Guest editorial: Network architectures and communication protocols for smart industrial IoT applications

The rapid growth in hardware technologies and the fourth industrial revolution-Industry 4.0 have enabled the Internet of Things(IoT)to be smarter.One of the main drivers in Industry 4.0 is smart and secured Industrial IoT(IIoT)[1].The IIoT results from the widespread use of computers and the interconnectedness of machines.It has made software a crucial tool for almost every industry,from bakeries and arts to manufacturing facilities and healthcare systems[2].The IIoT devices can be mobile and geographically distributed over a long distance,which exposes them to network disturbances,Quality of Service(QoS)degradation,and security vulnerabilities.In addition,the IIoT is a complex network at a large scale,and there is a dire need for network architecture and protocol design to accommodate these diverse domains and competencies and handle the increasing levels of complexity.Therefore,in this special issue,we aim to focus on the challenges of network architectures and communication protocol design in the context of the smart industry.This special issue has attracted numerous high-quality research articles and has accepted fourteen research papers[3–16].

New Modified Controlled Bat Algorithm for Numerical Optimization Problem

Bat algorithm(BA)is an eminent meta-heuristic algorithm that has been widely used to solve diverse kinds of optimization problems.BA leverages the echolocation feature of bats produced by imitating the bats’searching behavior.BA faces premature convergence due to its local search capability.Instead of using the standard uniform walk,the Torus walk is viewed as a promising alternative to improve the local search capability.In this work,we proposed an improved variation of BA by applying torus walk to improve diversity and convergence.The proposed.Modern Computerized Bat Algorithm(MCBA)approach has been examined for fifteen well-known benchmark test problems.The finding of our technique shows promising performance as compared to the standard PSO and standard BA.The proposed MCBA,BPA,Standard PSO,and Standard BA have been examined for well-known benchmark test problems and training of the artificial neural network(ANN).We have performed experiments using eight benchmark datasets applied from the worldwide famous machine-learning(ML)repository of UCI.Simulation results have shown that the training of an ANN with MCBA-NN algorithm tops the list considering exactness,with more superiority compared to the traditional methodologies.The MCBA-NN algorithm may be used effectively for data classification and statistical problems in the future.

Unprecedented Smart Algorithm for Uninterrupted SDN Services During DDoS Attack

In the design and planning of next-generation Internet of Things(IoT),telecommunication,and satellite communication systems,controller placement is crucial in software-defined networking(SDN).The programmability of the SDN controller is sophisticated for the centralized control system of the entire network.Nevertheless,it creates a significant loophole for the manifestation of a distributed denial of service(DDoS)attack straightforwardly.Furthermore,recently a Distributed Reflected Denial of Service(DRDoS)attack,an unusual DDoS attack,has been detected.However,minimal deliberation has given to this forthcoming single point of SDN infrastructure failure problem.Moreover,recently the high frequencies of DDoS attacks have increased dramatically.In this paper,a smart algorithm for planning SDN smart backup controllers under DDoS attack scenarios has proposed.Our proposed smart algorithm can recommend single or multiple smart backup controllers in the event of DDoS occurrence.The obtained simulated results demonstrate that the validation of the proposed algorithm and the performance analysis achieved 99.99%accuracy in placing the smart backup controller under DDoS attacks within 0.125 to 46508.7 s in SDN.

Evaluation of the neuropharmacological properties of nerol in mice

The search for therapeutic agents that will provide the ground for man and an improvement in their quality of life is ceaseless. The nerol (cis-2,6-dimethyl-2,6-octadien-8-ol) is a monoterpene which can be found in various medicinal plants as Lippia spp and Melissa officinalis L. The objective of this study was to analyze the acute effect of nerol in the central nervous system (CNS) by performing behavioral tests in mice (open field, elevated plus-maze, light/dark and rota rod tests). We used male albino mice (Mus musculus), Swiss variety, adult with 2 month-old. The animals were divided into five groups (n = 8) for each experimental protocol, and they were administered intraperitoneally (i.p.), respectively, Tween 80 0.05% dissolved in saline solution 0.9%, nerol (30, 60 or 90 mg/kg) or diazepam (2 mg/kg). In the open field test, all groups treated with nerol showed a significant decrease in motor activity (number of crossings, rearings and groomings) when compared with vehicle group. In the elevated plus-maze test, nerol groups significantly increased the number of entries and time of permanence in the open arms when compared with vehicle group. In the light-dark test, nerol groups showed a significant increase the time of permanence in the room clear when compared with vehicle group. In the rota rod test, the groups treated with nerol didn’t show modification in time spent and number of falls in the revolving bar when compared with vehicle group. These results indicate a possible anxiolytic effect of nerol in mice.

Photoluminescence emissions of Ca_(1-x)WO_(4):xEu^(3+):Bridging between experiment and DFT calculations

In this work,the impact of the doping process on the photoluminescence emission of CaWO_(4) as a function of the concentration of Eu^(3+) cation(0.01 mol%,0.02 mol%,0.04 mol%,0.06 mol%,0.08 mol%,and 0.10 mol%) is discussed in detail.Ca_(1-x)WO~4:xEu^(3+) samples were successfully synthesized by a simple coprecipitation method followed by microwave irradiation.The blue shift in the absorption edge confirms the quantum confinement effect and the band gap energy covers the range from 3.91 to 4.18 eV,as the amount of Eu^(3+) cations increases.The experimental results are sustained by first-principles calculations,at the density functional theory level,to decipher the geometry and electronic properties,thereby enabling a more accurate and direct comparison between theory and experiment for the Ca_(1-x)WO_(4):xEu^(3+) structure.