An overview of millimeter waves challenges in 5G vehicle-to-everything networks

International audienceThe Automotive Vehicle to Everything (V2X) technology is one of the most important innovations that the world will see in the years to come. This paradigm will support many advanced services such as object detection and recognition, risk identification and avoidance, car platooning. These services will require several keys among them, the high data transmission rates of the order of gigabits per driving hour, and high reliability, and high speed for transition of data, which may be available through the capabilities of the new architecture for the next generation of wireless communications 5G and the wide bandwidth of the millimeter wave (mm Wave) which is deemed to be a real solution for the V2X requirements. However, the challenges related to the reliability/latency and security of the V2X system and nature of mm wave communication require several solutions either for natural challenges such as High path loss propagation, penetrating disability or for the technical challenges. This paper provides an overview of the V2X communication technology investigates the V2X challenges including the mm wave and and finally presents some efficient solutions

Ultra reliable 5G mmWAve communications for V2X scénarios

The Automotive Vehicle to Everything (V2X)technology is one of the most important innovations that theworld will see in the years to come. This paradigm will supportmany advanced services such as object detection and recognition,risk identification and avoidance, car platooning. These serviceswill require several keys among them, the high data transmissionrates of the order of gigabits per driving hour, and highreliability, and high speed for transition of data, which may beavailable through the capabilities of the new architecture for thenext generation of wireless communications 5G and the widebandwidth of the millimeter wave (mm Wave) which is deemed tobe a real solution for the V2X requirements. However, thechallenges related to the reliability/latency and security of theV2X system and nature of mm wave communication requireseveral solutions either for natural challenges such as High pathloss propagation, penetrating disability or for the technicalchallenges. This paper provides an overview of the V2Xcommunication technology investigates the V2X challengesincluding the mm wave and and finally presents some efficientsolutions

Energy-Efficient Hybrid K-Means Algorithm for Clustered Wireless Sensor Networks

Energy efficiency is the most critical challenge in wireless sensor network. The transmission energy is the most consuming task in sensor nodes, specifically in large distances. Clustered routing techniques are efficient approaches used to lower the transmission energy and maximize the network’s lifetime. In this paper, a hybrid clustered routing approach is proposed for energy optimization in WSN. This approach is based on K-Means clustering algorithm and LEACH protocol. The simulation results using MATLAB tool have shown that the proposed hybrid approach outperforms LEACH protocol and optimizes the nodes energy and the network lifetime

Energy Performance of LDPC Scheme in Multi-Hop Wireless Sensor Network with Two base Stations Model

Conservation of the energy is one of the main design issues in wireless sensor networks. The limited battery power of each sensor node is a challenging task in deploying this type of network. The challenge is crucial in reliable wireless network when implementing efficient error correcting scheme with energy consuming routing protocol. In this work, we investigated the energy performance of LDPC code in multi-hop wireless sensor network. We proposed a model of two base stations to prolong the lifetime and build a reliable and energy-efficient network. Through performed MATLAB simulations, we examine the energy effectiveness of multiple base stations model on reliable wireless sensor network performance in different network dimensions

An energy-efficient clustering protocol using fuzzy logic and network segmentation for heterogeneous WSN

Wireless sensor networks have become an emerging research area due to their importance in the present industrial application. The enlargement of network lifetime is the major limitation in WSN. Several routing protocols study the extension of lifespan in WSN. Routing protocols significantly influence on the global of energy consumption for sensors in WSN. It is essential to correct the energy efficiency performance of routing protocol in order to improve the lifetime. The protocols based on clustering are the most routing protocols in WSN to reduce energy consumption. The protocols dedicate to WSN have demonstrated their limitation in expanding the lifetime of the network. In this paper, we present Hybrid SEP protocol : Multi-zonal Fuzzy logic heterogeneous Clustering based on Stable Election Protocol (FMZ-SEP). The FMZ-SEP characterizes by four parameters: WSN segmentation (splitting the WSN into the triangle zones ), the Subtractive Clustering Method to determine a correct number of clusters, the FCM and the SEP protocol. The FMZ-SEP prolong the stability period and extend the lifetime. The simulation results point out that the stability period of FMZ-SEP. FMZ-SEP protocol outperforms of MZ-SEP, FSEP and SEP protocol by improving the network lifetime and the stability period

Smart industrial IoT monitoring and control system based on UAV and cloud computing applied to a concrete plant

Unmanned aerial vehicles (UAVs) are now considered one of the best remote sensing techniques for gathering data over large areas. They are now being used in the industry sector as sensing tools for proactively solving or preventing many issues, besides quantifying production and helping to make decisions. UAVs are a highly consistent technological platform for efficient and cost-effective data collection and event monitoring. The industrial Internet of things (IIoT) sends data from systems that monitor and control the physical world to data processing systems that cloud computing has shown to be important tools for meeting processing requirements. In fog computing, the IoT gateway links different objects to the internet. It can operate as a joint interface for different networks and support different communication protocols. A great deal of effort has been put into developing UAVs and multi-UAV systems. This paper introduces a smart IIoT monitoring and control system based on an unmanned aerial vehicle that uses cloud computing services and exploits fog computing as the bridge between IIoT layers. Its novelty lies in the fact that the UAV is automatically integrated into an industrial control system through an IoT gateway platform, while UAV photos are systematically and instantly computed and analyzed in the cloud. Visual supervision of the plant by drones and cloud services is integrated in real-time into the control loop of the industrial control system. As a proof of concept, the platform was used in a case study in an industrial concrete plant. The results obtained clearly illustrate the feasibility of the proposed platform in providing a reliable and efficient system for UAV remote control to improve product quality and reduce waste. For this, we studied the communication latency between the different IIoT layers in different IoT gateways.The authors would like to thank the Seneca Foundation as also FRUMECAR S.L., for their support and the opportunity to implement and test the proposed approach on their facilities. This work was partially supported by FRUMECAR S.L. and Seneca Foundation's "Murcia Regional Scientific Excellence Research Program" (Murcia Science and Technology Agency-19895/GERM/15)

On the performance of adaptive coding schemes for energy efficient and reliable clustered wireless sensor networks

Clustering is the key for energy constrained wireless sensor networks (WSNs). Energy optimization and communication reliability are the most important consideration in designing efficient clustered WSN. In lossy environment, channel coding is mandatory to ensure reliable and efficient communication. This reliability is compromised by additional energy of coding and decoding in cluster heads. In this paper, we investigated the trade-offbetween reliability and energy efficiency and proposed adaptive FEC/FWD and FEC/ARQ coding frameworks for clustered WSNs. The proposed schemes consider channel condition and inter-node distance to decide the adequate channel coding usage. Simulation results show that both the proposed frameworks are energy efficient compared to ARQ schemes and FEC schemes, and suitable to prolong the clustered network lifespan as well as improve the reliability

Digital Twins in Industry 4.0: A Literature Review

Digital Twin is one of the most promising fields in Industry 4.0 due to its advantages related to real-time monitoring, performance analysis, and predictive maintenance. It is a virtual up-to-date representation of a realworld asset, system, being, and even city that is updated in real-time with data from its physical counterpart. By bridging the physical and digital, it is considered to be the innovation backbone of the future. In this contribution, we review the concept of digital twins, the development of its uses in industrial applications, and the level of integration in scientific work

Digital Twins in Industry 4.0: A Literature Review

Digital Twin is one of the most promising fields in Industry 4.0 due to its advantages related to real-time monitoring, performance analysis, and predictive maintenance. It is a virtual up-to-date representation of a realworld asset, system, being, and even city that is updated in real-time with data from its physical counterpart. By bridging the physical and digital, it is considered to be the innovation backbone of the future. In this contribution, we review the concept of digital twins, the development of its uses in industrial applications, and the level of integration in scientific work

A Novel Approach of Latency and Energy Efficiency Analysis of IIoT With SQL and NoSQL Databases Communication

Industrial Internet of Things (IIoT)-enabled production facilities generate vast amounts of data, which, if harnessed effectively, can substantially enhance manufacturing efficiency through latency reduction. The selection of the appropriate data storage technology is a pivotal consideration in achieving this objective. While prior studies have examined SQL and NoSQL databases in terms of latency and energy efficiency, these evaluations have not been conducted specifically within the context of IIoT. This paper aims to fill this research gap by conducting a rigorous comparison of SQL and NoSQL databases, focusing on their performance latency and energy efficiency when interfaced with IoT nodes. By elucidating these relationships, our research offers actionable insights that can guide IIoT-enabled manufacturing facilities in optimizing their operations. Specifically, the paper aids in the selection of the most suitable database technology, thereby contributing to latency minimization and efficiency maximization in industrial settings