ICT Express最新文献

Like numerous new websites created globally every day on the web, new spaces are constantly produced in the metaverse and interconnected to each other through the Internet. The continuous expansion of the metaverse space requires a search system that supports efficiently navigating and retrieving globally distributed spaces. Current metaverse search systems are limited to text-based retrieval within local platforms, and web search systems have critical limitations to apply to the metaverse. In this study, we propose an architecture for a metaverse search system that overcomes these limitations, enabling global space search across the distributed metaverse. We analyze the gaps between the web and the metaverse, identify challenges and technologies in developing a metaverse search system, and explore potential applications from different user perspectives. This study sets the foundation for a seamless browsing experience in the metaverse, enabling users to navigate three-dimensional spaces easily and freely, similar to surfing the traditional web.

Cyber threats increasingly target mission-critical systems in the military and private sectors. CMIA has emerged to mitigate such cyber threats and assure the resilience of critical missions. Existing approaches merely provide partial, manual analysis methods to support CMIA and lack the ability to provide optimal defense measures. In this paper, we propose a novel CMIA framework enabling a streamlined, automated CMIA procedure, based on the Bayesian Stackelburg game. Unlike conventional approaches, our framework provides the most probable cyber threat and the optimal defense, i.e., countermeasures against the cyber threat in a given mission environment, securing the resilience of mission-critical systems.

In 1997, the US National Science Foundation recognized the need to unite research communities together to solve mutual problems, overcome challenges, future development and practical applications of cryptography and error correction coding. Recent works in this area are connected with turbo codes, which have a special ability to provide error correction characteristics of the information transmission close to theoretically obtained values. Besides, they are used for television (DVB-RCS, DVB-RCT), wireless local networks (WiMAX), software-defined radio systems, mobile (3G, 4G, Inmarsat) and space (CCSDS) communications etc. In this article is presented the crypto coding system based on turbo codes with secret keys used by interleavers. All calculations are performed during data encoding, which reduces the computational complexity of data pre-encryption. The necessary mathematical apparatus was presented, the security level of the communication system was estimated, a simulation of the error correction characteristics was performed, and multimedia information was processed. The working characteristics of the classical and proposed turbo codecs do not differ statistically. The results can be used in communication systems for various functional purposes.

In this paper, we will consider the problem of multi-unmanned aerial vehicles (UAVs) deployment among users’ hotspots. UAVs carry reconfigurable intelligent surface (RIS) boards to strengthen millimeter wave (mmWave) coverage at these hotspots. UAVs should maximize hotspots’ sum data rates while minimizing their flights’ cost, i.e., hovering and flying energy consumptions. Moreover, collisions should be avoided among UAVs, i.e., one hotspot should be served by only one UAV at a time. In this paper, this problem is considered as a multi-player multi-armed bandit (MP-MAB) game with budget constraint and collision avoidance. In this context, budget constraint Thompson sampling (TS) with collision avoidance MAB algorithm (BTSCA-MAB) is proposed to efficiently implement the formulated MP-MAB game. Numerical analysis confirms the superior performance of the proposed BTSCA-MAB over other benchmarks.

Note that 40% of the world’s population, $i.e.,$ three billion people, live within 100 km of the ocean or seashore surfaces. To explore and experience marine life, human activities in ocean-based environments are increasing day-by-day. To make human activities safer and stronger, highly efficient and reliable wireless communication is crucial for conveying any unnatural things that occur in oceans. Exploring the vast environment is difficult because of its rapidly changing characteristics, which creates various levels of skip-zone, resulting in the loss of information. A re-configurable intelligent surface (RIS)-assisted optical link is employed to mitigate the effects of skip-zones and enable high-speed and efficient communication links. In addition to this, it is also necessary to convey information to the coastal line through a RIS-assisted free-space optical (FSO) link. In this study, we propose a RIS-assisted dual-hop underwater wireless optical communication (UWOC)-FSO communication system. For the proposed RIS-based dual-hop UWOC-FSO system, closed-form expressions for the outage probability (OP), bit error rate (BER) for coherent and non-coherent type binary phase-shift keying, binary frequency shift keying modulation schemes are derived and results are corroborated with the Monte-Carlo simulations and asymptotic analysis.

Due to the complex functioning of Smart Healthcare Systems (SHS), many security concerns have been raised in the past. It provisions the attackers to hamper the working of SHS in a variety of ways, e.g., injection of false data to replace vital signs, tampering of medical devices to prevent informing critical situations, etc. In this work, a novel ML-based framework, i.e., SmartHealth is proposed to secure IoMT devices in SHS. SmartHealth watches the vital signs gathered through different IoMT to analyze the change in various body activities to differentiate between normal activities and dangerous security attacks. The performance of the SmartHealth is also analyzed for three different dangerous attacks. During performance analysis, it has been observed that SmartHealth can identify wicked activities in IoMT 92% times accurately with an F1-score of 90%.

Maintaining a service continuum is crucial for providing a reliable service in an Internet-of-Things (IoT) system based on Network Function Virtualization (NFV) due to the distribution of Virtual Network Functions (VNF). We address the optimization problem of VNF migration in an NFV-enabled IoT system (NIoT), considering the dynamics of traffic volume processed by an individual IoT function. We develop an optimization model based on integer linear programming and a function traffic-aware heuristic algorithm to solve the problem. The evaluation results show that our proposed heuristic algorithm offers an approximation solution very close to the optimal VNF migration in significantly reduced time. It outperforms a benchmark solution based on Simulated Annealing in both the service restoration cost and computation time. Furthermore, our findings provide valuable insights into an investment strategy for an IoT service provider seeking to enhance the system performance in the presence of a failure.

In this paper, we propose and analyze an unmanned aerial vehicle (UAV)-assisted non-orthogonal multiple access (NOMA) short packet communication (SPC) system, where finite-size data packets are transmitted from a UAV to multiple users. The block error rate (BLER), throughput, and energy efficiency (EE) are used as metrics to evaluate the proposed system performance. We adopt the Gaussian-Chebyshev quadrature and the first-order Riemann integral to derive the approximate expressions of BLERs. The accuracy of the derived expressions is verified by presenting that numerical results are perfectly matched with analysis results. We also formulate optimization problems to maximize the throughput with respect to the number of transmitted bits and the altitude of the UAV. Numerical results in this paper provide useful knowledge about the relationships among BLER, throughput, EE, transmitted packet size, the altitude of the UAV, and the Rician factor.

This work investigates the problem of efficient packet scheduling and transmission for IEEE 802.15.4e TSCH based on the Traffic-Aware Scheduling Algorithm (TASA). Three Integer Linear Programming (ILP) formulations are proposed, namely ILP1, ILP2, and ILP3, to comprehensively address key aspects of how packets are optimally delivered from child nodes to the root node, including node parent selection, packet scheduling, and frequency assignment. ILP1 is proposed to model the fundamental operations of TASA including packet scheduling and frequency assignment, while ILP2 further takes node parent selection into consideration for jointly optimizing node parent selection, packet scheduling, and frequency assignment. Despite its superior performance, ILP2 is only applicable to relatively small network problems due to high computational complexity. Therefore, we finally propose ILP3 for fast and efficient node parent selection. ILP3 can be combined with ILP1 and, most importantly, TASA for achieving effective node parent selection atop packet scheduling and frequency assignment for practical TSCH networks. ILP3 combined with ILP 1 led to computational complexity while ILP3 combined with TASA yielded good performance where it required less than one second of execution time and less packet delivery time.

This paper presents bidirectional encoder representations from transformers (BERT)-based deep learning model for the classification of scientific articles. This model aims to increase the efficiency and reliability of human health risk assessments related to electromagnetic fields (EMF). The proposed model takes the title and abstract of EMF-related articles and classifies them into four categories: animal exposure experiment, cell exposure experiment, human exposure experiment, and epidemiological study. We conducted a performance evaluation to verify the superiority of the proposed model. The results demonstrated that the proposed model outperforms other deep learning models that use pre-trained embeddings, with an average accuracy of 98.33%.