This letter proposes a cost-efficient convolutional neural network (CNN) for robust automatic modulation classification (AMC) deployed cognitive radio services of modern communication systems. The architecture is designed with several specific blocks to concurrently learn the spatiotemporal signal correlations via different asymmetric convolution kernels. Additionally, these are associated skip connections preserve more initially residual information at multi-scale feature maps and prevent...

The Physical Internet (PI, or π) paradigm has been developed to be a global logistics system that aims move, handle, store, and transport products in sustainable efficient way. To achieve the goal, PI requires high-level interconnectivity physical, informational, operational aspects enabled by an interconnected network of intermodal hubs, collaborative protocols, standardized, modular, smart containers. In this context, is key player poised benefit from Internet-of-Things (IoT) revolution...

In this letter, we propose an improved convolutional neural network (CNN)-based automatic modulation classification (IC-AMCNet), algorithm to classify the type of a wireless signal. Since adaptive coding and is widely used in communication, high accuracy short computing time classifier needed. Compared with existing CNN architectures, adjusted number layers added new comply estimated latency standards beyond fifth-generation (B5G) communications. According simulation results, proposed scheme...

Abstract The Metaverse is a concept used to refer virtual world that exists in parallel the physical world. It has grown from conceptual level having real applications reality games. applicability of numerous sectors like marketing, education, social, and even advertising exists. However, there little or no work on transportation industry. Data‐driven intelligent systems (DDITS) aim provide more based exploiting data. This paper reviews concepts features Metaverse. Also, review goes over...

In the IoT-based systems, fog computing allows nodes to offload and process tasks requested from IoT-enabled devices in a distributed manner instead of centralized cloud servers reduce response delay. However, achieving such benefit is still challenging systems with high rate requests, which imply long queues nodes, thus exposing probably an inefficiency terms latency tasks. addition, complicated heterogeneous degree environment introduces additional issue that many single fogs can not heavy...

Software-defined networking (SDN)-based Industrial Internet of Things (IIoT) networks have a centralized controller that is single attractive target for unauthorized users to attack. Cybersecurity in IIoT becoming the most significant challenge, especially from increasingly sophisticated Distributed Denial-of-Service (DDoS) attacks. This situation necessitates efficient approaches mitigate recent attacks following incompetence existing techniques focus more on DDoS detection. Most detection...

The Internet of Things (IoT) vision enables multiple resource-constrained embedded devices, objects, and humans to connect together through the protocol for a ubiquitous data exchange. Logistics is considered be key player poised from this achieve full visibility transparency leveraging pervasive interconnectivity collect reliable safe real-time data. In addition, valuable information extracted transformed IoT can exploited create intelligent services applications improve logistics...

In oceanic remote sensing operations, underwater acoustic target recognition is always a difficult and extremely important task of sonar systems, especially in the condition complex sound wave propagation characteristics. The expensively learning model for big data analysis typically an obstacle most traditional machine (ML) algorithms, whereas convolutional neural network (CNN), type deep network, can automatically extract features accurate classification. this study, we propose approach...

Recently, numerous methods have been introduced for three-dimensional (3-D) action recognition using handcrafted feature descriptors coupled traditional classifiers. However, they cannot learn high-level features of a whole skeleton sequence exhaustively. In this paper, novel encoding technique - namely, pose to image (PoF2I), is transform the joint-joint distance and orientation color pixels. By concatenating all frames in sequence, generated depict spatial joint correlations temporal...

This paper proposes a routing scheme that enhances energy consumption and end-to-end delay for large-scale Industrial Internet of Things (IIoT) systems based on IEEE 802.15.4a MAC. In the current IIoT, larger-scale complex deployment has been noticeable obstacle minimizing power real-time. Thus, proposed algorithm is targeted at where data are aggregated through different clusters their way to sink. Moreover, hierarchical system framework employed promote scalability IIoT elements. By...

Automatic modulation classification (AMC), which aims to blindly identify the type of an incoming signal at receiver in wireless communication systems, is a fundamental processing technique physical layer improve spectrum utilization efficiency.Motivated by deep learning (DL) high-impact success many informatics domains, including radio for communications, numerous recent AMC methods exploiting networks have been proposed overcome existing drawbacks traditional approaches.DL capable...

In the IoT-based systems, fog computing allows nodes to offload and process tasks requested from IoT-enabled devices in a distributed manner instead of centralized cloud servers reduce response delay. However, achieving such benefit is still challenging systems with high rate requests, which imply long queues nodes, thus exposing probably an inefficiency terms latency tasks. addition, complicated heterogeneous degree environment introduces additional issue that many single fogs can not heavy...

Automotive radars, with a widespread emergence in the last decade, have faced various jamming attacks. Utilizing low probability of intercept (LPI) radar waveforms, as one essential solutions, demands an accurate waveform recognizer at receiver. Numerous conventional approaches been studied for LPI recognition, but their performance is inadequate under channel condition deterioration. In this letter, by exploiting deep learning (DL) to capture intrinsic radio characteristics, we propose...

This paper proposes a convolutional neural network (CNN), called SCGNet, for low-complexity and robust modulation recognition in intelligent communication receivers. Principally, the combines two types of sparse layers-depthwise regular grouped an architecture to achieve high accuracy while keeping more lightweight. The leverages sparsely connected layers three principal modules: speed-accuracy tradeoff (SAT), deep feature extraction processing (DFEP), generic (GFE) data pre-processing...

The dynamic nature of the vehicular space exposes it to distributed malicious attacks irrespective integration enabling technologies. software-defined network (SDN) represents one these technologies, providing an integrated improvement over traditional ad-hoc (VANET). Due centralized characteristics SDN, they are vulnerable that may result in life-threatening situations. Securing SDN-based VANETs is vital and requires incorporating artificial intelligence (AI) techniques. Hence, this work...

Unmanned aerial vehicle (UAV) contributes substantial strategic benefits on the Internet of Military Things (IoMT). However, untrusted party's misuse UAV may violate security and even demolish critical operation in IoMT system. In addition, data manipulation falsification using unauthorized access are significant challenges response to this problem, study proposes a blockchain-integrated convolution neural network (CNN)-based intelligent framework named IoMT-Net for identification tracking...

Parked vehicle-assisted multi-access edge computing (PVMEC) is a paradigm that exploits the under-utilized resources of parked vehicles (PVs) to assist MEC servers for offloaded task execution. This article investigates partial offloading strategy multi-user PVMEC, where each mobile device (MD)'s can be partially server or nearby PV. We formulate system utility maximization problem with joint consideration decisions, ratio, and resource allocation. Considering complexity privacy issues...