Intelligent Network Slicing in V2X Networks-A Comprehensive Review

The rise of the Internet of Things and autonomous systems has made connecting vehicles more critical.Connected autonomous vehicles can create diverse communication networks that can improve the environment and offer contemporary applications.With the advent of Fifth Generation(5G)networks,vehicle-to-everything(V2X)networks are expected to be highly intelligent,reside on superfast,reliable,and low-latency connections.Network slicing,machine learning(ML),and deep learning(DL)are related to network automation and optimization in V2X communication.ML/DL with network slicing aims to optimize the performance,reliability of the V2X networks,personalized services,costs,and scalability,and thus,it enhances the overall driving experience.These advantages can ultimately lead to a safer and more efficient transportation system.However,existing long-term evolution systems and enabling 5G technologies cannot meet such dynamic requirements without adding higher complexity levels.ML algorithms mitigate complexity levels,which can be highly instrumental in such vehicular communication systems.This study aims to review V2X slicing based on a proposed taxonomy that describes the enablers of slicing,a different configuration of slicing,the requirements of slicing,and the ML algorithm used to control and manage to slice.This study also reviews various research works established in network slicing through ML algorithms to enable V2X communication use cases,focusing on V2X network slicing and considering efficient control and management.The enabler technologies are considered in light of the network requirements,particular configurations,and the underlying methods and algorithms,with a review of some critical challenges and possible solutions available.The paper concludes with a future roadmap by discussing some open research issues and future directions.

Particle Size-Controlled Oxygen Reduction and Evolution Reaction Nanocatalysts Regulate Ru(bpy)_(3)^(2+)’s Dual-potential Electrochemiluminescence for Sandwich Immunoassay

Multiple signal strategies remarkably improve the accuracy and efficiency of electrochemiluminescence(ECL)immunoassays,but the lack of potential-resolved luminophore pairs and chemical cross talk hinders their development.In this study,we synthesized a series of gold nanoparticles(AuNPs)/reduced graphene oxide(Au/rGO)composites as adjustable oxygen reduction reaction and oxygen evolution reaction catalysts to promote and modulate tris(2,2′-bipyridine)ruthenium(II)(Ru(bpy)_(3)^(2+))’s multisignal luminescence.With the increase in the diameter of AuNPs(3 to 30 nm),their ability to promote Ru(bpy)_(3)^(2+)’s anodic ECL was first impaired and then strengthened,and cathodic ECL was first enhanced and then weakened.Au/rGOs with medium-small and medium-large AuNP diameters remarkably increased Ru(bpy)_(3)^(2+)’s cathodic and anodic luminescence,respectively.Notably,the stimulation effects of Au/rGOs were superior to those of most existing Ru(bpy)_(3)^(2+)co-reactants.Moreover,we proposed a novel ratiometric immunosensor construction strategy using Ru(bpy)_(3)^(2+)’s luminescence promoter rather than luminophores as tags of antibodies to achieve signal resolution.This method avoids signal cross talk between luminophores and their respective co-reactants,which achieved a good linear range of 10−7 to 10−1 ng/ml and a limit of detection of 0.33 fg/ml for detecting carcinoembryonic antigen.This study addresses the previous scarcity of the macromolecular co-reactants of Ru(bpy)_(3)^(2+),broadening its application in biomaterial detection.Furthermore,the systematic clarification of the detailed mechanisms for converting the potential-resolved luminescence of Ru(bpy)_(3)^(2+)could facilitate an in-depth understanding of the ECL process and should inspire new designs of Ru(bpy)_(3)^(2+)luminescence enhancers or applications of Au/rGOs to other luminophores.This work removes some impediments to the development of multisignal ECL biodetection systems and provides vitality into their widespread applications.