A Novel IoT Architecture, Assessment of Threats and Their Classification withMachine Learning Solutions

The Internet of Things(IoT)will significantly impact our social and economic lives in the near future.Many Internet of Things(IoT)applications aim to automate multiple tasks so inactive physical objects can behave independently of others.IoT devices,however,are also vulnerable,mostly because they lack the essential built-in security to thwart attackers.It is essential to perform the necessary adjustments in the structure of the IoT systems in order to create an end-to-end secure IoT environment.As a result,the IoT designs that are now in use do not completely support all of the advancements that have been made to include sophisticated features in IoT,such as Cloud computing,machine learning techniques,and lightweight encryption techniques.This paper presents a detailed analysis of the security requirements,attack surfaces,and security solutions available for IoT networks and suggests an innovative IoT architecture.The Seven-Layer Architecture in IoT provides decent attack detection accuracy.According to the level of risk they pose,the security threats in each of these layers have been properly categorized,and the essential evaluation criteria have been developed to evaluate the various threats.Also,Machine Learning algorithms like Random Forest and Support Vector Machines,etc.,and Deep Learning algorithms like Artificial Neural Networks,Q Learning models,etc.,are implemented to overcome the most damaging threats posing security breaches to the different IoT architecture layers.

Predictive cruise control for heavy trucks based on slope information under cloud control system

With the advantage of fast calculation and map resources on cloud control system(CCS), cloud-based predictive cruise control(CPCC) for heavy trucks has great potential to improve energy efficiency, which is significant to achieve the goal of national carbon neutrality. However, most investigations focus on the on-board predictive cruise control(PCC) system,lack of research on CPCC architecture under CCS. Besides, the current PCC algorithms have the problems of a single control target and high computational complexity, which hinders the improvement of the control effect. In this paper, a layered architecture based on CCS is proposed to effectively address the realtime computing of CPCC system and the deployment of its algorithm on vehicle-cloud. In addition, based on the dynamic programming principle and the proposed road point segmentation method(RPSM), a PCC algorithm is designed to optimize the speed and gear of heavy trucks with slope information. Simulation results show that the CPCC system can adaptively control vehicle driving through the slope prediction, with fuel-saving rate of 6.17% in comparison with the constant cruise control. Also,compared with other similar algorithms, the PCC algorithm can make the engine operate more in the efficient zone by cooperatively optimizing the gear and speed. Moreover, the RPSM algorithm can reconfigure the road in advance, with a 91% roadpoint reduction rate, significantly reducing algorithm complexity.Therefore, this study has essential research significance for the economic driving of heavy trucks and the promotion of the CPCC system.

Maritime Platform Facilities POB Plan Management Module Research and Development

There are many access ends and information asymmetry in the management of offshore platform production facility personnel information. In the actual business, the problem is decomposed and a multi-layer logical architecture is selected to design and develop the POB plan management module applicable to offshore platform facilities. The main functions of this module include task management, facility management, area management, sea-going unit management, plan management, report management, authority control, and comprehensive query. It can efficiently solve on-site business problems and improve the efficiency of POB plan management for various professionals on land and at sea. In actual use, the module can well assist in completing POB plan management tasks and improve work efficiency.

Symbols detection for frequency-selective V-BLAST OFDM systems

As the combining form of the orthogonal frequency-division multiplexing (OFDM) technique and the vertical Bell Labs layered space-time (V-BLAST) architecture, the V-BLAST OFDM system can better meet the demand of next-generation (NextG) broadband mobile wireless multimedia communications. The symbols detection problem of the V-BLAST OFDM system is investigated under the frequency-selective fading environment. The joint space-frequency demultiplexing operation is proposed in the V-BLAST OFDM system. Successively, one novel half-rate rotational invariance joint space-frequency coding scheme for the V-BLAST OFDM system is proposed. By elegantly exploiting the above rotational invariance property, we derive one direct symbols detection scheme without knowing channels state information (CSI) for the frequency-selective V-BLAST OFDM system. Extensive simulation results demonstrate the validity of the novel half-rate rotational invariance joint space-frequency coding scheme and the performance of the direct symbols detection scheme.

Improved BLAST for wireless communications

Bell layered space-time architecture （BLAST） is a multi-antenna communication structure with high spectrum efficiency, and it has found wide applications in LANs and WLANs. However, its performance is much poorer than those of other space-time coding approaches. In order to improve its performance, an improved BLAST based on RAKE receiving is investigated. The new system introduces orthogonal spreading sequences （OSS） into the transmitter while retains the basic structure of BLAST. The proposed receiver suppresses interferences from other antennas by the orthogonality contained in the received signals, and extracts information from each receiving antenna by using RAKE receiving principle to construct efficient statistic decision. Simulation results show that the improved system performs well over both frequency-fiat and frequency-selective fading channels.

Successive interference cancellation (SIC) in V-BLAST systems with asynchronous transmission mode

The V-BLAST system with asynchronous transmission mode first proposed by Shao can achieve full diversity only by using a simple linear detection scheme under zero forcing （ZF） criterion; therefore it gives a reasonable tradeoff between complexity and performance. In this paper, we propose two types of successive interference cancellation （SIC） detection schemes for the asynchronous V-BLAST system, one is characterized by applying Mr successive interference cancellators before a maximal ratio combiner （where Mr is the number of receive antennas）, and the other has a maximal ratio combiner before a successive interference cancellator. Since Type Ⅰ consumes more energy of the previously detected signals to recover a signal, Type Ⅱ can offer a better performance and simulations demonstrate its validity.