An intelligent sustainable efficient transmission internet protocol to switch between <scp>User Datagram Protocol</scp> and <scp>Transmission Control Protocol</scp> in <scp>IoT</scp> computing

Khaniabadi, Shadi Mahmoodi; Javadpour, Amir; Gheisari, Mehdi; Zhang, Weizhe; Liu, Yang; Sangaiah, Arun Kumar

doi:10.1111/exsy.13129

Cited by 16 publications

(13 citation statements)

References 20 publications

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“…There are many theoretical models concerning the communication effect of games as media [ 51 ]. The computer networking concept was adopted as the inspiration for this research based on the idea of engineering.…”

Section: Methodsmentioning

confidence: 99%

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A Serious Game (“Fight With Virus”) for Preventing COVID-19 Health Rumors: Development and Experimental Study

Xiong,

Zuo,

Chen

et al. 2024

JMIR Serious Games

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Background Health rumors arbitrarily spread in mainstream social media on the internet. Health rumors emerged in China during the outbreak of COVID-19 in early 2020. Many midelders/elders (age over 40 years) who lived in Wuhan believed these rumors. Objective This study focused on designing a serious game as an experimental program to prevent and control health rumors. The focus of the study was explicitly on the context of the social networking service for midelders/elders. Methods This research involved 2 major parts: adopting the Transmission Control Protocol model for games and then, based on the model, designing a game named “Fight With Virus” as an experimental platform and developing a cognitive questionnaire with a 5-point Likert scale. The relevant variables for this experimental study were defined, and 10 hypotheses were proposed and tested with an empirical study. In total, 200 participants were selected for the experiments. By collecting relevant data in the experiments, we conducted statistical observations and comparative analysis to test whether the experimental hypotheses could be proved. Results We noted that compared to traditional media, serious games are more capable of inspiring interest in research participants toward their understanding of the knowledge and learning of health commonsense. In judging and recognizing the COVID-19 health rumor, the test group that used game education had a stronger ability regarding identification of the rumor and a higher accuracy rate of identification. Results showed that the more educated midelders/elders are, the more effective they are at using serious games. Conclusions Compared to traditional media, serious games can effectively improve midelders’/elders’ cognitive abilities while they face a health rumor. The gameplay effect is related to the individual’s age and educational background, while income and gender have no impact.

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Section: Methodsmentioning

confidence: 99%

“…The computer networking concept was adopted as the inspiration for this research based on the idea of engineering. Two main protocols exist in network communication: Transmission Control Protocol (TCP) and User Datagram Protocol (UDP) [ 51 ]. TCP originated in the initial network implementation, complementing Internet Protocol (IP).…”

Section: Methodsmentioning

confidence: 99%

A Serious Game (“Fight With Virus”) for Preventing COVID-19 Health Rumors: Development and Experimental Study

Xiong,

Zuo,

Chen

et al. 2024

JMIR Serious Games

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“…IoT consists of various info-communication technologies that enable its operation. Its architecture has a multi-level structure and reflects the relationship between these technologies [13]. There are architectures with different numbers of layers, as shown in Fig.…”

Section: A Architecture Of the Internet Of Thingsmentioning

confidence: 99%

Network Attack Detection Using NeuroEvolution of Augmenting Topologies (NEAT) Algorithm

Zhukabayeva,

Adamova,

Ven-Tsen

et al. 2024

JOIV : Int. J. Inform. Visualization

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The imperfection of existing intrusion detection methods and the changing nature of malicious actions on the attacker's part led to the Internet of Things (IoT) network interaction in an unsafe state. The actual problem of improving the technology of the IOT is counteracting malicious network impacts. In this regard, research and development aimed at creating effective tools for solving applied problems within the framework of this problem are becoming increasingly important. This study seeks to develop tools for detecting anomalous network conditions resulting from malicious attacks. In particular, the accuracy of the identification of DoS and DDoS attacks is sufficient for operational use. This study analyzes various multi-level architectures, relevant communication protocols, and different types of network attacks. The presented research was conducted on open datasets TON_IOT DATASETS, which include multiple data sources collected from IoT sensors. The modified HyperNEAT algorithm was used as the basis for the development. The NEAT methodology used in the study allows you to combine various network nodes. Results of the study: a neuro-evolutionary algorithm for identifying DoS and DDoS attacks was implemented, integrated, and real-tested based on a multi-level analysis of network traffic combined with various adaptive modules. The accuracy of identifying DoS and DDoS attacks is 0.9242 in the Accuracy metric. The study implies that the proposed approach can be recommended for network intrusion detection, ensuring security when interacting with the IoT.

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“…Data preprocessing stands as a cornerstone in the realm of data analytics and machine learning, pivotal in refining raw data into a more digestible and analyzable format, enhancing the efficacy of subsequent operations [46]. This transformative process encompasses several stages, each critical to enhancing the data's quality and, consequently, the outcomes derived from it [47][48][49]. The stages integral to data preprocessing include: Data Cleaning: This initial stage addresses the dataset's hygiene, identifying and rectifying missing, incomplete, or irrelevant records and anomalies.…”

Section: Data Preparationmentioning

confidence: 99%

Development of an Intelligent Service Delivery System to Increase Efficiency of Software Defined Networks

Joldasbayev,

Sapakova,

Zhaksylyk

et al. 2023

IJACSA

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The burgeoning complexity in network management has garnered considerable attention, specifically focusing on Software-Defined Networking (SDN), a transformative technology that addresses limitations inherent in traditional network infrastructures. Despite its advantages, SDN is often susceptible to bottlenecks and excessive load issues, underscoring the necessity for more robust load balancing solutions. Previous research in this realm has predominantly concentrated on employing static or dynamic methodologies, encapsulating only a handful of parameters for traffic management, thereby limiting their effectiveness. This study introduces an innovative, intelligence-led approach to service delivery systems in SDN, specifically by orchestrating packet forwarding-encompassing both TCP and UDP traffic-through a multi-faceted analysis utilizing twelve distinct parameters elaborated in subsequent sections. This research leverages advanced machine learning algorithms, notably K-Means and DBSCAN clustering, to discern patterns and optimize traffic distribution, ensuring a more nuanced, responsive load balancing mechanism. A salient feature of this methodology involves determining the ideal number of operational clusters to enhance efficiency systematically. The proposed system underwent rigorous testing with an escalating scale of network packets, encompassing counts of 5,000 to an extensive 10,000,000, to validate performance under varying load conditions. Comparative analysis between K-Means and DBSCAN's results reveals critical insights into their operational efficacy, corroborated by juxtaposition with extant scholarly perspectives. This investigation's findings significantly contribute to the discourse on adaptive network solutions, demonstrating that an intelligent, parameter-rich approach can substantively mitigate load-related challenges, thereby revolutionizing service delivery paradigms within Software-Defined Networks.

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An intelligent sustainable efficient transmission internet protocol to switch between User Datagram Protocol and Transmission Control Protocol in IoT computing

Cited by 16 publications

References 20 publications

A Serious Game (“Fight With Virus”) for Preventing COVID-19 Health Rumors: Development and Experimental Study

A Serious Game (“Fight With Virus”) for Preventing COVID-19 Health Rumors: Development and Experimental Study

Network Attack Detection Using NeuroEvolution of Augmenting Topologies (NEAT) Algorithm

Development of an Intelligent Service Delivery System to Increase Efficiency of Software Defined Networks

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