The Internet of Things (IoT) is basically like a system for connecting computer devices, mechanical and digital machines, objects, or individuals provided with the unique system (UIDs) and without transfer to transmit data over an ability human-to-human or computer-to-human relation. Another thing on the internet is that the items in the IoT are like a connected manner with humans and computers to which internet protocol addresses can be assigned and which can transfer data over the network or another man-made object. In this paper, we describe the utilization of IoT in the cloud, fog, IoT technologies with applications and security. Specifically, we provide IoT architecture for design and development with sensors in 6G. Finally, we discuss the current research, solutions, and present open issues of future research in IoT.

A Review and State of Art of Internet of Things (IoT)

A 5G wireless network requires an efficient approach to effectively manage and segment the resource. A Centralized Radio Access Network (CRAN) is used to handle complex distributed networks. Specific to network infrastructure, multicast communication is considered in the performance of data storage and information-based network connectivity. This paper proposes a modified Resource Allocation (RA) scheme for effectively handling the RA problem using a learning-based Resource Segmentation (RS) technique. It uses a modified Random Forest Algorithm (RFA) with Signal Interference and Noise Ratio (SINR) and position coordinates to obtain the position coordinates of end-users. Further, it predicts Modulation and Coding Schemes (MCS) for establishing a connection between the end-user device and the Remote Radio Head (RRH). The proposed algorithm depends on the accuracy of positional coordinates for the correctness of the input parameters, such as SINR, based on the position and orientation of the antenna. The simulation analysis renders the efficiency of the proposed technique in terms of throughput and energy efficiency.

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Effective Resource Allocation Technique to Improve QoS in 5G Wireless Network

A wireless network is used to connect various wired organizational structures and provide connectivity within the organization for employees to move freely by avoiding the hurdle of a physical network. Maintenance of WLAN security is crucial to an organization because WLANs are directly linked to the core organization’s network. In this paper, we reviewed the architectures and protocols of wireless communication, security issues, and type of threats used to launch an attack as well as their solutions. Finally, we discuss open research for future development to make a secure wireless network and safe for data transfer.

Survey on Wireless Network Security

The enterprise educational environment will involve big data technology, cloud computing, Internet of Things (IoT) and artificial intelligence (AI), which will characterize the current society extreme automation and enterprise productivity through reinventing the new world educational reform. This current paper captured the manageability issues in electronic learning environments and explored ways through which the managerial performances could be improved in the perspective of electronic learning investments through incorporation of context-awareness and self-reconfiguration adaptive systems. The aim is to allow the open source electronic learning system to provide educators, administrators, and learners with a single robust and integrated system for creating a personalized and autonomous learning accomplishments. The paper reviewed the contemporary development in electronic learning system in internet of things and cloud computing and established the prospect for the continued educational investment. A survey of four tertiary institution in the south eastern Nigeria provided a justification for the adoption of cloud computing technology as the best alternative approach for organizational data warehousing in the ongoing society automation. The result of the paper indicated that technology implementation in schools are fundamental to students’ academic accomplishment, which made it obviously imperative that teachers in the 21st century should adjust digitally and technologically and prepare students for the opportunities in the emerging digital new world. The paper concluded that the successful curriculum implementation in the twenty first century will require a blend of technology innovation and enterprise platform adaptability as potential leverages in achieving the global educational sustainability.

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Contemporary Development in E-Learning Education, Cloud Computing Technology & Internet of Things

Network intrusion anomaly detection technique has been widely employed in computer network environments as a highly effective security prevention method. As network technology and network applications have advanced at a rapid pace, so too has network data traffic, resulting in an increase in virus and attack kinds. In the face of large-scale traffic and characteristic information, traditional intrusion detection will have problems such as low detection accuracy, high false negatives, and reliance on dimensionality reduction algorithms. Therefore, it is particularly important to establish a fast and efficient network intrusion anomaly detection method to deal with the current complex network environment. This work designs a computer network intrusion detection model with a recurrent neural network in order to explore a new intrusion detection method. The main purpose of this article include the following: (1) design a network security emergency response system architecture with the recurrent neural network model. This system consists of a management center module, a knowledge database module, a data acquisition module, a risk detection tool module, a risk analysis and processing module, a data protection module, and a remote connection auxiliary module. The modules cooperate with each other to complete system functions. (2) Aiming at the risk analysis and processing module, a network intrusion detection model combining bidirectional long short-term memory (BiLSTM) and deep neural network (DNN) is designed. In view of the lack of consideration of the before-and-after relevance of intrusion data features and the multifeature problem in existing models, the use of BiLSTM to extract the relevance between features and the use of DNN to extract deeper features are proposed. Aiming at the problem that the model lacks consideration of the importance of features, it is proposed to embed an attention mechanism into the network to increase consideration for the importance of features. (3) Massive experiments have verified the reliability and effectiveness of the method proposed in this work.

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Computer Network Intrusion Anomaly Detection with Recurrent Neural Network

In recent years, cloud computing is an emergent field in the Internet era. There is rapid development in high-performance computing and technology extended from grid computing to cloud computing to provide computing resources on pay per basis. Cloud service providers developed applications for users to easily access cloud services with quality of service (QoS) because cloud application plays an important role in service delivery of cloud organization. This paper provides a review of cloud computing technology, cloud models, deployment and cloud applications such as types of applications, reliability, and security. Finally, open research issues are provided for future research development.

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Rashid Nazir

Papers

Cloud Computing Applications: A Review

Survey on Wireless Network Security