaluate the proposed MSCET and the results illustrate that MSCET outperforms other existing schedules. © 2004-2012 IEEE.
Multi-aspect annotation and analysis of Nepali tweets on anti-establishment election discourse
- Rauniyar, Kritesh, Poudel, Sweta, Shiwakoti, Shuvam, Thapa, Surendrabikram, Rashid, Junaid, Kim, Jungeun, Imran, Muhammad, Naseem, Usman
- Authors: Rauniyar, Kritesh , Poudel, Sweta , Shiwakoti, Shuvam , Thapa, Surendrabikram , Rashid, Junaid , Kim, Jungeun , Imran, Muhammad , Naseem, Usman
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 143092-143115
- Full Text:
- Reviewed:
- Description: In today's social media-dominated landscape, digital platforms wield substantial influence over public opinion, particularly during crucial political events such as electoral processes. These platforms become hubs for diverse discussions, encompassing topics, reforms, and desired changes. Notably, in times of government dissatisfaction, they serve as arenas for anti-establishment discourse, highlighting the need to analyze public sentiment in these conversations. However, the analysis of such discourse is notably scarce, even in high-resource languages, and entirely non-existent in the context of the Nepali language. To address this critical gap, we present Nepal Anti Establishment discourse Tweets (NAET), a novel dataset comprising 4,445 multi-aspect annotated Nepali tweets, facilitating a comprehensive understanding of political conversations. Our contributions encompass evaluating tweet relevance, sentiment, and satire, while also exploring the presence of hate speech, identifying its targets, and distinguishing directed and non-directed expressions. Additionally, we investigate hope speech, an underexplored aspect crucial in the context of anti-establishment discourse, as it reflects the aspirations and expectations from new political figures and parties. Furthermore, we set NLP-based baselines for all these tasks. To ensure a holistic analysis, we also employ topic modeling, a powerful technique that helps us identify and understand the prevalent themes and patterns emerging from the discourse. Our research thus presents a comprehensive and multi-faceted perspective on anti-establishment election discourse in a low-resource language setting. The dataset is publicly available, facilitating in-depth analysis of political tweets in Nepali discourse and further advancing NLP research for the Nepali language through labeled data and baselines for various NLP tasks. The dataset for this work is made available at https://github.com/rkritesh210/NAET. © 2013 IEEE.
- Authors: Rauniyar, Kritesh , Poudel, Sweta , Shiwakoti, Shuvam , Thapa, Surendrabikram , Rashid, Junaid , Kim, Jungeun , Imran, Muhammad , Naseem, Usman
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 143092-143115
- Full Text:
- Reviewed:
- Description: In today's social media-dominated landscape, digital platforms wield substantial influence over public opinion, particularly during crucial political events such as electoral processes. These platforms become hubs for diverse discussions, encompassing topics, reforms, and desired changes. Notably, in times of government dissatisfaction, they serve as arenas for anti-establishment discourse, highlighting the need to analyze public sentiment in these conversations. However, the analysis of such discourse is notably scarce, even in high-resource languages, and entirely non-existent in the context of the Nepali language. To address this critical gap, we present Nepal Anti Establishment discourse Tweets (NAET), a novel dataset comprising 4,445 multi-aspect annotated Nepali tweets, facilitating a comprehensive understanding of political conversations. Our contributions encompass evaluating tweet relevance, sentiment, and satire, while also exploring the presence of hate speech, identifying its targets, and distinguishing directed and non-directed expressions. Additionally, we investigate hope speech, an underexplored aspect crucial in the context of anti-establishment discourse, as it reflects the aspirations and expectations from new political figures and parties. Furthermore, we set NLP-based baselines for all these tasks. To ensure a holistic analysis, we also employ topic modeling, a powerful technique that helps us identify and understand the prevalent themes and patterns emerging from the discourse. Our research thus presents a comprehensive and multi-faceted perspective on anti-establishment election discourse in a low-resource language setting. The dataset is publicly available, facilitating in-depth analysis of political tweets in Nepali discourse and further advancing NLP research for the Nepali language through labeled data and baselines for various NLP tasks. The dataset for this work is made available at https://github.com/rkritesh210/NAET. © 2013 IEEE.
Multi-slope path loss model-based performance assessment of heterogeneous cellular network in 5G
- Dahri, Safia, Shaikh, Muhammad, Alhussein, Musaed, Soomro, Muhammad, Aurangzeb, Khursheed, Imran, Muhammad
- Authors: Dahri, Safia , Shaikh, Muhammad , Alhussein, Musaed , Soomro, Muhammad , Aurangzeb, Khursheed , Imran, Muhammad
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 30473-30485
- Full Text:
- Reviewed:
- Description: The coverage and capacity required for fifth generation (5G) and beyond can be achieved using heterogeneous wireless networks. This exploration set up a limited number of user equipment (UEs) while taking into account the three-dimensional (3D) distance between UEs and base stations (BSs), multi-slope line of sight (LOS) and non-line of sight (n-LOS), idle mode capability (IMC), and third generation partnership projects (3GPP) path loss (PL) models. In the current work, we examine the relationship between the height and gain of the macro (M) and pico (P) base stations (BSs) antennas and the ratio of the density of the MBSs to the PBSs, indicated by the symbol $\beta $. Recent research demonstrates that the antenna height of PBSs should be kept to a minimum to get the best performance in terms of coverage and capacity for a 5G wireless network, whereas ASE smashes as $\beta $ crosses a specific value in 5G. We aim to address these issues and increased the performance of the 5G network by installing directional antennas at MBSs and omnidirectional antennas at Pico BSs while taking into consideration traditional antenna heights. The authors of this work used the multi-tier 3GPP PL model to take into account real-world scenarios and calculated SINR using average power. This study demonstrates that, when the multi-slope 3GPP PL model is used and directional antennas are installed at MBSs, coverage can be improved 10% and area spectral efficiency (ASE) can be improved 2.5 times over the course of the previous analysis. Similarly to this, the issue of an ASE crash after a base station density of 1000 has been resolved in this study. © 2013 IEEE.
- Authors: Dahri, Safia , Shaikh, Muhammad , Alhussein, Musaed , Soomro, Muhammad , Aurangzeb, Khursheed , Imran, Muhammad
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 30473-30485
- Full Text:
- Reviewed:
- Description: The coverage and capacity required for fifth generation (5G) and beyond can be achieved using heterogeneous wireless networks. This exploration set up a limited number of user equipment (UEs) while taking into account the three-dimensional (3D) distance between UEs and base stations (BSs), multi-slope line of sight (LOS) and non-line of sight (n-LOS), idle mode capability (IMC), and third generation partnership projects (3GPP) path loss (PL) models. In the current work, we examine the relationship between the height and gain of the macro (M) and pico (P) base stations (BSs) antennas and the ratio of the density of the MBSs to the PBSs, indicated by the symbol $\beta $. Recent research demonstrates that the antenna height of PBSs should be kept to a minimum to get the best performance in terms of coverage and capacity for a 5G wireless network, whereas ASE smashes as $\beta $ crosses a specific value in 5G. We aim to address these issues and increased the performance of the 5G network by installing directional antennas at MBSs and omnidirectional antennas at Pico BSs while taking into consideration traditional antenna heights. The authors of this work used the multi-tier 3GPP PL model to take into account real-world scenarios and calculated SINR using average power. This study demonstrates that, when the multi-slope 3GPP PL model is used and directional antennas are installed at MBSs, coverage can be improved 10% and area spectral efficiency (ASE) can be improved 2.5 times over the course of the previous analysis. Similarly to this, the issue of an ASE crash after a base station density of 1000 has been resolved in this study. © 2013 IEEE.
Numerical model of cloud-to-ground lightning for pyroCb thunderstorms
- Barman, Surajit, Shah, Rakibuzzaman, Islam, Syed, Kumar, Apurv
- Authors: Barman, Surajit , Shah, Rakibuzzaman , Islam, Syed , Kumar, Apurv
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 16, no. (2023), p. 8689-8701
- Full Text:
- Reviewed:
- Description: This paper demonstrates a 2-D numerical model to represent two conceptual pyrocumulonimbus (pyroCb) thundercloud structures: i) tilted dipole and ii) tripole structure with enhanced lower positive charge layer, which are hypothesized to explain the occurrence of lightning flashes in pyroCb storms created from severe wildfire events. The presented model considers more realistic thundercloud charge structures to investigate the electrical states and determine surface charge density for identifying potential lightning strike areas on Earth. Simulation results on dipole structure-based pyroCb thunderclouds confirm that the wind-shear extension of its upper positive (UP) charge layer by 2-8 km reduces the electric field and indicates the initiation of negative surface charge density around the earth periphery underneath the anvil cloud. These corresponding lateral extensions have confined the probable striking zone of-CG and +CG lightning within 0-23.5 km and 23.5-30 km in the simulation domain. In contrast, pyroCb thundercloud possessing the tripole structure with enhanced lower positive charge develops a negative electric field at the cloud's bottom part to block the progression of downward negative leader and cause the surface charge density beneath the thundercloud to become negative, which would lead to the formation of +CG flashes. Later, a parametric study is conducted assuming a positive linear correlation between the charge density and aerosol concentration to examine the effect of high aerosol concentration on surface charge density in both pyroCb thunderclouds. The proposed model can be expanded into 3-D to simulate lightning leader movement, aiding wildfire risk management. © 2008-2012 IEEE.
- Authors: Barman, Surajit , Shah, Rakibuzzaman , Islam, Syed , Kumar, Apurv
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 16, no. (2023), p. 8689-8701
- Full Text:
- Reviewed:
- Description: This paper demonstrates a 2-D numerical model to represent two conceptual pyrocumulonimbus (pyroCb) thundercloud structures: i) tilted dipole and ii) tripole structure with enhanced lower positive charge layer, which are hypothesized to explain the occurrence of lightning flashes in pyroCb storms created from severe wildfire events. The presented model considers more realistic thundercloud charge structures to investigate the electrical states and determine surface charge density for identifying potential lightning strike areas on Earth. Simulation results on dipole structure-based pyroCb thunderclouds confirm that the wind-shear extension of its upper positive (UP) charge layer by 2-8 km reduces the electric field and indicates the initiation of negative surface charge density around the earth periphery underneath the anvil cloud. These corresponding lateral extensions have confined the probable striking zone of-CG and +CG lightning within 0-23.5 km and 23.5-30 km in the simulation domain. In contrast, pyroCb thundercloud possessing the tripole structure with enhanced lower positive charge develops a negative electric field at the cloud's bottom part to block the progression of downward negative leader and cause the surface charge density beneath the thundercloud to become negative, which would lead to the formation of +CG flashes. Later, a parametric study is conducted assuming a positive linear correlation between the charge density and aerosol concentration to examine the effect of high aerosol concentration on surface charge density in both pyroCb thunderclouds. The proposed model can be expanded into 3-D to simulate lightning leader movement, aiding wildfire risk management. © 2008-2012 IEEE.
Reverse blocking over current busbar protection scheme based on IEC 61850 architecture
- Kumar, Shantanu, Abu-Siada, Ahmed, Das, Narottam, Islam, Syed
- Authors: Kumar, Shantanu , Abu-Siada, Ahmed , Das, Narottam , Islam, Syed
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Transactions on Industry Applications Vol. 59, no. 2 (2023), p. 2225-2233
- Full Text:
- Reviewed:
- Description: Substation Automation System (SAS) is currently in a matured state of technology that shall facilitate transformational changes from conventional protection scheme. IEC 61850 protocol is considered as the crux of digital SAS due to its multifunction features that include seamless communication, ability to integrate various intelligent electronic devices, potential for improved real-time condition monitoring, reliable protection, and control of critical electrical assets. Because the application of IEC 61850 in SAS is relatively new and has not fully implemented in many substations yet, further feasibility studies using multivendor equipment to assess its performance under different operating conditions is imperative. In this article, a practical reliable and efficient reverse blocking over current bus bar protection scheme based on IEC 61850 is implemented and tested. Also, a comparison of digital SAS and conventional protection scheme is presented to highlight the superiority of the former one. Experimental results attest the reliability and effectiveness of the proposed digital protection scheme along with the accuracy and security of transmitting data packets using sampled values and generic objective-oriented substation event communication protocols adopted by IEC 61850. © 2022 IEEE.
- Authors: Kumar, Shantanu , Abu-Siada, Ahmed , Das, Narottam , Islam, Syed
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Transactions on Industry Applications Vol. 59, no. 2 (2023), p. 2225-2233
- Full Text:
- Reviewed:
- Description: Substation Automation System (SAS) is currently in a matured state of technology that shall facilitate transformational changes from conventional protection scheme. IEC 61850 protocol is considered as the crux of digital SAS due to its multifunction features that include seamless communication, ability to integrate various intelligent electronic devices, potential for improved real-time condition monitoring, reliable protection, and control of critical electrical assets. Because the application of IEC 61850 in SAS is relatively new and has not fully implemented in many substations yet, further feasibility studies using multivendor equipment to assess its performance under different operating conditions is imperative. In this article, a practical reliable and efficient reverse blocking over current bus bar protection scheme based on IEC 61850 is implemented and tested. Also, a comparison of digital SAS and conventional protection scheme is presented to highlight the superiority of the former one. Experimental results attest the reliability and effectiveness of the proposed digital protection scheme along with the accuracy and security of transmitting data packets using sampled values and generic objective-oriented substation event communication protocols adopted by IEC 61850. © 2022 IEEE.
Survey : self-empowered wireless sensor networks security taxonomy, challenges, and future research directions
- Adil, Muhammad, Menon, Varun, Balasubramanian, Venki, Alotaibi, Sattam, Song, Houbing, Jin, Zhanpeng, Farouk, Ahmed
- Authors: Adil, Muhammad , Menon, Varun , Balasubramanian, Venki , Alotaibi, Sattam , Song, Houbing , Jin, Zhanpeng , Farouk, Ahmed
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Sensors Journal Vol. 23, no. 18 (2023), p. 20519-20535
- Full Text:
- Reviewed:
- Description: In the recent past, patient-wearable devices and implantable biosensors revealed exponential growth in digital healthcare, because they have the capability to allow access to information anywhere and every time to improve the life standard of multifarious disease-affected patients followed by healthy people. Following these advantages, digital healthcare demands a secure wireless communication infrastructure for interconnected self-empowered biosensor devices to maintain the trust of patients, doctors, pharmacologists, nursing staff, and other associated stakeholders. Several authentications, privacy, and data preservation schemes had been used in the literature to ensure the security of this emerging technology, but with time, these counteraction prototypes become vulnerable to new security threats, as the hackers work tirelessly to compromise them and steal the legitimate information of user's or disrupt the operation of an employed self-empowered wireless sensor network (SWSN). To discuss the security problems of SWSN applications, in this review article, we have presented a detailed survey of the present literature from 2019 to 2022, to familiarize the readers with different security threats and their counteraction schemes. Following this, we will highlight the pros and cons of these countermeasure techniques in the context of SWSN security requirements to underscore their limitations. Thereafter, we will follow-up on the underlined limitations to discuss the open security challenges of SWSNs that need the concerned authorities' attention. Based on this, we will pave a road map for future research work that could be useful for every individual associated with this technology. For the novelty and uniqueness of this work, we will make a comparative analysis with present survey papers published on this topic to answer the question of reviewers, readers, editors, and students why this article is in time and needed in the presence of rival papers. © 2022 IEEE.
- Authors: Adil, Muhammad , Menon, Varun , Balasubramanian, Venki , Alotaibi, Sattam , Song, Houbing , Jin, Zhanpeng , Farouk, Ahmed
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Sensors Journal Vol. 23, no. 18 (2023), p. 20519-20535
- Full Text:
- Reviewed:
- Description: In the recent past, patient-wearable devices and implantable biosensors revealed exponential growth in digital healthcare, because they have the capability to allow access to information anywhere and every time to improve the life standard of multifarious disease-affected patients followed by healthy people. Following these advantages, digital healthcare demands a secure wireless communication infrastructure for interconnected self-empowered biosensor devices to maintain the trust of patients, doctors, pharmacologists, nursing staff, and other associated stakeholders. Several authentications, privacy, and data preservation schemes had been used in the literature to ensure the security of this emerging technology, but with time, these counteraction prototypes become vulnerable to new security threats, as the hackers work tirelessly to compromise them and steal the legitimate information of user's or disrupt the operation of an employed self-empowered wireless sensor network (SWSN). To discuss the security problems of SWSN applications, in this review article, we have presented a detailed survey of the present literature from 2019 to 2022, to familiarize the readers with different security threats and their counteraction schemes. Following this, we will highlight the pros and cons of these countermeasure techniques in the context of SWSN security requirements to underscore their limitations. Thereafter, we will follow-up on the underlined limitations to discuss the open security challenges of SWSNs that need the concerned authorities' attention. Based on this, we will pave a road map for future research work that could be useful for every individual associated with this technology. For the novelty and uniqueness of this work, we will make a comparative analysis with present survey papers published on this topic to answer the question of reviewers, readers, editors, and students why this article is in time and needed in the presence of rival papers. © 2022 IEEE.
UDTN-RS : a new underwater delay tolerant network routing protocol for coastal patrol and surveillance
- Azad, Saiful, Neffati, Ahmed, Mahmud, Mufti, Kaiser, M., Ahmed, Muhammad, Kamruzzaman, Joarder
- Authors: Azad, Saiful , Neffati, Ahmed , Mahmud, Mufti , Kaiser, M. , Ahmed, Muhammad , Kamruzzaman, Joarder
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 142780-142793
- Full Text:
- Reviewed:
- Description: The Coastal Patrol and Surveillance Application (CPSA) is developed and deployed to detect, track and monitor water vessel traffic using automated devices. The latest advancements of marine technologies, including Automatic Underwater Vehicles, have encouraged the development of this type of applications. To facilitate their operations, installation of a Coastal Patrol and Surveillance Network (CPSN) is mandatory. One of the primary design objectives of this network is to deliver an adequate amount of data within an effective time frame. This is particularly essential for the detection of an intruder's vessel and its notification through the adverse underwater communication channels. Additionally, intermittent connectivity of the nodes remains another important obstacle to overcome to allow the smooth functioning of CPSA. Taking these objectives and obstacles into account, this work proposes a new protocol by ensembling forward error correction technique (namely Reed-Solomon codes or RS) in Underwater Delay Tolerant Network with probabilistic spraying technique (UDTN-Prob) routing protocol, named Underwater Delay Tolerant Protocol with RS (UDTN-RS). In addition, the existing binary packet spraying technique in UDTN-Prob is enhanced for supporting encoded packet exchange between the contacting nodes. A comprehensive simulation has been performed employing DEsign, Simulate, Emulate and Realize Test-beds (DESERT) underwater simulator along with World Ocean Simulation System (WOSS) package to receive a more realistic account of acoustic propagation for identifying the effectiveness of the proposed protocol. Three scenarios are considered during the simulation campaign, namely varying data transmission rate, varying area size, and a scenario focusing on estimating the overhead ratio. Conversely, for the first two scenarios, three metrics are taken into account: normalised packet delivery ratio, delay, and normalised throughput. The acquired results for these scenarios and metrics are compared to its ancestor, i.e., UDTN-Prob. The results suggest that the proposed UDTN-RS protocol can be considered as a suitable alternative to the existing protocols like UDTN-Prob, Epidemic, and others for sparse networks like CPSN. © 2013 IEEE.
- Authors: Azad, Saiful , Neffati, Ahmed , Mahmud, Mufti , Kaiser, M. , Ahmed, Muhammad , Kamruzzaman, Joarder
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 142780-142793
- Full Text:
- Reviewed:
- Description: The Coastal Patrol and Surveillance Application (CPSA) is developed and deployed to detect, track and monitor water vessel traffic using automated devices. The latest advancements of marine technologies, including Automatic Underwater Vehicles, have encouraged the development of this type of applications. To facilitate their operations, installation of a Coastal Patrol and Surveillance Network (CPSN) is mandatory. One of the primary design objectives of this network is to deliver an adequate amount of data within an effective time frame. This is particularly essential for the detection of an intruder's vessel and its notification through the adverse underwater communication channels. Additionally, intermittent connectivity of the nodes remains another important obstacle to overcome to allow the smooth functioning of CPSA. Taking these objectives and obstacles into account, this work proposes a new protocol by ensembling forward error correction technique (namely Reed-Solomon codes or RS) in Underwater Delay Tolerant Network with probabilistic spraying technique (UDTN-Prob) routing protocol, named Underwater Delay Tolerant Protocol with RS (UDTN-RS). In addition, the existing binary packet spraying technique in UDTN-Prob is enhanced for supporting encoded packet exchange between the contacting nodes. A comprehensive simulation has been performed employing DEsign, Simulate, Emulate and Realize Test-beds (DESERT) underwater simulator along with World Ocean Simulation System (WOSS) package to receive a more realistic account of acoustic propagation for identifying the effectiveness of the proposed protocol. Three scenarios are considered during the simulation campaign, namely varying data transmission rate, varying area size, and a scenario focusing on estimating the overhead ratio. Conversely, for the first two scenarios, three metrics are taken into account: normalised packet delivery ratio, delay, and normalised throughput. The acquired results for these scenarios and metrics are compared to its ancestor, i.e., UDTN-Prob. The results suggest that the proposed UDTN-RS protocol can be considered as a suitable alternative to the existing protocols like UDTN-Prob, Epidemic, and others for sparse networks like CPSN. © 2013 IEEE.
Wearable obstacle avoidance electronic travel aids for blind and visually impaired individuals : a systematic review
- Xu, Peijie, Kennedy, Gerard, Zhao, Fei-Yi, Zhang, Wen-Jing, Van Schyndel, Ron
- Authors: Xu, Peijie , Kennedy, Gerard , Zhao, Fei-Yi , Zhang, Wen-Jing , Van Schyndel, Ron
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 66587-66613
- Full Text:
- Reviewed:
- Description: Background Wearable obstacle avoidance electronic travel aids (ETAs) have been developed to assist the safe displacement of blind and visually impaired individuals (BVIs) in indoor/outdoor spaces. This systematic review aimed to understand the strengths and weaknesses of existing ETAs in terms of hardware functionality, cost, and user experience. These elements may influence the usability of the ETAs and are valuable in guiding the development of superior ETAs in the future. Methods Formally published studies designing and developing the wearable obstacle avoidance ETAs were searched for from six databases from their inception to April 2023. The PRISMA 2020 and APISSER guidelines were followed. Results Eighty-nine studies were included for analysis, 41 of which were judged to be of moderate to high quality. Most wearable obstacle avoidance ETAs mainly depend on camera- and ultrasonic-based techniques to achieve perception of the environment. Acoustic feedback was the most common human-computer feedback form used by the ETAs. According to user experience, the efficacy and safety of the device was usually their primary concern. Conclusions Although many conceptualised ETAs have been designed to facilitate BVIs' independent navigation, most of these devices suffer from shortcomings. This is due to the nature and limitations of the various processors, environment detection techniques and human-computer feedback those ETAs are equipped with. Integrating multiple techniques and hardware into one ETA is a way to improve performance, but there is still a need to address the discomfort of wearing the device and the high-cost. Developing an applicable systematic review guideline along with a credible quality assessment tool for these types of studies is also required. © 2013 IEEE.
- Authors: Xu, Peijie , Kennedy, Gerard , Zhao, Fei-Yi , Zhang, Wen-Jing , Van Schyndel, Ron
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 66587-66613
- Full Text:
- Reviewed:
- Description: Background Wearable obstacle avoidance electronic travel aids (ETAs) have been developed to assist the safe displacement of blind and visually impaired individuals (BVIs) in indoor/outdoor spaces. This systematic review aimed to understand the strengths and weaknesses of existing ETAs in terms of hardware functionality, cost, and user experience. These elements may influence the usability of the ETAs and are valuable in guiding the development of superior ETAs in the future. Methods Formally published studies designing and developing the wearable obstacle avoidance ETAs were searched for from six databases from their inception to April 2023. The PRISMA 2020 and APISSER guidelines were followed. Results Eighty-nine studies were included for analysis, 41 of which were judged to be of moderate to high quality. Most wearable obstacle avoidance ETAs mainly depend on camera- and ultrasonic-based techniques to achieve perception of the environment. Acoustic feedback was the most common human-computer feedback form used by the ETAs. According to user experience, the efficacy and safety of the device was usually their primary concern. Conclusions Although many conceptualised ETAs have been designed to facilitate BVIs' independent navigation, most of these devices suffer from shortcomings. This is due to the nature and limitations of the various processors, environment detection techniques and human-computer feedback those ETAs are equipped with. Integrating multiple techniques and hardware into one ETA is a way to improve performance, but there is still a need to address the discomfort of wearing the device and the high-cost. Developing an applicable systematic review guideline along with a credible quality assessment tool for these types of studies is also required. © 2013 IEEE.
A fault-tolerant cascaded switched-capacitor multilevel inverter for domestic applications in smart grids
- Akbari, Ehsan, Teimouri, Ali, Saki, Mojtaba, Rezaei, Mohammad, Hu, Jiefeng, Band, Shahab, Pai, Hao-Ting, Mosavi, Amir
- Authors: Akbari, Ehsan , Teimouri, Ali , Saki, Mojtaba , Rezaei, Mohammad , Hu, Jiefeng , Band, Shahab , Pai, Hao-Ting , Mosavi, Amir
- Date: 2022
- Type: Text , Journal article
- Relation: IEEE Access Vol. 10, no. (2022), p. 110590-110602
- Full Text:
- Reviewed:
- Description: Cascaded multilevel inverters (MLIs) generate an output voltage using series-connected power modules that employ standard configurations of low-voltage components. Each module may employ one or more switched capacitors to double or quadruple its input voltage. The higher number of switched capacitors and semiconductor switches in MLIs compared to conventional two-level inverters has led to concerns about overall system reliability. A fault-tolerant design can mitigate this reliability issue. If one part of the system fails, the MLI can continue its planned operation at a reduced level rather than the entire system failing, which makes the fault tolerance of the MLI particularly important. In this paper, a novel fault location technique is presented that leads to a significant reduction in fault location detection time based on the reliability priority of the components of the proposed fault-tolerant switched capacitor cascaded MLI (CSCMLI). The main contribution of this paper is to reduce the number of MLI switches under fault conditions while operating at lower levels. The fault-tolerant inverter requires fewer switches at higher reliability, and the comparison with similar MLIs shows a faster dynamic response of fault detection and reduced fault location detection time. The experimental results confirm the effectiveness of the presented methods applied in the CSCMLI. Also, all experimental data including processor code, schematic, PCB, and video of CSCMLI operation are attached. © 2013 IEEE.
- Authors: Akbari, Ehsan , Teimouri, Ali , Saki, Mojtaba , Rezaei, Mohammad , Hu, Jiefeng , Band, Shahab , Pai, Hao-Ting , Mosavi, Amir
- Date: 2022
- Type: Text , Journal article
- Relation: IEEE Access Vol. 10, no. (2022), p. 110590-110602
- Full Text:
- Reviewed:
- Description: Cascaded multilevel inverters (MLIs) generate an output voltage using series-connected power modules that employ standard configurations of low-voltage components. Each module may employ one or more switched capacitors to double or quadruple its input voltage. The higher number of switched capacitors and semiconductor switches in MLIs compared to conventional two-level inverters has led to concerns about overall system reliability. A fault-tolerant design can mitigate this reliability issue. If one part of the system fails, the MLI can continue its planned operation at a reduced level rather than the entire system failing, which makes the fault tolerance of the MLI particularly important. In this paper, a novel fault location technique is presented that leads to a significant reduction in fault location detection time based on the reliability priority of the components of the proposed fault-tolerant switched capacitor cascaded MLI (CSCMLI). The main contribution of this paper is to reduce the number of MLI switches under fault conditions while operating at lower levels. The fault-tolerant inverter requires fewer switches at higher reliability, and the comparison with similar MLIs shows a faster dynamic response of fault detection and reduced fault location detection time. The experimental results confirm the effectiveness of the presented methods applied in the CSCMLI. Also, all experimental data including processor code, schematic, PCB, and video of CSCMLI operation are attached. © 2013 IEEE.
A new hybrid cascaded switched-capacitor reduced switch multilevel inverter for renewable sources and domestic loads
- Rezaei, Mohammad, Nayeripour, Majid, Hu, Jiefeng, Band, Shahab, Mosavi, Amir, Khooban, Mohammad-Hassan
- Authors: Rezaei, Mohammad , Nayeripour, Majid , Hu, Jiefeng , Band, Shahab , Mosavi, Amir , Khooban, Mohammad-Hassan
- Date: 2022
- Type: Text , Journal article
- Relation: IEEE Access Vol. 10, no. (2022), p. 14157-14183
- Full Text:
- Reviewed:
- Description: This multilevel inverter type summarizes an output voltage of medium voltage based on a series connection of power cells employing standard configurations of low-voltage components. The main problems of cascaded switched-capacitor multilevel inverters (CSCMLIs) are the harmful reverse flowing current of inductive loads, the large number of switches, and the surge current of the capacitors. As the number of switches increases, the reliability of the inverter decreases. To address these issues, a new CSCMLI is proposed using two modules containing asymmetric DC sources to generate 13 levels. The main novelty of the proposed configuration is the reduction of the number of switches while increasing the maximum output voltage. Despite the many similarities, the presented topology differs from similar topologies. Compared to similar structures, the direction of some switches is reversed, leading to a change in the direction of current flow. By incorporating the lowest number of semiconductors, it was demonstrated that the proposed inverter has the lowest cost function among similar inverters. The role of switched-capacitor inrush current in the selection of switch, diode, and DC source for inverter operation in medium and high voltage applications is presented. The inverter performance to supply the inductive loads is clarified. Comparison of the simulation and experimental results validates the effectiveness of the proposed inverter topology, showing promising potentials in photovoltaic, buildings, and domestic applications. A video demonstrating the experimental test, and all manufacturing data are attached. © 2013 IEEE.
- Authors: Rezaei, Mohammad , Nayeripour, Majid , Hu, Jiefeng , Band, Shahab , Mosavi, Amir , Khooban, Mohammad-Hassan
- Date: 2022
- Type: Text , Journal article
- Relation: IEEE Access Vol. 10, no. (2022), p. 14157-14183
- Full Text:
- Reviewed:
- Description: This multilevel inverter type summarizes an output voltage of medium voltage based on a series connection of power cells employing standard configurations of low-voltage components. The main problems of cascaded switched-capacitor multilevel inverters (CSCMLIs) are the harmful reverse flowing current of inductive loads, the large number of switches, and the surge current of the capacitors. As the number of switches increases, the reliability of the inverter decreases. To address these issues, a new CSCMLI is proposed using two modules containing asymmetric DC sources to generate 13 levels. The main novelty of the proposed configuration is the reduction of the number of switches while increasing the maximum output voltage. Despite the many similarities, the presented topology differs from similar topologies. Compared to similar structures, the direction of some switches is reversed, leading to a change in the direction of current flow. By incorporating the lowest number of semiconductors, it was demonstrated that the proposed inverter has the lowest cost function among similar inverters. The role of switched-capacitor inrush current in the selection of switch, diode, and DC source for inverter operation in medium and high voltage applications is presented. The inverter performance to supply the inductive loads is clarified. Comparison of the simulation and experimental results validates the effectiveness of the proposed inverter topology, showing promising potentials in photovoltaic, buildings, and domestic applications. A video demonstrating the experimental test, and all manufacturing data are attached. © 2013 IEEE.
Adaptation of a real-time deep learning approach with an analog fault detection technique for reliability forecasting of capacitor banks used in mobile vehicles
- Rezaei, Mohammad, Fathollahi, Arman, Rezaei, Sajad, Hu, Jiefeng, Gheisarnejad, Meysam, Teimouri, Ali, Rituraj, Rituraj, Mosavi, Amir, Khooban, Mohammad-Hassan
- Authors: Rezaei, Mohammad , Fathollahi, Arman , Rezaei, Sajad , Hu, Jiefeng , Gheisarnejad, Meysam , Teimouri, Ali , Rituraj, Rituraj , Mosavi, Amir , Khooban, Mohammad-Hassan
- Date: 2022
- Type: Text , Journal article
- Relation: IEEE Access Vol. 10, no. (2022), p. 132271-132287
- Full Text:
- Reviewed:
- Description: The DC-Link capacitor is defined as the essential electronics element which sources or sinks the respective currents. The reliability of DC-link capacitor-banks (CBs) encounters many challenges due to their usage in electric vehicles. Heavy shocks may damage the internal capacitors without shutting down the CB. The fundamental development obstacles of CBs are: lack of considering capacitor degradation in reliability assessment, the impact of unforeseen sudden internal capacitor faults in forecasting CB lifetime, and the faults consequence on CB degradation. The sudden faults change the CB capacitance, which leads to reliability change. To more accurately estimate the reliability, the type of the fault needs to be detected for predicting the correct post-fault capacitance. To address these practical problems, a new CB model and reliability assessment formula covering all fault types are first presented, then, a new analog fault-detection method is presented, and a combination of online-learning long short-term memory (LSTM) and fault-detection method is subsequently performed, which adapt the sudden internal CB faults with the LSTM to correctly predict the CB degradation. To confirm the correct LSTM operation, four capacitors degradation is practically recorded for 2000-hours, and the off-line faultless degradation values predicted by the LSTM are compared with the actual data. The experimental findings validate the applicability of the proposed method. The codes and data are provided. © 2013 IEEE.
- Authors: Rezaei, Mohammad , Fathollahi, Arman , Rezaei, Sajad , Hu, Jiefeng , Gheisarnejad, Meysam , Teimouri, Ali , Rituraj, Rituraj , Mosavi, Amir , Khooban, Mohammad-Hassan
- Date: 2022
- Type: Text , Journal article
- Relation: IEEE Access Vol. 10, no. (2022), p. 132271-132287
- Full Text:
- Reviewed:
- Description: The DC-Link capacitor is defined as the essential electronics element which sources or sinks the respective currents. The reliability of DC-link capacitor-banks (CBs) encounters many challenges due to their usage in electric vehicles. Heavy shocks may damage the internal capacitors without shutting down the CB. The fundamental development obstacles of CBs are: lack of considering capacitor degradation in reliability assessment, the impact of unforeseen sudden internal capacitor faults in forecasting CB lifetime, and the faults consequence on CB degradation. The sudden faults change the CB capacitance, which leads to reliability change. To more accurately estimate the reliability, the type of the fault needs to be detected for predicting the correct post-fault capacitance. To address these practical problems, a new CB model and reliability assessment formula covering all fault types are first presented, then, a new analog fault-detection method is presented, and a combination of online-learning long short-term memory (LSTM) and fault-detection method is subsequently performed, which adapt the sudden internal CB faults with the LSTM to correctly predict the CB degradation. To confirm the correct LSTM operation, four capacitors degradation is practically recorded for 2000-hours, and the off-line faultless degradation values predicted by the LSTM are compared with the actual data. The experimental findings validate the applicability of the proposed method. The codes and data are provided. © 2013 IEEE.