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  • 1
    Online Resource
    Online Resource
    Non-Cooperative Learning Based Routing for 6G-IoT Cognitive Radio Network
    Computers, Materials and Continua (Tech Science Press) ; 2022
    In:  Intelligent Automation & Soft Computing Vol. 33, No. 2 ( 2022), p. 809-824
    Details
    In: Intelligent Automation & Soft Computing, Computers, Materials and Continua (Tech Science Press), Vol. 33, No. 2 ( 2022), p. 809-824
    Type of Medium: Online Resource
    ISSN: 1079-8587
    URL: Article
    DOI: 10.32604/iasc.2022.021128
    Language: English
    Publisher: Computers, Materials and Continua (Tech Science Press)
    Publication Date: 2022
    detail.hit.zdb_id: 2716453-6
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  • 2
    Online Resource
    Online Resource
    Comparison of Blackhole and Wormhole Attacks in Cloud MANET Enabled IoT for Agricultural Field Monitoring
    Hindawi Limited ; 2022
    In:  Security and Communication Networks Vol. 2022 ( 2022-4-29), p. 1-18
    Details
    In: Security and Communication Networks, Hindawi Limited, Vol. 2022 ( 2022-4-29), p. 1-18
    Abstract: In Mobile Ad hoc Network (MANET) enabled Internet of Things (IoT) agricultural field monitoring, sensor devices are automatically connected and form an independent network that serves as a cloud for many services such as monitoring, securing, and properly maintaining. Cloud-based services in MANET models can prove to be an extremely effective way of smart agricultural functionalities for device-to-device information exchange. Security is a serious issue with Cloud-MANET-based IoT since nodes are scattered, mobile, and lacking centralized administrator, which makes it possible for data tampering and illegal actions on cloud servers. Therefore, these types of networks are more vulnerable to Denial of Service (DoS) attacks such as Blackhole and Wormhole. The MANET Enabled IoT-Agricultural Field Monitoring environment is deployed through a case study. The effect of Blackhole and Wormhole attacks is analyzed using the Ad hoc On-demand Distance Vector (AODV) routing protocol with the help of Network Simulator 3 (NS-3) in order to determine which has the most impact on network performance. We computed performance constraints such as throughput, packet delivery ratio (PDR), end-to-end delay (EED), and Jitter-Sum of preprocessed data gathered with the flow-monitor module of NS-3. The effect of attacks on MANET Enabled IoT-Agricultural Field Monitoring is compared on the varying number of nodes participating in the Cloud-MANET-based IoT network. The throughput and goodput capability of every node is computed through the trace metric package. This method is also highly useful for future Cloud-MANET-Based IoT smart agricultural field security research.
    Type of Medium: Online Resource
    ISSN: 1939-0122 , 1939-0114
    URL: Article
    DOI: 10.1155/2022/4943218
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2415104-X
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  • 3
    Online Resource
    Online Resource
    RL-IoT: Reinforcement Learning-Based Routing Approach for Cognitive Radio-Enabled IoT Communications
    Institute of Electrical and Electronics Engineers (IEEE) ; 2023
    In:  IEEE Internet of Things Journal Vol. 10, No. 2 ( 2023-1-15), p. 1836-1847
    Details
    In: IEEE Internet of Things Journal, Institute of Electrical and Electronics Engineers (IEEE), Vol. 10, No. 2 ( 2023-1-15), p. 1836-1847
    Type of Medium: Online Resource
    ISSN: 2327-4662 , 2372-2541
    URL: Article
    DOI: 10.1109/JIOT.2022.3210703
    Language: Unknown
    Publisher: Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2023
    detail.hit.zdb_id: 2751199-6
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  • 4
    Online Resource
    Online Resource
    E-Learning Development Based on Internet of Things and Blockchain Technology during COVID-19 Pandemic
    MDPI AG ; 2021
    In:  Mathematics Vol. 9, No. 24 ( 2021-12-07), p. 3151-
    Details
    In: Mathematics, MDPI AG, Vol. 9, No. 24 ( 2021-12-07), p. 3151-
    Abstract: The suspension of institutions around the world in early 2020 due to the COVID-19 virus did not stop the learning process. E-learning concepts and digital technologies enable students to learn from a safe distance while continuing their educational pursuits. Currently, the Internet of Things (IoT) is one of the most rapidly increasing technologies in today’s digital world; and e-learning is one of the most powerful learning methods available. In today’s world, smart devices and new technologies assist teachers in concentrating on new models of student learning while avoiding time wastage. By examining the characteristics of the Internet of Things and the challenges that exist in the field of e-learning, the potential functions, benefits, and advancements of utilizing the Internet of Things in online education are identified and discussed. This article examines the existing and future condition of the Internet of Things world as it pertains to the topic of education and sophisticated capabilities available through the Internet of Things that enable the application of e-learning after an architecture has been designed. Students’ pulse rates, brain waves, and skin resistance are measured in real time by a collection of IoT sensors, including cameras, microphones, and wearable gadgets. By utilizing the proposed architecture, universities can change their distance learning tactics to maximize resources and boost efficiency without changing their overall academic activities. According to the study’s findings, e-learning has a favorable and statistically significant impact on students’ flexibility, learning experience, educational productivity, and overall quality of education.
    Type of Medium: Online Resource
    ISSN: 2227-7390
    URL: Article
    DOI: 10.3390/math9243151
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2704244-3
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  • 5
    Online Resource
    Online Resource
    Automated Brain Hemorrhage Classification and Volume Analysis
    Computers, Materials and Continua (Tech Science Press) ; 2023
    In:  Computers, Materials & Continua Vol. 75, No. 1 ( 2023), p. 2283-2299
    Details
    In: Computers, Materials & Continua, Computers, Materials and Continua (Tech Science Press), Vol. 75, No. 1 ( 2023), p. 2283-2299
    Type of Medium: Online Resource
    ISSN: 1546-2226
    URL: Article
    DOI: 10.32604/cmc.2023.030706
    Language: English
    Publisher: Computers, Materials and Continua (Tech Science Press)
    Publication Date: 2023
    detail.hit.zdb_id: 2227467-4
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  • 6
    Online Resource
    Online Resource
    Deep Learning Approach for Automatic Microaneurysms Detection
    MDPI AG ; 2022
    In:  Sensors Vol. 22, No. 2 ( 2022-01-11), p. 542-
    Details
    In: Sensors, MDPI AG, Vol. 22, No. 2 ( 2022-01-11), p. 542-
    Abstract: In diabetic retinopathy (DR), the early signs that may lead the eyesight towards complete vision loss are considered as microaneurysms (MAs). The shape of these MAs is almost circular, and they have a darkish color and are tiny in size, which means they may be missed by manual analysis of ophthalmologists. In this case, accurate early detection of microaneurysms is helpful to cure DR before non-reversible blindness. In the proposed method, early detection of MAs is performed using a hybrid feature embedding approach of pre-trained CNN models, named as VGG-19 and Inception-v3. The performance of the proposed approach was evaluated using publicly available datasets, namely “E-Ophtha” and “DIARETDB1”, and achieved 96% and 94% classification accuracy, respectively. Furthermore, the developed approach outperformed the state-of-the-art approaches in terms of sensitivity and specificity for microaneurysms detection.
    Type of Medium: Online Resource
    ISSN: 1424-8220
    URL: Article
    DOI: 10.3390/s22020542
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2052857-7
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  • 7
    Online Resource
    Online Resource
    Reinforcement Learning-Based Routing Protocol to Minimize Channel Switching and Interference for Cognitive Radio Networks
    Hindawi Limited ; 2020
    In:  Complexity Vol. 2020 ( 2020-08-13), p. 1-24
    Details
    In: Complexity, Hindawi Limited, Vol. 2020 ( 2020-08-13), p. 1-24
    Abstract: In the existing network-layered architectural stack of Cognitive Radio Ad Hoc Network (CRAHN), channel selection is performed at the Medium Access Control (MAC) layer. However, routing is done on the network layer. Due to this limitation, the Secondary/Unlicensed Users (SUs) need to access the channel information from the MAC layer whenever the channel switching event occurred during the data transmission. This issue delayed the channel selection process during the immediate routing decision for the channel switching event to continue the transmission. In this paper, a protocol is proposed to implement the channel selection decisions at the network layer during the routing process. The decision is based on past and expected future routing decisions of Primary Users (PUs). A learning agent operating in the cross-layer mode of the network-layered architectural stack is implemented in the spectrum mobility manager to pass the channel information to the network layer. This information is originated at the MAC layer. The channel selection is performed on the basis of reinforcement learning algorithms such as No-External Regret Learning, Q -Learning, and Learning Automata. This leads to minimizing the channel switching events and user interferences in the Reinforcement Learning- (RL-) based routing protocol. Simulations are conducted using Cognitive Radio Cognitive Network simulator based on Network Simulator (NS-2). The simulation results showed that the proposed routing protocol performed better than all the other comparative routing protocols in terms of number of channel switching events, average data rate, packet collision, packet loss, and end-to-end delay. The proposed routing protocol implies the improved Quality of Service (QoS) of the delay sensitive and real-time networks such as Cellular and Tele Vision (TV) networks.
    Type of Medium: Online Resource
    ISSN: 1076-2787 , 1099-0526
    URL: Article
    DOI: 10.1155/2020/8257168
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2020
    detail.hit.zdb_id: 2004607-8
    SSG: 11
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  • 8
    Online Resource
    Online Resource
    An Efficient Algorithm to Enhance Nonoverlapping Coverage Area with Less Energy Consumption in WSN
    Hindawi Limited ; 2022
    In:  Wireless Communications and Mobile Computing Vol. 2022 ( 2022-12-12), p. 1-12
    Details
    In: Wireless Communications and Mobile Computing, Hindawi Limited, Vol. 2022 ( 2022-12-12), p. 1-12
    Abstract: Several chargeable sensor nodes are deployed randomly to cover the target points with an efficient heuristic approach for the mobility of sensor nodes in an area of interest (AoI). The heuristic approach generates the cover set that includes the targets for a prolonged time. The cover sets are the subset of the total sensor node area where each set is capable of representing all the targets. The functionality of the sensor nodes depends upon the network lifetime of the target points covering an AoI. The network lifetime would improve by reducing the consumption of battery power through heuristic process. The proposed heuristic process can do this by generating cover sets and selecting sensor nodes with the highest remaining battery power. These cover sets remove the redundant sensor node in an AoI that causes the overlapping issue and assign the maximum lifetime which is the minimum amount of battery power of the sensor node, participating in the cover set. The results show the improvement in the mobility of sensor nodes by coverage and attain maximum network lifetime as compared to the existing algorithms.
    Type of Medium: Online Resource
    ISSN: 1530-8677 , 1530-8669
    URL: Article
    DOI: 10.1155/2022/7459824
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2045240-8
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  • 9
    Online Resource
    Online Resource
    Efficient Joint Key Authentication Model in E-Healthcare
    Computers, Materials and Continua (Tech Science Press) ; 2022
    In:  Computers, Materials & Continua Vol. 71, No. 2 ( 2022), p. 2739-2753
    Details
    In: Computers, Materials & Continua, Computers, Materials and Continua (Tech Science Press), Vol. 71, No. 2 ( 2022), p. 2739-2753
    Type of Medium: Online Resource
    ISSN: 1546-2226
    URL: Article
    DOI: 10.32604/cmc.2022.022706
    Language: English
    Publisher: Computers, Materials and Continua (Tech Science Press)
    Publication Date: 2022
    detail.hit.zdb_id: 2227467-4
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  • 10
    Online Resource
    Online Resource
    An Efficient and Secure Fog Based Routing Mechanism in IoT Network
    MDPI AG ; 2023
    In:  Mathematics Vol. 11, No. 17 ( 2023-08-24), p. 3652-
    Details
    In: Mathematics, MDPI AG, Vol. 11, No. 17 ( 2023-08-24), p. 3652-
    Abstract: The Internet of Things (IoT) networks are the most prone to internal as well as external attacks in addition to energy consumption problems. Conventional security solutions are not able to address these issues effectively due to the limited resources of sensor nodes participating in IoT communications. In this work, an Efficient and Secure Fog Based Routing Mechanism (ESFRM) is proposed to protect the network from faulty internal as well as external attacks. Every node participating in IoT communications calculates the comprehensive trust value of the next intermediate node which is the addition of direct trust, indirect trust and energy trust values before forwarding the data. This comprehensive trust value is then compared with the comprehensive threshold trust value to decide whether the particular node is a rogue node or a valid normal node. Further, an enhanced RSA (Rivest, Shamir, Adleman) algorithm is implemented to provide three levels of data security from Cluster Head (CH) to fog node, from fog node to cloud server and directly from CH to cloud server. For this purpose, an efficient CH selection technique is also proposed in this work. The proposed methodology is compared with the Secure Energy-efficient Fog-based Routing (SEFR) protocol and Trust-aware Secure Routing Protocol (TSRP). The evaluation results show that the proposed ESFRM outperforms the conventional schemes with respect to energy consumption, malicious node detection and transmission rate.
    Type of Medium: Online Resource
    ISSN: 2227-7390
    URL: Article
    DOI: 10.3390/math11173652
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2704244-3
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