A Review and Bibliometric Analysis of the Current Studies for the 6G Networks

The race to develop the next generation of wireless networks,known as Sixth Generation(6G)wireless,which will be operational in 2030,has already begun.To realize its full potential over the next decade,6G will undoubtedly necessitate additional improvements that integrate existing solutions with cutting-edge ones.However,the studies about 6G are mainly limited and scattered,whereas no bibliometric study covers the 6G field.Thus,this study aims to review,examine,and summarize existing studies and research activities in 6G.This study has examined the Scopus database through a bibliometric analysis of more than 1,000 papers published between 2017 and 2021.Then,we applied the bibliometric analysis methods by including(1)document type,(2)subject area,(3)author,and(4)country of publication.The study’s results reflect the research 6G community’s trends,highlight important research challenges,and elucidate potential directions for future research in this interesting area.

Improving resource-constrained IoT device lifetimes by mitigating redundant transmissions across heterogeneous wireless multimedia of things

In Wireless Multimedia Sensor Networks(WMSNs),nodes capable of retrieving video,audio,images,and small scale sensor data,tend to generate immense traffic of various types.The energy-efficient transmission of such a vast amount of heterogeneous multimedia content while simultaneously ensuring the quality of service and optimal energy consumption is indispensable.Therefore,we propose a Power-Efficient Wireless Multimedia of Things(PE-WMoT),a robust and energy-efficient cluster-based mechanism to improve the overall lifetime of WMSNs.In a PE-WMoT,nodes declare themselves Cluster Heads(CHs)based on available resources.Once cluster formation and CH declaration processes are completed,the Sub-Cluster(SC)formation process triggers,in which application base nodes within close vicinity of each other organize themselves under the administration of a Sub-Cluster Head(SCH).The SCH gathers data from member nodes,removes redundancies,and forwards miniaturized data to its respective CH.PE-WMoT adopts a fuzzy-based technique named the analytical hierarchical process,which enables CHs to select an optimal SCH among available SCs.A PE-WMoT also devises a robust scheduling mechanism between CH,SCH,and child nodes to enable collision-free data transmission.Simulation results revealed that a PE-WMoT significantly reduces the number of redundant packet transmissions,improves energy consumption of the network,and effectively increases network throughput.

Explainable AI-Based DDoS Attacks Classification Using Deep Transfer Learning

In the era of the Internet of Things(IoT),the proliferation of connected devices has raised security concerns,increasing the risk of intrusions into diverse systems.Despite the convenience and efficiency offered by IoT technology,the growing number of IoT devices escalates the likelihood of attacks,emphasizing the need for robust security tools to automatically detect and explain threats.This paper introduces a deep learning methodology for detecting and classifying distributed denial of service(DDoS)attacks,addressing a significant security concern within IoT environments.An effective procedure of deep transfer learning is applied to utilize deep learning backbones,which is then evaluated on two benchmarking datasets of DDoS attacks in terms of accuracy and time complexity.By leveraging several deep architectures,the study conducts thorough binary and multiclass experiments,each varying in the complexity of classifying attack types and demonstrating real-world scenarios.Additionally,this study employs an explainable artificial intelligence(XAI)AI technique to elucidate the contribution of extracted features in the process of attack detection.The experimental results demonstrate the effectiveness of the proposed method,achieving a recall of 99.39%by the XAI bidirectional long short-term memory(XAI-BiLSTM)model.

A Review of Privacy and Security of Edge Computing in Smart Healthcare Systems: Issues, Challenges, and Research Directions

The healthcare industry is rapidly adapting to new computing environments and technologies. With academics increasingly committed to developing and enhancing healthcare solutions that combine the Internet of Things (IoT) and edge computing, there is a greater need than ever to adequately monitor the data being acquired, shared, processed, and stored. The growth of cloud, IoT, and edge computing models presents severe data privacy concerns, especially in the healthcare sector. However, rigorous research to develop appropriate data privacy solutions in the healthcare sector is still lacking. This paper discusses the current state of privacy-preservation solutions in IoT and edge healthcare applications. It identifies the common strategies often used to include privacy by the intelligent edges and technologies in healthcare systems. Furthermore, the study addresses the technical complexity, efficacy, and sustainability limits of these methods. The study also highlights the privacy issues and current research directions that have driven the IoT and edge healthcare solutions, with which more insightful future applications are encouraged.

Power Allocation in NOMA-CR for 5G Enabled IoT Networks

In the power domain,non-orthogonal multiple access(NOMA)supports multiple users on the same time-frequency resources,assigns different transmission powers to different users,and differentiates users by user channel gains.Multi-user signals are superimposed and transmitted in the power domain at the transmitting end by actively implementing controllable interference information,and multi-user detection algorithms,such as successive interference cancellation(SIC)is performed at the receiving end to demodulate the necessary user signals.In contrast to the orthogonal transmission method,the non-orthogonal method can achieve higher spectrum utilization.However,it will increase the receiver complexity.With the development of microelectronics technology,chip processing capabilities continue to increase,laying the foundation for the practical application of non-orthogonal transmission technology.In NOMA,different users are differentiated by different power levels.Therefore,the power allocation has a considerable impact on the NOMA system performance.To address this issue,the idea of splitting power into two portions,intra-subbands and intersubbands,is proposed in this study as a useful algorithm.Then,such optimization problems are solved using proportional fair scheduling and water-filling algorithms.Finally,the error propagation was modeled and analyzed for the residual interference.The proposed technique effectively increased the system throughput and performance under various operating settings according to simulation findings.A comparison is performed with existing algorithms for performance evaluation.

An efficient resource optimization scheme for D2D communication

With the rapid development of wireless technologies,wireless access networks have entered their Fifth-Generation(5G)system phase.The heterogeneous and complex nature of a 5G system,with its numerous technological scenarios,poses significant challenges to wireless resource management,making radio resource optimization an important aspect of Device-to-Device(D2D)communication in such systems.Cellular D2D communication can improve spectrum efficiency,increase system capacity,and reduce base station communication burdens by sharing authorized cell resources;however,can also cause serious interference.Therefore,research focusing on reducing this interference by optimizing the configuration of shared cellular resources has also grown in importance.This paper proposes a novel algorithm to address the problems of co-channel interference and energy efficiency optimization in a long-term evolution network.The proposed algorithm uses the fuzzy clustering method,which employs minimum outage probability to divide D2D users into several groups in order to improve system throughput and reduce interference between users.An efficient power control algorithm based on game theory is also proposed to optimize user transmission power within each group and thereby improve user energy efficiency.Simulation results show that these proposed algorithms can effectively improve system throughput,reduce co-channel interference,and enhance energy efficiency.