An improved pulse coupled neural networks model for semantic IoT

In recent years,the Internet of Things(IoT)has gradually developed applications such as collecting sensory data and building intelligent services,which has led to an explosion in mobile data traffic.Meanwhile,with the rapid development of artificial intelligence,semantic communication has attracted great attention as a new communication paradigm.However,for IoT devices,however,processing image information efficiently in real time is an essential task for the rapid transmission of semantic information.With the increase of model parameters in deep learning methods,the model inference time in sensor devices continues to increase.In contrast,the Pulse Coupled Neural Network(PCNN)has fewer parameters,making it more suitable for processing real-time scene tasks such as image segmentation,which lays the foundation for real-time,effective,and accurate image transmission.However,the parameters of PCNN are determined by trial and error,which limits its application.To overcome this limitation,an Improved Pulse Coupled Neural Networks(IPCNN)model is proposed in this work.The IPCNN constructs the connection between the static properties of the input image and the dynamic properties of the neurons,and all its parameters are set adaptively,which avoids the inconvenience of manual setting in traditional methods and improves the adaptability of parameters to different types of images.Experimental segmentation results demonstrate the validity and efficiency of the proposed self-adaptive parameter setting method of IPCNN on the gray images and natural images from the Matlab and Berkeley Segmentation Datasets.The IPCNN method achieves a better segmentation result without training,providing a new solution for the real-time transmission of image semantic information.

Advancements in Web3 Infrastructure for the Metaverse

Web3,also known as Web 3.0,has recently been attracting increasing attention from industry and academia.Leveraging the potential of blockchain technologies,Web3 has emerged as a pivotal foundation in the realm of metaverse development,which is considered by many as the next-generation Internet.Specifically,Web3 technologies such as smart contracts and protocols like non-fungible tokens(NFTs)have supported the immersive and content-rich experience of current Web3 metaverse projects.

Ultra-Dense Networking Architectures and Technologies for 5G

With the continuous enrichment of mobile communication application scenarios in the future, the traditional macro-cellular-based mobile communication network architecture will be difficult to meet the explosive growth in demand for communications services.

Wireless Acoustic Sensor Networks and Edge Computing for Rapid Acoustic Monitoring

Passive acoustic monitoring is emerging as a promising solution to the urgent, global need for new biodiversity assessment methods. The ecological relevance of the soundscape is increasingly recognised, and the affordability of robust hardware for remote audio recording is stimulating international interest in the potential for acoustic methods for biodiversity monitoring.The scale of the data involved requires automated methods,however, the development of acoustic sensor networks capable of sampling the soundscape across time and space and relaying the data to an accessible storage location remains a significant technical challenge, with power management at its core. Recording and transmitting large quantities of audio data is power intensive,hampering long-term deployment in remote, off-grid locations of key ecological interest. Rather than transmitting heavy audio data, in this paper, we propose a low-cost and energy efficient wireless acoustic sensor network integrated with edge computing structure for remote acoustic monitoring and in situ analysis.Recording and computation of acoustic indices are carried out directly on edge devices built from low noise primo condenser microphones and Teensy microcontrollers, using internal FFT hardware support. Resultant indices are transmitted over a ZigBee-based wireless mesh network to a destination server.Benchmark tests of audio quality, indices computation and power consumption demonstrate acoustic equivalence and significant power savings over current solutions.

Evolutionary Algorithms in Software Defined Networks: Techniques, Applications, and Issues

A software defined networking(SDN) system has a logically centralized control plane that maintains a global network view and enables network-wide management, optimization, and innovation. Network-wide management and optimization problems are typicallyvery complex with a huge solution space, large number of variables, and multiple objectives. Heuristic algorithms can solve theseproblems in an acceptable time but are usually limited to some particular problem circumstances. On the other hand, evolutionaryalgorithms(EAs), which are general stochastic algorithms inspired by the natural biological evolution and/or social behavior of species, can theoretically be used to solve any complex optimization problems including those found in SDNs. This paper reviewsfour types of EAs that are widely applied in current SDNs: Genetic Algorithms(GAs), Particle Swarm Optimization(PSO), Ant Colony Optimization(ACO), and Simulated Annealing(SA) by discussing their techniques, summarizing their representative applications, and highlighting their issues and future works. To the best of our knowledge, our work is the first that compares the tech-niques and categorizes the applications of these four EAs in SDNs.

RecCac:Recommendation-Empowered Cooperative Edge Caching for Internet of Things

Edge caching is an emerging technology for supporting massive content access in mobile edge networks to address rapidly growing Internet of Things(IoT)services and content applications.However,the edge server is limited with the computation/storage capacity,which causes a low cache hit.Cooperative edge caching jointing neighbor edge servers is regarded as a promising technique to improve cache hit and reduce congestion of the networks.Further,recommender systems can provide personalized content services to meet user’s requirements in the entertainment-oriented mobile networks.Therefore,we investigate the issue of joint cooperative edge caching and recommender systems to achieve additional cache gains by the soft caching framework.To measure the cache profits,the optimization problem is formulated as a 0-1 Integer Linear Programming(ILP),which is NP-hard.Specifically,the method of processing content requests is defined as server actions,we determine the server actions to maximize the quality of experience(QoE).We propose a cachefriendly heuristic algorithm to solve it.Simulation results demonstrate that the proposed framework has superior performance in improving the QoE.

Outage Probability of Composite Microscopic and Macroscopic Diversity over Correlated Shadowed Fading Channels

The outage probability of a composite microscopic and macroscopic diversity system is evaluated over correlated shadowed fading channels.The correlations on both a microlevel and macrolevel are taken into account for the evaluations.The expression of the desired outage probability is explicitly presented,and two evaluation approaches,i.e.a compact Gaussian-Hermite quadrature method and an effective iterative algorithm,are proposed.The accuracy and efficiency of the proposed approaches are analysed,and a guideline is provided for their application.By employing the proposed evaluation approaches,results and demonstrations are presented,which display the implied effects of the corresponding parameters on the system outage performance,and reveal the potential to facilitate the design and analysis of such composite diversity systems.

Subcarrier Intensity Modulated Optical Wireless Communications:A Survey from Communication Theory Perspective

Subcarrier intensity modulation with direet detection is a modulatiou/detection technique tbr optical wireless communication systems, where a pre-modulated and properly biased radio frequency signal is modulated on the intensity of the optical carrier. The most important benefits of subcarrier intensity modulation are as follows： 1） it does not provide irreducible error floor like the conventional on-off keying intensity modulation with a fixed detection threshold; 2） it provides improved spectral efficiency and supports higher order modulation schemes; and 3） it has much less implementation complexity compared to coherent optical wireless communications with heterodyne or homodyne detection. In this paper, we present an up-to-date review of subcarrier intensity modulated optical wireless communication systems. We survey the error rate and outage performance of subcarrier intensity modulations in the atmospheric turbulence channels considering different modulation and coding schemes. We also explore different contemporary atmospheric turbulence fading mitigation solutions that can be employed for subcarrier intensity modulation. These solutions include diversity combining, adaptive transmission, relay assisted transmission, multiple-subcarrier intensity modulations, and optical orthogonal frequency division multiplexing. Moreover, we review the performance of subcarrier intensity modulations due to the pointing error and synchronization error.

Wireless Body Area Networks for Pervasive Healthcare and Smart Environments

Wireless body area networks （WBANs） use RF communication for interconnection of tiny sensor nodes located in, on, or in close prox- imity to the human body. A WBAN enables physiological signals, physical activity, and body position to be continuously monitored.

Arm PSA-Certified IoT Chip Security: A Case Study

With the large scale adoption of Internet of Things(IoT)applications in people’s lives and industrial manufacturing processes,IoT security has become an important problem today.IoT security significantly relies on the security of the underlying hardware chip,which often contains critical information,such as encryption key.To understand existing IoT chip security,this study analyzes the security of an IoT security chip that has obtained an Arm Platform Security Architecture(PSA)Level 2 certification.Our analysis shows that the chip leaks part of the encryption key and presents a considerable security risk.Specifically,we use commodity equipment to collect electromagnetic traces of the chip.Using a statistical T-test,we find that the target chip has physical leakage during the AES encryption process.We further use correlation analysis to locate the detailed encryption interval in the collected electromagnetic trace for the Advanced Encryption Standard(AES)encryption operation.On the basis of the intermediate value correlation analysis,we recover half of the 16-byte AES encryption key.We repeat the process for three different tests;in all the tests,we obtain the same result,and we recover around 8 bytes of the 16-byte AES encryption key.Therefore,experimental results indicate that despite the Arm PSA Level 2 certification,the target security chip still suffers from physical leakage.Upper layer application developers should impose strong security mechanisms in addition to those of the chip itself to ensure IoT application security.

Anchor Vertex Selection for Enhanced Reliability of Traffic Offloading Service in Edge-Enabled Mobile P2P Social Networks

As the rapid growth of mobile social networks,mobile peer-to-peer(P2P)communications and mobile edge computing(MEC)have been developed to reduce the traffic load and improve the computation capacity of cellular networks.However,the stability of social network is largely ignored in the advances of P2P and MEC,which is related to the social relations between users.It plays a vital role in improving the efficiency and reliability of traffic offloading service.In this paper,we integrate an edge node and the nearby P2P users as a mobile P2P social network and introduce the problem of adaptive anchored(k,r)-core to maintain the stability of multiple mobile P2P networks.It aims to adaptively select and retain a set of critical users for each network,whose participation is critical to overall stability of the network,and allocate certain resource for them so that the maximum number of users of all networks will remain engaged and the traffic of cellular network can be minimized.We called the retained users as anchor vertices.To address it,we devise a peer-edge-cloud framework to achieve the adaptive allocation of resources.We also develop a similarity based onion layers anchored(k,r)-core(S-OLAK)algorithm to explore the anchor vertices.Experimental results based on a real large-scale mobile P2P data set demonstrate the effectiveness of our method.