Digital twin driven and intelligence enabled content delivery in end-edge-cloud collaborative 5G networks

The rapid development of 5G/6G and AI enables an environment of Internet of Everything(IoE)which can support millions of connected mobile devices and applications to operate smoothly at high speed and low delay.However,these massive devices will lead to explosive traffic growth,which in turn cause great burden for the data transmission and content delivery.This challenge can be eased by sinking some critical content from cloud to edge.In this case,how to determine the critical content,where to sink and how to access the content correctly and efficiently become new challenges.This work focuses on establishing a highly efficient content delivery framework in the IoE environment.In particular,the IoE environment is re-constructed as an end-edge-cloud collaborative system,in which the concept of digital twin is applied to promote the collaboration.Based on the digital asset obtained by digital twin from end users,a content popularity prediction scheme is firstly proposed to decide the critical content by using the Temporal Pattern Attention(TPA)enabled Long Short-Term Memory(LSTM)model.Then,the prediction results are input for the proposed caching scheme to decide where to sink the critical content by using the Reinforce Learning(RL)technology.Finally,a collaborative routing scheme is proposed to determine the way to access the content with the objective of minimizing overhead.The experimental results indicate that the proposed schemes outperform the state-of-the-art benchmarks in terms of the caching hit rate,the average throughput,the successful content delivery rate and the average routing overhead.

Task offloading mechanism based on federated reinforcement learning in mobile edge computing

With the arrival of 5G,latency-sensitive applications are becoming increasingly diverse.Mobile Edge Computing(MEC)technology has the characteristics of high bandwidth,low latency and low energy consumption,and has attracted much attention among researchers.To improve the Quality of Service(QoS),this study focuses on computation offloading in MEC.We consider the QoS from the perspective of computational cost,dimensional disaster,user privacy and catastrophic forgetting of new users.The QoS model is established based on the delay and energy consumption and is based on DDQN and a Federated Learning(FL)adaptive task offloading algorithm in MEC.The proposed algorithm combines the QoS model and deep reinforcement learning algorithm to obtain an optimal offloading policy according to the local link and node state information in the channel coherence time to address the problem of time-varying transmission channels and reduce the computing energy consumption and task processing delay.To solve the problems of privacy and catastrophic forgetting,we use FL to make distributed use of multiple users’data to obtain the decision model,protect data privacy and improve the model universality.In the process of FL iteration,the communication delay of individual devices is too large,which affects the overall delay cost.Therefore,we adopt a communication delay optimization algorithm based on the unary outlier detection mechanism to reduce the communication delay of FL.The simulation results indicate that compared with existing schemes,the proposed method significantly reduces the computation cost on a device and improves the QoS when handling complex tasks.

A Study of Configuration Evolution of an Operational IP Backbone Network

Configuration errors are proved to be the main reasons for network interruption and anomalies.Many researchers have paid their attention to configuration analysis and provisioning,but few works focus on understanding the configuration evolution.In this paper,we uncover the configuration evolution of an operational IP backbone based on the weekly reports gathered from January 2006 to January 2013.We find that rate limiting and launching routes for new customers are configured most frequently.In addition,we conduct an analysis of network failures and find that link failures are the main causes for network failures.We suggest that we should configure redundant links for the links which are easy to break down.At last,according to the analysis results,we illustrate how to provide semi-automated configuration for rate limiting and adding customers.

Fragmental Weight-Conservation Combining Scheme for Statistical Signal Transmissions under Fast Time-Varying Channels

Statistical Signal Transmission(SST)is a technique based on orthogonal frequency-division multiplexing(OFDM)and adopts cyclostationary features,which can transmit extra information without additional bandwidth.However,the more complicated environment in 5G communication systems,especially the fast time-varying scenarios,will dramatically degrade the performance of the SST.In this paper,we propose a fragmental weight-conservation combining(FWCC)scheme for SST,to overcome its performance degradation under fast time-varying channels.The proposed FWCC scheme consists of three phases:1、incise the received OFDM stream into pieces;2、endue different weights for fine and contaminated pieces,respectively;3、combine cyclic autocorrelation function energies of all the pieces;and 4、compute the final feature and demodulate data of SST.Through these procedures above,the detection accuracy of SST will be theoretically refined under fast time-varying channels.Such an inference is confirmed through numerical results in this paper.It is demonstrated that the BER performance of proposed scheme outperforms that of the original scheme both in ideal channel estimation conditions and in imperfect channel estimation conditions.In addition,we also find the experiential optimal weight distribution strategy for the proposed FWCC scheme,which facilitates practical applications.

Secure vehicular data communication in Named Data Networking

Vehicular data misuse may lead to traffic accidents and even loss of life,so it is crucial to achieve secure vehicular data communications.This paper focuses on secure vehicular data communications in the Named Data Networking(NDN).In NDN,names,provider IDs and data are transmitted in plaintext,which exposes vehicular data to security threats and leads to considerable data communication costs and failure rates.This paper proposes a Secure vehicular Data Communication(SDC)approach in NDN to supress data communication costs and failure rates.SCD constructs a vehicular backbone to reduce the number of authenticated nodes involved in reverse paths.Only the ciphtertext of the name and data is included in the signed Interest and Data and transmitted along the backbone,so the secure data communications are achieved.SCD is evaluated,and the data results demonstrate that SCD achieves the above objectives.

Modification of POSS and their tribological properties and resistant to space atomic oxygen irradiation as lubricant additive of multialkylated cyclopentanes

Developing functional additive resistant to space atomic oxygen(AO)irradiation through simple molecular design and chemical synthesis to enhance the lubricating performance of multialkylated cyclopentanes(MACs)oil is a significant challenge.Herein,sulfur-containing polyhedral oligomere silsesquioxane(POSS)were synthesize via a click-chemistry reaction of octavinyl polyhedral oligomeric with alkyl sulfide.The reduce-friction(RF),anti-wear(AW)properties and anti-AO irradiation of POSS-S-R as MACs base oil additives in atmospheric and simulated space environments were systematically investigated for the first time.Results demonstrate that POSS-S-R not only possesses outstanding anti-AO irradiation capacity but also effectively improves the RF and AW of MACs in atmospheric or simulated space surroundings.This improvement is due to the excellent anti-AO irradiation properties of the POSS structure itself and the high load-carrying ability of silicon-containing and sulfur-containing compounds generated by tribo-chemical reactions,which effectively separates the direct contact of the friction interface.We believe that this synthesized POSS-S-R is a promising additive for space lubricants.

Interfacial mechanism of hydrogel with controllable thickness for stable drag reduction

Surface wettability plays a significant role in reducing solid–liquid frictional resistance,especially the superhydrophilic/hydrophilic interface because of its excellent thermodynamic stability.In this work,poly(acrylic acid)-poly(acrylamide)(PAA–PAM)hydrogel coatings with different thicknesses were prepared in situ by polydopamine(PDA)-UV assisted surface catalytically initiated radical polymerization.Fluid drag reduction performance of hydrogel surface was measured using a rotational rheometer by the plate–plate mode.The experimental results showed that the average drag reduction of hydrogel surface could reach up to about 56%in Couette flow,which was mainly due to the interfacial polymerization phenomenon that enhanced the ability of hydration layer to delay the momentum dissipation between fluid layers and the diffusion behavior of surface.The proposed drag reduction mechanism of hydrogel surface was expected to shed new light on hydrogel–liquid interface interaction and provide a new way for the development of steady-state drag reduction methods.

TEPG:a traffic engineering based power-aware greedy routing algorithm in backbone networks with bundled links

1 Introduction and main contributions Various power-aware solutions have been proposed to address the alarming energy waste and consequent serious environmental issues since Gupta and Singh initiated the seminal study on green networking problem in 2003.Most of the researches concentrated their efforts on power-aware networking under the non-bundled link scenarios by leveraging the dynamic power management based Low Power Idle(LPI)policy which was defined and standardized in the IEEE 802.3az standard.However,in modern backbone networks,pairs of routers are typically connected,for each traffic direction,by multiple physical links that form one logical bundled link,which is the link aggregation technique defined and standardized in IEEE 802.1AX.

Formation mechanism and stability of low environment-sensitive ternary nanoparticles based on zein-pea protein-pectin for astaxanthin delivery

This study was devoted for preparing zein-pea protein-pectin ternary nanoparticles through an alcohol-free pH-shifting method for the delivery of astaxanthin(Ax).The complexation of zein and pea protein(PP)in the weight ratio range of 1:2.5 to 1.2:1 maintained the dispersity at pH 7.0 with the average particle size of 90.47-132.38 nm and the polydispersity index of 0.204-0.245.The circular dichroism,fluorescence,Fourier transform infrared spectroscopy and other analyses indicated that the zein interacted with PP to form a composite structure through the folding action of protein structure in the process of pH reduction driven by hydrophobic and electrostatic forces.The incorporation of pectin(pec)further enhanced the physicochemical stability of the nanoparticles.The optimal weight ratio of zein/PP/pec was 2:4:3,and the encapsulation efficiency of astaxanthin reached 94.22%.The X-ray diffraction results showed that the astaxanthin was amorphous after embedding.Compared with Ax/zein-PP,the Ax/zein-PP-pec showed better colloidal stability under the conditions of wide pH range(4.0-8.0),high temperature(90℃),long time ultraviolet light treatment,and 15-day storage.These results indicated that the construction of the zein-PP-pec nanoparticles could be used as a low environment-sensitive nanocarrier for the loading,protection,and delivery of hydrophobic functional substances such as astaxanthin.

Microwave heating and conduction heating pork belly: Influence of heat transfer modes on volatile compounds and aroma attributes

This work was conducted to compare the differences in odor attributes and the formation causes of pork belly cooked by different heating modes and the feasibility of achieving convenient and delicious cooking of stir-fried pork cuisines by modifying the heat transfer mode of the microwave.The effects of traditional pan-heating(TH),microwave heating(MH),and microwave combined with conduction heating(MH+CH)on sensory aroma attributes,aroma profile,free fatty acids,and volatile compounds of pork belly were investigated.The results showed that the pork belly heated by TH had the lowest total amount of stable volatile compounds(1695.41μg/kg)and contents of free fatty acids(751.44 mg/100g),but the balanced distribution and the rich contents of volatile compounds derived from thermal processing resulted in the better aroma quality of pork belly.In contrast,although the pork belly cooked by MH had higher free fatty acids contents(1215.32 mg/100g)and the highest volatile compounds(5410.56μg/kg),due to the cell destruction effect and the molecular movement acceleration of microwave,the contents of volatile compounds derived from spices were too high,leading to the disharmony of aroma characteristics.However,the pork belly cooked with MH+CH not only promoted the production of free fatty acids(1434.23 mg/100g),but also increased the generation and retention of pork characteristic aroma by changing the heating modes.Compared with MH,it enhanced the uniformity of aroma distribution and improved the overall aroma similarity to TH.

面向互联网的SDN流量多粒度处理机制

软件定义网络(software defined networking,SDN)作为一种新型的网络架构,将网络的控制平面与数据转发平面分离,实现了可编程化控制,为互联网提供了改善网络全局性能的新思路.虽然SDN具有全局视角优势,但在处理互联网海量数据时也存在性能瓶颈:频繁的层间通信会使控制器计算效率下降,海量的流表项数据使得交换机存储压力过大.为了进一步提升SDN的性能使其适应互联网的海量流量处理,本文提出了面向互联网的SDN流量多粒度处理机制,将SDN架构应用到互联网骨干网的流量处理中,分别从路由和调度两个方面设计并实现了流量多粒度处理机制.仿真结果表明:本文设计的流量多粒度处理机制能减少层间通信次数,减少下发流表项,维持负载均衡,提高了路由选取的正确性和有效性,提升了SDN性能,进而提升了处理互联网海量数据的能力.

Entropy-Based Global and Local Weight Adaptive Image Segmentation Models

This paper proposes a parameter adaptive hybrid model for image segmentation. The hybrid model combines the global and local information in an image, and provides an automated solution for adjusting the selection of the two weight parameters. Firstly, it combines an improved local model with the global Chan-Vese(CV) model, while the image’s local entropy is used to establish the index for measuring the image’s gray-level information. Parameter adjustment is then performed by the real-time acquisition of the ratio of the different functional energy in a self-adapting model responsive to gray-scale distribution in the image segmentation process.Compared with the traditional linear adjustment model, which is based on trial-and-error, this paper presents a more quantitative and intelligent method for achieving the dynamic nonlinear adjustment of global and local terms.Experiments show that the proposed model achieves fast and accurate segmentation for different types of noisy and non-uniform grayscale images and noise images. Moreover, the method demonstrates high stability and is insensitive to the position of the initial contour.

Plant genome resequencing and population genomics:Current status and future prospects

Advances in DNA sequencing technology have sparked a genomics revolution,driving breakthroughs in plant genetics and crop breeding.Recently,the focus has shifted from cataloging genetic diversity in plants to exploring their functional significance and delivering beneficial alleles for crop improvement.This transformation has been facilitated by the increasing adoption of whole-genome resequencing.In this review,we summarize the current progress of population-based genome resequencing studies and how these studies affect crop breeding.A total of 187 land plants from 163 countries have been resequenced,comprising 54413 accessions.As part of resequencing efforts 367 traits have been surveyed and 86 genome-wide association studies have been conducted.Economically important crops,particularly cereals,vegetables,and legumes,have dominated the resequencing efforts,leaving a gap in 49 orders,including Lycopodiales,Liliales,Acorales,Austrobaileyales,and Commelinales.The resequenced germplasm is distributed across diverse geographic locations,providing a global perspective on plant genomics.We highlight genes that have been selected during domestication,or associated with agronomic traits,and form a repository of candidate genes for future research and application.Despite the opportunities for cross-species comparative genomics,many population genomic datasets are not accessible,impeding secondary analyses.We call for a more open and collaborative approach to population genomics that promotes data sharing and encourages contribution-based credit policy.The number of plant genome resequencing studies will continue to rise with the decreasing DNA sequencing costs,coupled with advances in analysis and computational technologies.This expansion,in terms of both scale and quality,holds promise for deeper insights into plant trait genetics and breeding design.

A PUF-Based and Cloud-Assisted Lightweight Authentication for Multi-Hop Body Area Network

Wireless sensor technology plays an important role in the military,medical,and commercial fields nowadays.Wireless Body Area Network(WBAN)is a special application of the wireless sensor network in human health monitoring,through which patients can know their physical condition in real time and respond to emergencies on time.Data reliability,guaranteed by the trust of nodes in WBAN,is a prerequisite for the effective treatment of patients.Therefore,authenticating the sensor nodes and the sink nodes in WBAN is necessary.This paper proposes a lightweight Physical Unclonable Function(PUF)-based and cloud-assisted authentication mechanism for multi-hop body area networks,which compared with the star single-hop network,can enhance the adaptability to human motion and the integrity of data transmission.Such authentication mechanism can significantly reduce the storage overhead and resource loss in the data transmission process.

Lignin composite ionic liquid lubricants with excellent anti-corrosion,anti-oxidation,and tribological properties

A new type of lubricating material(BTA-P_(4444)-Lig)was synthesized by combining lignin with tetrabutylphosphorus and benzotriazole.The tribological properties,corrosion resistance,and anti-oxidation properties of BTA-P_(4444)-Lig as a lubricant were investigated.The lubricating material exhibits excellent friction reduction and wear resistance,as well as good thermal stability and excellent oxidation resistance.Mechanistic analysis reveals that the active elements N and P in the lubricating material react with the metal substrate,and the reaction film effectively blocks direct contact between the friction pairs,affording excellent friction reduction and wear resistance.At the same time,the phenolic hydroxyl group in lignin reacts with oxygen free radicals to form a resonance-stable semi-quinone free radical,which interrupts the chain reaction and affords good anti-oxidant activity.

Winner determination problem with loss-averse buyers in reverse auctions

Reverse auctions have been widely adopted for purchasing goods and services. This paper considers a novel winner determination problem in a multiple-object reverse auction in which the buyer involves loss-averse behavior due to uncertain attributes. A corresponding winner determination model based on cumulative prospect theory is proposed. Due to the NP-hard characteristic, a loaded route strategy is proposed to ensure the feasibility of the model. Then, an improved ant colony algorithm that consists of a dynamic transition strategy and a Max-Min pheromone strategy is designed. Numerical experiments are conducted to illustrate the effectiveness of the proposed model and algorithm. We find that under the loaded route strategy, the improved ant colony algorithm performs better than the basic ant colony algorithm. In addition, the proposed model can effectively characterize the buyer's loss-averse behavior.

Progress in MXene-based materials for microwave absorption

Due to the rapid development of radar technology,the demand for absorbing stealth materials is increas-ing,and ultra-broadband absorption(effective absorption bandwidth>8 GHz)has become an inevitable requirement.As a new type of two-dimensional material,MXene material possesses the characteristics of excellent wave absorbing material due to its easy preparation,easy modulation of defects and sur-face functional groups,and high conductivity.This work summarizes the absorbing theory and research progress on MXene-based absorbing materials in recent years,including pure MXene absorbing materials and MXene-based magnetic or dielectric composite materials with multiple losses.Some shortcomings and research directions of MXene-based materials were pointed out.Currently,research on MXene-based absorbent materials is thriving and in a state of vigorous development.Excellent absorbent materials have been reported,but their shortcomings are also apparent.The factors that affect the performance of MXene-based absorbent materials are complex,and the absorption mechanism is relatively simple.Further systematic and detailed research is needed to clarify these influencing mechanisms,broaden the absorption bandwidth,and reduce the matching thickness to meet practical usage requirements in the future.