Link failure is a critical issue in large networks and must be effectively addressed.In software-defined networks(SDN),link failure recovery schemes can be categorized into proactive and reactive approaches.Reactive s...Link failure is a critical issue in large networks and must be effectively addressed.In software-defined networks(SDN),link failure recovery schemes can be categorized into proactive and reactive approaches.Reactive schemes have longer recovery times while proactive schemes provide faster recovery but overwhelm the memory of switches by flow entries.As SDN adoption grows,ensuring efficient recovery from link failures in the data plane becomes crucial.In particular,data center networks(DCNs)demand rapid recovery times and efficient resource utilization to meet carrier-grade requirements.This paper proposes an efficient Decentralized Failure Recovery(DFR)model for SDNs,meeting recovery time requirements and optimizing switch memory resource consumption.The DFR model enables switches to autonomously reroute traffic upon link failures without involving the controller,achieving fast recovery times while minimizing memory usage.DFR employs the Fast Failover Group in the OpenFlow standard for local recovery without requiring controller communication and utilizes the k-shortest path algorithm to proactively install backup paths,allowing immediate local recovery without controller intervention and enhancing overall network stability and scalability.DFR employs flow entry aggregation techniques to reduce switch memory usage.Instead of matching flow entries to the destination host’s MAC address,DFR matches packets to the destination switch’s MAC address.This reduces the switches’Ternary Content-Addressable Memory(TCAM)consumption.Additionally,DFR modifies Address Resolution Protocol(ARP)replies to provide source hosts with the destination switch’s MAC address,facilitating flow entry aggregation without affecting normal network operations.The performance of DFR is evaluated through the network emulator Mininet 2.3.1 and Ryu 3.1 as SDN controller.For different number of active flows,number of hosts per edge switch,and different network sizes,the proposed model outperformed various failure recovery models:restoration-based,protection by flow entries,protection by group entries and protection by Vlan-tagging model in terms of recovery time,switch memory consumption and controller overhead which represented the number of flow entry updates to recover from the failure.Experimental results demonstrate that DFR achieves recovery times under 20 milliseconds,satisfying carrier-grade requirements for rapid failure recovery.Additionally,DFR reduces switch memory usage by up to 95%compared to traditional protection methods and minimizes controller load by eliminating the need for controller intervention during failure recovery.Theresults underscore the efficiency and scalability of the DFR model,making it a practical solution for enhancing network resilience in SDN environments.展开更多
Software-defined networking(SDN)is an innovative paradigm that separates the control and data planes,introducing centralized network control.SDN is increasingly being adopted by Carrier Grade networks,offering enhance...Software-defined networking(SDN)is an innovative paradigm that separates the control and data planes,introducing centralized network control.SDN is increasingly being adopted by Carrier Grade networks,offering enhanced networkmanagement capabilities than those of traditional networks.However,because SDN is designed to ensure high-level service availability,it faces additional challenges.One of themost critical challenges is ensuring efficient detection and recovery from link failures in the data plane.Such failures can significantly impact network performance and lead to service outages,making resiliency a key concern for the effective adoption of SDN.Since the recovery process is intrinsically dependent on timely failure detection,this research surveys and analyzes the current literature on both failure detection and recovery approaches in SDN.The survey provides a critical comparison of existing failure detection techniques,highlighting their advantages and disadvantages.Additionally,it examines the current failure recovery methods,categorized as either restoration-based or protection-based,and offers a comprehensive comparison of their strengths and limitations.Lastly,future research challenges and directions are discussed to address the shortcomings of existing failure recovery methods.展开更多
The 2025 Shanghai Auto Show reaffirmed its role as one of the world’s most influential automotive industry events,offering a panoramic view of the future shaped by intelligent and electrified vehicles.With over 200 n...The 2025 Shanghai Auto Show reaffirmed its role as one of the world’s most influential automotive industry events,offering a panoramic view of the future shaped by intelligent and electrified vehicles.With over 200 new models on display-85 percent of them new energy vehicles-this year’s show spotlighted how the global auto industry is pivoting rapidly towards an era of software-defined and AI-powered mobility.展开更多
Continuity is the foremost defining characteristic of Chinese civilization.It ensures that the evolution of this civilization respects the fine traditions and stays on the right course throughout its creative course.M...Continuity is the foremost defining characteristic of Chinese civilization.It ensures that the evolution of this civilization respects the fine traditions and stays on the right course throughout its creative course.Meanwhile,creativity imparts ceaseless vitality to this civilization,serving as the intrinsic propulsive force that fuels its evolution.The rise of Song Studies marks one of the symbolic events in the transformation in the Chinese ideological and cultural realm.It encapsulates the dialectical unity between continuity and creativity that characterizes Chinese civilization.Song Studies adhere to the traditional classic interpretations,center the core values around“benevolence,”and pursue the way of sages,which reflect the continuity of Chinese civilization.They also embody creativity.This is manifested in the emergence of a new academic spirit that emphasizes the seeking of truth and reason,a new academic ethos that involves questioning classics in the process of their dissemination and interpreting them with one’s own insight,as well as the fusion of philosophical speculation with social practice.Conducting an integrated analysis of the defining characteristics of Chinese civilization and the rise of Song Studies helps us gain a thorough understanding of the dialectical unity between the continuity and creativity of Chinese civilization through the interactions between history and reality.It also enables us to effectively address the relationship between inheritance and transformation,as well as between maintaining core values and pursuing creativity throughout its ongoing development.展开更多
Conventional echocardiography can sometimes pose a challenge to diagnosis due to sub-optimal images.Ultrasound contrast agents(UCAs)have been shown to drastically enhance imaging quality,particularly depicting the lef...Conventional echocardiography can sometimes pose a challenge to diagnosis due to sub-optimal images.Ultrasound contrast agents(UCAs)have been shown to drastically enhance imaging quality,particularly depicting the left ventricular endocardial borders.Their use during echocardiography has become a valuable tool in non-invasive diagnostics.UCAs provide higher-quality images that may ultimately reduce the length of hospital stays and improve patient care.The higher cost associated with UCAs in many situations has been an impediment to frequent use.However,when used as an initial diagnostic test,UCA during rest echocardiogram is more cost-effective than the traditional diagnostic approach,which frequently includes multiple tests and imaging studies to make an accurate diagnosis.They can be easily performed across multiple patient settings and provide optimal images that allow clinicians to make sound medical decisions.This consequently allows for better diagnostic accuracies and improvement in patient care.展开更多
Following the work of Li-Shi-Qing, we propose the definition of the relative volume function for an AH manifold. It is not a constant function in general and we study the regularity of this function. We use this funct...Following the work of Li-Shi-Qing, we propose the definition of the relative volume function for an AH manifold. It is not a constant function in general and we study the regularity of this function. We use this function to provide an accurate characterization of the height of the geodesic defining function for the AH manifold with a given boundary metric. Furthermore, it is shown that such functions are uniformly bounded from below at infinity and the bound only depends on the dimension. In the end, we apply this function to study the capacity of balls in AH manifolds and demonstrate that the “relative p—capacity function” coincides with the relative volume function under appropriate curvature conditions.展开更多
Preterm birth(PTB),defined as delivery before 37 weeks of gestation,is the most common adverse pregnancy outcome[1].PTB is a global health concern,with an estimated 13.4 million cases in 2020[1],accounting for more th...Preterm birth(PTB),defined as delivery before 37 weeks of gestation,is the most common adverse pregnancy outcome[1].PTB is a global health concern,with an estimated 13.4 million cases in 2020[1],accounting for more than one in 10 births worldwide.Compared to full-term births,PTBs are associated with a higher risk of short-and long-term complications,including bronchopulmonary dysplasia,necrotizing enterocolitis,visual impairment,and cerebral injuries[2].Despite substantial research efforts to prevent PTB,the global PTB rate has shown little improvement over the past decade[1].Therefore,identifying additional risk factors remains a critical goal in preventing PTB.展开更多
The increasing reliance on interconnected Internet of Things(IoT)devices has amplified the demand for robust anonymization strategies to protect device identities and ensure secure communication.However,traditional an...The increasing reliance on interconnected Internet of Things(IoT)devices has amplified the demand for robust anonymization strategies to protect device identities and ensure secure communication.However,traditional anonymization methods for IoT networks often rely on static identity models,making them vulnerable to inference attacks through long-term observation.Moreover,these methods tend to sacrifice data availability to protect privacy,limiting their practicality in real-world applications.To overcome these limitations,we propose a dynamic device identity anonymization framework using Moving Target Defense(MTD)principles implemented via Software-Defined Networking(SDN).In our model,the SDN controller periodically reconfigures the network addresses and routes of IoT devices using a constraint-aware backtracking algorithmthat constructs new virtual topologies under connectivity and performance constraints.This address-hopping scheme introduces continuous unpredictability at the network layer dynamically changing device identifiers,routing paths,and even network topology which thwarts attacker reconnaissance while preserving normal communication.Experimental results demonstrate that our approach significantly reduces device identity exposure and scan success rates for attackers compared to static networks.Moreover,the dynamic schememaintains high data availability and network performance.Under attack conditions it reduced average communication delay by approximately 60% vs.an unprotected network,with minimal overhead on system resources.展开更多
Efficient resource provisioning,allocation,and computation offloading are critical to realizing lowlatency,scalable,and energy-efficient applications in cloud,fog,and edge computing.Despite its importance,integrating ...Efficient resource provisioning,allocation,and computation offloading are critical to realizing lowlatency,scalable,and energy-efficient applications in cloud,fog,and edge computing.Despite its importance,integrating Software Defined Networks(SDN)for enhancing resource orchestration,task scheduling,and traffic management remains a relatively underexplored area with significant innovation potential.This paper provides a comprehensive review of existing mechanisms,categorizing resource provisioning approaches into static,dynamic,and user-centric models,while examining applications across domains such as IoT,healthcare,and autonomous systems.The survey highlights challenges such as scalability,interoperability,and security in managing dynamic and heterogeneous infrastructures.This exclusive research evaluates how SDN enables adaptive policy-based handling of distributed resources through advanced orchestration processes.Furthermore,proposes future directions,including AI-driven optimization techniques and hybrid orchestrationmodels.By addressing these emerging opportunities,thiswork serves as a foundational reference for advancing resource management strategies in next-generation cloud,fog,and edge computing ecosystems.This survey concludes that SDN-enabled computing environments find essential guidance in addressing upcoming management opportunities.展开更多
5G-R is the main type of next-generation mobile communication system for railways,offering highly reliable broadband data transmission services for intelligent railway operations.In the light of meeting the bearing de...5G-R is the main type of next-generation mobile communication system for railways,offering highly reliable broadband data transmission services for intelligent railway operations.In the light of meeting the bearing demands of the 5G-R network,a comprehensive data transmission platform is proposed.This platform enables unified accession for various data service systems and applies Software Defined Network(SDN)technology for dynamic routing selection and high-effective data forwarding.Based on shared key lightweight access authentication technology,two-way identity authentication is performed for mobile terminals and network-side devices,ensuring the legitimacy verification of heterogeneous terminals within the application domain.展开更多
[Objectives]This study was conducted to promote the rational use of special use level of antibiotics in clinic and delay the emergence of drug resistance.[Methods]The application of antibiotics for special use among i...[Objectives]This study was conducted to promote the rational use of special use level of antibiotics in clinic and delay the emergence of drug resistance.[Methods]The application of antibiotics for special use among inpatients of a hospital in 2019 was analyzed.The data in the drug information management system of the hospital were queried,and the collected expert consultation records of special-use antibiotics were sorted out.Indicators including the use rate of special-use antibiotics,antibiotic use density(AUD),defined daily dose system(DDDs)and defined daily dose system cost(DDDc)of each drug,the annual pathogen detection rate,disease distribution and pathogenic microorganism detection were summarized and analyzed for inpatients in the hospital retrospectively.[Results]In 2019,the average annual use rate of special-use antibiotics in the hospital was 1.53%,and the average annual use density was 1.59 DDDs.The antibiotics with the top three DDDs were imipenem and cilastatin,meropenem and cefepime.The antibiotics with the top three DDDc were voriconazole dispersible tablets,voriconazole for injection,and meropenem for injection.The average annual detection rate of microorganisms was 85.77%.The diseases were mainly diagnosed as respiratory infections such as pneumonia and secondary infections after radiotherapy and chemotherapy before medication,and the detected pathogens were mainly Candida and its subspecies,Escherichia coli,and Klebsiella and its subspecies.[Conclusions]The clinical use of special-use antibiotics in the hospital was basically reasonable,but there were still some problems.It is necessary to increase management efforts,strengthen training for relevant medical personnel,and provide management ideas for further standardizing the use of antibiotics in the hospital.展开更多
Component-based Chinese Medicine(CCM)stands as a pivotal endeavor in modernizing traditional Chinese medicine(TCM).By integrating classical TCM theories with modern scientific methodologies,CCM aims to achieve herbal ...Component-based Chinese Medicine(CCM)stands as a pivotal endeavor in modernizing traditional Chinese medicine(TCM).By integrating classical TCM theories with modern scientific methodologies,CCM aims to achieve herbal formulas with“defined components,clarified mechanisms,and controllable quality.”This approach not only transitions TCM development from empirical tradition to evidence-based science but also positions it for global recognition.Drawing on recent advancements in CCM,this editorial explores key insights and challenges shaping its trajectory.展开更多
Software Defined Network(SDN)and Network Function Virtualization(NFV)technology promote several benefits to network operators,including reduced maintenance costs,increased network operational performance,simplified ne...Software Defined Network(SDN)and Network Function Virtualization(NFV)technology promote several benefits to network operators,including reduced maintenance costs,increased network operational performance,simplified network lifecycle,and policies management.Network vulnerabilities try to modify services provided by Network Function Virtualization MANagement and Orchestration(NFV MANO),and malicious attacks in different scenarios disrupt the NFV Orchestrator(NFVO)and Virtualized Infrastructure Manager(VIM)lifecycle management related to network services or individual Virtualized Network Function(VNF).This paper proposes an anomaly detection mechanism that monitors threats in NFV MANO and manages promptly and adaptively to implement and handle security functions in order to enhance the quality of experience for end users.An anomaly detector investigates these identified risks and provides secure network services.It enables virtual network security functions and identifies anomalies in Kubernetes(a cloud-based platform).For training and testing purpose of the proposed approach,an intrusion-containing dataset is used that hold multiple malicious activities like a Smurf,Neptune,Teardrop,Pod,Land,IPsweep,etc.,categorized as Probing(Prob),Denial of Service(DoS),User to Root(U2R),and Remote to User(R2L)attacks.An anomaly detector is anticipated with the capabilities of a Machine Learning(ML)technique,making use of supervised learning techniques like Logistic Regression(LR),Support Vector Machine(SVM),Random Forest(RF),Naïve Bayes(NB),and Extreme Gradient Boosting(XGBoost).The proposed framework has been evaluated by deploying the identified ML algorithm on a Jupyter notebook in Kubeflow to simulate Kubernetes for validation purposes.RF classifier has shown better outcomes(99.90%accuracy)than other classifiers in detecting anomalies/intrusions in the containerized environment.展开更多
With the advancements of software defined network(SDN)and network function virtualization(NFV),service function chain(SFC)placement becomes a crucial enabler for flexible resource scheduling in low earth orbit(LEO)sat...With the advancements of software defined network(SDN)and network function virtualization(NFV),service function chain(SFC)placement becomes a crucial enabler for flexible resource scheduling in low earth orbit(LEO)satellite networks.While due to the scarcity of bandwidth resources and dynamic topology of LEO satellites,the static SFC placement schemes may cause performance degradation,resource waste and even service failure.In this paper,we consider migration and establish an online migration model,especially considering the dynamic topology.Given the scarcity of bandwidth resources,the model aims to maximize the total number of accepted SFCs while incurring as little bandwidth cost of SFC transmission and migration as possible.Due to its NP-hardness,we propose a heuristic minimized dynamic SFC migration(MDSM)algorithm that only triggers the migration procedure when new SFCs are rejected.Simulation results demonstrate that MDSM achieves a performance close to the upper bound with lower complexity.展开更多
Software Defined Networking(SDN)is programmable by separation of forwarding control through the centralization of the controller.The controller plays the role of the‘brain’that dictates the intelligent part of SDN t...Software Defined Networking(SDN)is programmable by separation of forwarding control through the centralization of the controller.The controller plays the role of the‘brain’that dictates the intelligent part of SDN technology.Various versions of SDN controllers exist as a response to the diverse demands and functions expected of them.There are several SDN controllers available in the open market besides a large number of commercial controllers;some are developed tomeet carrier-grade service levels and one of the recent trends in open-source SDN controllers is the Open Network Operating System(ONOS).This paper presents a comparative study between open source SDN controllers,which are known as Network Controller Platform(NOX),Python-based Network Controller(POX),component-based SDN framework(Ryu),Java-based OpenFlow controller(Floodlight),OpenDayLight(ODL)and ONOS.The discussion is further extended into ONOS architecture,as well as,the evolution of ONOS controllers.This article will review use cases based on ONOS controllers in several application deployments.Moreover,the opportunities and challenges of open source SDN controllers will be discussed,exploring carriergrade ONOS for future real-world deployments,ONOS unique features and identifying the suitable choice of SDN controller for service providers.In addition,we attempt to provide answers to several critical questions relating to the implications of the open-source nature of SDN controllers regarding vendor lock-in,interoperability,and standards compliance,Similarly,real-world use cases of organizations using open-source SDN are highlighted and how the open-source community contributes to the development of SDN controllers.Furthermore,challenges faced by open-source projects,and considerations when choosing an open-source SDN controller are underscored.Then the role of Artificial Intelligence(AI)and Machine Learning(ML)in the evolution of open-source SDN controllers in light of recent research is indicated.In addition,the challenges and limitations associated with deploying open-source SDN controllers in production networks,how can they be mitigated,and finally how opensource SDN controllers handle network security and ensure that network configurations and policies are robust and resilient are presented.Potential opportunities and challenges for future Open SDN deployment are outlined to conclude the article.展开更多
The healthcare sector holds valuable and sensitive data.The amount of this data and the need to handle,exchange,and protect it,has been increasing at a fast pace.Due to their nature,software-defined networks(SDNs)are ...The healthcare sector holds valuable and sensitive data.The amount of this data and the need to handle,exchange,and protect it,has been increasing at a fast pace.Due to their nature,software-defined networks(SDNs)are widely used in healthcare systems,as they ensure effective resource utilization,safety,great network management,and monitoring.In this sector,due to the value of thedata,SDNs faceamajor challengeposed byawide range of attacks,such as distributed denial of service(DDoS)and probe attacks.These attacks reduce network performance,causing the degradation of different key performance indicators(KPIs)or,in the worst cases,a network failure which can threaten human lives.This can be significant,especially with the current expansion of portable healthcare that supports mobile and wireless devices for what is called mobile health,or m-health.In this study,we examine the effectiveness of using SDNs for defense against DDoS,as well as their effects on different network KPIs under various scenarios.We propose a threshold-based DDoS classifier(TBDC)technique to classify DDoS attacks in healthcare SDNs,aiming to block traffic considered a hazard in the form of a DDoS attack.We then evaluate the accuracy and performance of the proposed TBDC approach.Our technique shows outstanding performance,increasing the mean throughput by 190.3%,reducing the mean delay by 95%,and reducing packet loss by 99.7%relative to normal,with DDoS attack traffic.展开更多
Software-Defined Networking(SDN),with segregated data and control planes,provides faster data routing,stability,and enhanced quality metrics,such as throughput(Th),maximum available bandwidth(Bd(max)),data transfer(DT...Software-Defined Networking(SDN),with segregated data and control planes,provides faster data routing,stability,and enhanced quality metrics,such as throughput(Th),maximum available bandwidth(Bd(max)),data transfer(DTransfer),and reduction in end-to-end delay(D(E-E)).This paper explores the critical work of deploying SDN in large-scale Data Center Networks(DCNs)to enhance its Quality of Service(QoS)parameters,using logically distributed control configurations.There is a noticeable increase in Delay(E-E)when adopting SDN with a unified(single)control structure in big DCNs to handle Hypertext Transfer Protocol(HTTP)requests causing a reduction in network quality parameters(Bd(max),Th,DTransfer,D(E-E),etc.).This article examines the network performance in terms of quality matrices(bandwidth,throughput,data transfer,etc.),by establishing a large-scale SDN-based virtual network in the Mininet environment.The SDN network is simulated in three stages:(1)An SDN network with unitary controller-POX to manage the data traffic flow of the network without the server load management algorithm.(2)An SDN network with only one controller to manage the data traffic flow of the network with a server load management algorithm.(3)Deployment of SDN in proposed control arrangement(logically distributed controlled framework)with multiple controllers managing data traffic flow under the proposed Intelligent Sensing Server Load Management(ISSLM)algorithm.As a result of this approach,the network quality parameters in large-scale networks are enhanced.展开更多
Link flooding attack(LFA)is a type of covert distributed denial of service(DDoS)attack.The attack mechanism of LFAs is to flood critical links within the network to cut off the target area from the Internet.Recently,t...Link flooding attack(LFA)is a type of covert distributed denial of service(DDoS)attack.The attack mechanism of LFAs is to flood critical links within the network to cut off the target area from the Internet.Recently,the proliferation of Internet of Things(IoT)has increased the quantity of vulnerable devices connected to the network and has intensified the threat of LFAs.In LFAs,attackers typically utilize low-speed flows that do not reach the victims,making the attack difficult to detect.Traditional LFA defense methods mainly reroute the attack traffic around the congested link,which encounters high complexity and high computational overhead due to the aggregation of massive attack traffic.To address these challenges,we present an LFA defense framework which can mitigate the attack flows at the border switches when they are small in scale.This framework is lightweight and can be deployed at border switches of the network in a distributed manner,which ensures the scalability of our defense system.The performance of our framework is assessed in an experimental environment.The simulation results indicate that our method is effective in detecting and mitigating LFAs with low time complexity.展开更多
The deployment of distributed multi-controllers for Software-Defined Networking(SDN)architecture is an emerging solution to improve network scalability and management.However,the network control failure affects the dy...The deployment of distributed multi-controllers for Software-Defined Networking(SDN)architecture is an emerging solution to improve network scalability and management.However,the network control failure affects the dynamic resource allocation in distributed networks resulting in network disruption and low resilience.Thus,we consider the control plane fault tolerance for cost-effective and accurate controller location models during control plane failures.This fault-tolerance strategy has been applied to distributed SDN control architecture,which allows each switch to migrate to next controller to enhance network performance.In this paper,the Reliable and Dynamic Mapping-based Controller Placement(RDMCP)problem in distributed architecture is framed as an optimization problem to improve the system reliability,quality,and availability.By considering the bound constraints,a heuristic state-of-the-art Controller Placement Problem(CPP)algorithm is used to address the optimal assignment and reassignment of switches to nearby controllers other than their regular controllers.The algorithm identifies the optimal controller location,minimum number of controllers,and the expected assignment costs after failure at the lowest effective cost.A metaheuristic Particle Swarm Optimization(PSO)algorithm was combined with RDMCP to form a hybrid approach that improves objective function optimization in terms of reliability and cost-effectiveness.The effectiveness of our hybrid RDMCP-PSO was then evaluated using extensive experiments and compared with other baseline algorithms.The findings demonstrate that the proposed hybrid technique significantly increases the network performance regarding the controller number and load balancing of the standalone heuristic CPP algorithm.展开更多
Software Defined Network(SDN)has been developed rapidly in technology and popularized in application due to its efficiency and flexibility in network management.In multi-controller SDN architecture,the Controller Plac...Software Defined Network(SDN)has been developed rapidly in technology and popularized in application due to its efficiency and flexibility in network management.In multi-controller SDN architecture,the Controller Placement Problem(CPP)must be solved carefully as it directly affects the whole network performance.This paper proposes a Multi-objective Greedy Optimized K-means Algorithm(MGOKA)to solve this problem to optimize worst-case and average delay between switches and controllers as well as synchronization delay and load balance among controllers for Wide Area Networks(WAN).MGOKA combines the process of network partition based on the K-means algorithm with cluster fusion based on the greedy algorithm and designs a normalization strategy to convert a multi-objective into a single-objective optimization problem.The simulation results depict that in different network scales with different numbers of controllers,the relative optimization rate of our proposed algorithm compared with K-means,K-means++,and GOKA can reach up to 101.5%,109.9%,and 79.8%,respectively.Moreover,the error rate between MGOKA and the global optimal solution is always less than 4%.展开更多
文摘Link failure is a critical issue in large networks and must be effectively addressed.In software-defined networks(SDN),link failure recovery schemes can be categorized into proactive and reactive approaches.Reactive schemes have longer recovery times while proactive schemes provide faster recovery but overwhelm the memory of switches by flow entries.As SDN adoption grows,ensuring efficient recovery from link failures in the data plane becomes crucial.In particular,data center networks(DCNs)demand rapid recovery times and efficient resource utilization to meet carrier-grade requirements.This paper proposes an efficient Decentralized Failure Recovery(DFR)model for SDNs,meeting recovery time requirements and optimizing switch memory resource consumption.The DFR model enables switches to autonomously reroute traffic upon link failures without involving the controller,achieving fast recovery times while minimizing memory usage.DFR employs the Fast Failover Group in the OpenFlow standard for local recovery without requiring controller communication and utilizes the k-shortest path algorithm to proactively install backup paths,allowing immediate local recovery without controller intervention and enhancing overall network stability and scalability.DFR employs flow entry aggregation techniques to reduce switch memory usage.Instead of matching flow entries to the destination host’s MAC address,DFR matches packets to the destination switch’s MAC address.This reduces the switches’Ternary Content-Addressable Memory(TCAM)consumption.Additionally,DFR modifies Address Resolution Protocol(ARP)replies to provide source hosts with the destination switch’s MAC address,facilitating flow entry aggregation without affecting normal network operations.The performance of DFR is evaluated through the network emulator Mininet 2.3.1 and Ryu 3.1 as SDN controller.For different number of active flows,number of hosts per edge switch,and different network sizes,the proposed model outperformed various failure recovery models:restoration-based,protection by flow entries,protection by group entries and protection by Vlan-tagging model in terms of recovery time,switch memory consumption and controller overhead which represented the number of flow entry updates to recover from the failure.Experimental results demonstrate that DFR achieves recovery times under 20 milliseconds,satisfying carrier-grade requirements for rapid failure recovery.Additionally,DFR reduces switch memory usage by up to 95%compared to traditional protection methods and minimizes controller load by eliminating the need for controller intervention during failure recovery.Theresults underscore the efficiency and scalability of the DFR model,making it a practical solution for enhancing network resilience in SDN environments.
文摘Software-defined networking(SDN)is an innovative paradigm that separates the control and data planes,introducing centralized network control.SDN is increasingly being adopted by Carrier Grade networks,offering enhanced networkmanagement capabilities than those of traditional networks.However,because SDN is designed to ensure high-level service availability,it faces additional challenges.One of themost critical challenges is ensuring efficient detection and recovery from link failures in the data plane.Such failures can significantly impact network performance and lead to service outages,making resiliency a key concern for the effective adoption of SDN.Since the recovery process is intrinsically dependent on timely failure detection,this research surveys and analyzes the current literature on both failure detection and recovery approaches in SDN.The survey provides a critical comparison of existing failure detection techniques,highlighting their advantages and disadvantages.Additionally,it examines the current failure recovery methods,categorized as either restoration-based or protection-based,and offers a comprehensive comparison of their strengths and limitations.Lastly,future research challenges and directions are discussed to address the shortcomings of existing failure recovery methods.
文摘The 2025 Shanghai Auto Show reaffirmed its role as one of the world’s most influential automotive industry events,offering a panoramic view of the future shaped by intelligent and electrified vehicles.With over 200 new models on display-85 percent of them new energy vehicles-this year’s show spotlighted how the global auto industry is pivoting rapidly towards an era of software-defined and AI-powered mobility.
基金a phased achievement of the“Research on Chinese Confucian Orthodoxy”(Project No.:17ZDA010),a major project of the National Social Science Fund of China.
文摘Continuity is the foremost defining characteristic of Chinese civilization.It ensures that the evolution of this civilization respects the fine traditions and stays on the right course throughout its creative course.Meanwhile,creativity imparts ceaseless vitality to this civilization,serving as the intrinsic propulsive force that fuels its evolution.The rise of Song Studies marks one of the symbolic events in the transformation in the Chinese ideological and cultural realm.It encapsulates the dialectical unity between continuity and creativity that characterizes Chinese civilization.Song Studies adhere to the traditional classic interpretations,center the core values around“benevolence,”and pursue the way of sages,which reflect the continuity of Chinese civilization.They also embody creativity.This is manifested in the emergence of a new academic spirit that emphasizes the seeking of truth and reason,a new academic ethos that involves questioning classics in the process of their dissemination and interpreting them with one’s own insight,as well as the fusion of philosophical speculation with social practice.Conducting an integrated analysis of the defining characteristics of Chinese civilization and the rise of Song Studies helps us gain a thorough understanding of the dialectical unity between the continuity and creativity of Chinese civilization through the interactions between history and reality.It also enables us to effectively address the relationship between inheritance and transformation,as well as between maintaining core values and pursuing creativity throughout its ongoing development.
文摘Conventional echocardiography can sometimes pose a challenge to diagnosis due to sub-optimal images.Ultrasound contrast agents(UCAs)have been shown to drastically enhance imaging quality,particularly depicting the left ventricular endocardial borders.Their use during echocardiography has become a valuable tool in non-invasive diagnostics.UCAs provide higher-quality images that may ultimately reduce the length of hospital stays and improve patient care.The higher cost associated with UCAs in many situations has been an impediment to frequent use.However,when used as an initial diagnostic test,UCA during rest echocardiogram is more cost-effective than the traditional diagnostic approach,which frequently includes multiple tests and imaging studies to make an accurate diagnosis.They can be easily performed across multiple patient settings and provide optimal images that allow clinicians to make sound medical decisions.This consequently allows for better diagnostic accuracies and improvement in patient care.
文摘Following the work of Li-Shi-Qing, we propose the definition of the relative volume function for an AH manifold. It is not a constant function in general and we study the regularity of this function. We use this function to provide an accurate characterization of the height of the geodesic defining function for the AH manifold with a given boundary metric. Furthermore, it is shown that such functions are uniformly bounded from below at infinity and the bound only depends on the dimension. In the end, we apply this function to study the capacity of balls in AH manifolds and demonstrate that the “relative p—capacity function” coincides with the relative volume function under appropriate curvature conditions.
基金supported by the National Natural Science Foundation of China(8200340181972981)+1 种基金the Scientific and Technological Project of Henan Province(222102310150,China)the Open Research Fund of the National Health Commission Key Laboratory of Birth Defects Prevention(NHCKLBDP202504,China).
文摘Preterm birth(PTB),defined as delivery before 37 weeks of gestation,is the most common adverse pregnancy outcome[1].PTB is a global health concern,with an estimated 13.4 million cases in 2020[1],accounting for more than one in 10 births worldwide.Compared to full-term births,PTBs are associated with a higher risk of short-and long-term complications,including bronchopulmonary dysplasia,necrotizing enterocolitis,visual impairment,and cerebral injuries[2].Despite substantial research efforts to prevent PTB,the global PTB rate has shown little improvement over the past decade[1].Therefore,identifying additional risk factors remains a critical goal in preventing PTB.
基金supported by the National Key Research and Development Program of China(Project No.2022YFB3104300).
文摘The increasing reliance on interconnected Internet of Things(IoT)devices has amplified the demand for robust anonymization strategies to protect device identities and ensure secure communication.However,traditional anonymization methods for IoT networks often rely on static identity models,making them vulnerable to inference attacks through long-term observation.Moreover,these methods tend to sacrifice data availability to protect privacy,limiting their practicality in real-world applications.To overcome these limitations,we propose a dynamic device identity anonymization framework using Moving Target Defense(MTD)principles implemented via Software-Defined Networking(SDN).In our model,the SDN controller periodically reconfigures the network addresses and routes of IoT devices using a constraint-aware backtracking algorithmthat constructs new virtual topologies under connectivity and performance constraints.This address-hopping scheme introduces continuous unpredictability at the network layer dynamically changing device identifiers,routing paths,and even network topology which thwarts attacker reconnaissance while preserving normal communication.Experimental results demonstrate that our approach significantly reduces device identity exposure and scan success rates for attackers compared to static networks.Moreover,the dynamic schememaintains high data availability and network performance.Under attack conditions it reduced average communication delay by approximately 60% vs.an unprotected network,with minimal overhead on system resources.
文摘Efficient resource provisioning,allocation,and computation offloading are critical to realizing lowlatency,scalable,and energy-efficient applications in cloud,fog,and edge computing.Despite its importance,integrating Software Defined Networks(SDN)for enhancing resource orchestration,task scheduling,and traffic management remains a relatively underexplored area with significant innovation potential.This paper provides a comprehensive review of existing mechanisms,categorizing resource provisioning approaches into static,dynamic,and user-centric models,while examining applications across domains such as IoT,healthcare,and autonomous systems.The survey highlights challenges such as scalability,interoperability,and security in managing dynamic and heterogeneous infrastructures.This exclusive research evaluates how SDN enables adaptive policy-based handling of distributed resources through advanced orchestration processes.Furthermore,proposes future directions,including AI-driven optimization techniques and hybrid orchestrationmodels.By addressing these emerging opportunities,thiswork serves as a foundational reference for advancing resource management strategies in next-generation cloud,fog,and edge computing ecosystems.This survey concludes that SDN-enabled computing environments find essential guidance in addressing upcoming management opportunities.
文摘5G-R is the main type of next-generation mobile communication system for railways,offering highly reliable broadband data transmission services for intelligent railway operations.In the light of meeting the bearing demands of the 5G-R network,a comprehensive data transmission platform is proposed.This platform enables unified accession for various data service systems and applies Software Defined Network(SDN)technology for dynamic routing selection and high-effective data forwarding.Based on shared key lightweight access authentication technology,two-way identity authentication is performed for mobile terminals and network-side devices,ensuring the legitimacy verification of heterogeneous terminals within the application domain.
基金Supported by National TCM Advantage Speciality Construction Project:Clinical Pharmacy(GZYYYZH[2024]90)Guizhou Provincial Key Discipline Construction Project of Traditional Chinese Medicine and Ethnic Medicine:Clinical Traditional Chinese pharmacy(QZYYZDXK(JS)-2023-04).
文摘[Objectives]This study was conducted to promote the rational use of special use level of antibiotics in clinic and delay the emergence of drug resistance.[Methods]The application of antibiotics for special use among inpatients of a hospital in 2019 was analyzed.The data in the drug information management system of the hospital were queried,and the collected expert consultation records of special-use antibiotics were sorted out.Indicators including the use rate of special-use antibiotics,antibiotic use density(AUD),defined daily dose system(DDDs)and defined daily dose system cost(DDDc)of each drug,the annual pathogen detection rate,disease distribution and pathogenic microorganism detection were summarized and analyzed for inpatients in the hospital retrospectively.[Results]In 2019,the average annual use rate of special-use antibiotics in the hospital was 1.53%,and the average annual use density was 1.59 DDDs.The antibiotics with the top three DDDs were imipenem and cilastatin,meropenem and cefepime.The antibiotics with the top three DDDc were voriconazole dispersible tablets,voriconazole for injection,and meropenem for injection.The average annual detection rate of microorganisms was 85.77%.The diseases were mainly diagnosed as respiratory infections such as pneumonia and secondary infections after radiotherapy and chemotherapy before medication,and the detected pathogens were mainly Candida and its subspecies,Escherichia coli,and Klebsiella and its subspecies.[Conclusions]The clinical use of special-use antibiotics in the hospital was basically reasonable,but there were still some problems.It is necessary to increase management efforts,strengthen training for relevant medical personnel,and provide management ideas for further standardizing the use of antibiotics in the hospital.
文摘Component-based Chinese Medicine(CCM)stands as a pivotal endeavor in modernizing traditional Chinese medicine(TCM).By integrating classical TCM theories with modern scientific methodologies,CCM aims to achieve herbal formulas with“defined components,clarified mechanisms,and controllable quality.”This approach not only transitions TCM development from empirical tradition to evidence-based science but also positions it for global recognition.Drawing on recent advancements in CCM,this editorial explores key insights and challenges shaping its trajectory.
基金This work was funded by the Deanship of Scientific Research at Jouf University under Grant Number(DSR2022-RG-0102).
文摘Software Defined Network(SDN)and Network Function Virtualization(NFV)technology promote several benefits to network operators,including reduced maintenance costs,increased network operational performance,simplified network lifecycle,and policies management.Network vulnerabilities try to modify services provided by Network Function Virtualization MANagement and Orchestration(NFV MANO),and malicious attacks in different scenarios disrupt the NFV Orchestrator(NFVO)and Virtualized Infrastructure Manager(VIM)lifecycle management related to network services or individual Virtualized Network Function(VNF).This paper proposes an anomaly detection mechanism that monitors threats in NFV MANO and manages promptly and adaptively to implement and handle security functions in order to enhance the quality of experience for end users.An anomaly detector investigates these identified risks and provides secure network services.It enables virtual network security functions and identifies anomalies in Kubernetes(a cloud-based platform).For training and testing purpose of the proposed approach,an intrusion-containing dataset is used that hold multiple malicious activities like a Smurf,Neptune,Teardrop,Pod,Land,IPsweep,etc.,categorized as Probing(Prob),Denial of Service(DoS),User to Root(U2R),and Remote to User(R2L)attacks.An anomaly detector is anticipated with the capabilities of a Machine Learning(ML)technique,making use of supervised learning techniques like Logistic Regression(LR),Support Vector Machine(SVM),Random Forest(RF),Naïve Bayes(NB),and Extreme Gradient Boosting(XGBoost).The proposed framework has been evaluated by deploying the identified ML algorithm on a Jupyter notebook in Kubeflow to simulate Kubernetes for validation purposes.RF classifier has shown better outcomes(99.90%accuracy)than other classifiers in detecting anomalies/intrusions in the containerized environment.
基金supported in part by the National Natural Science Foundation of China(NSFC)under grant numbers U22A2007 and 62171010the Open project of Satellite Internet Key Laboratory in 2022(Project 3:Research on Spaceborne Lightweight Core Network and Intelligent Collaboration)the Beijing Natural Science Foundation under grant number L212003.
文摘With the advancements of software defined network(SDN)and network function virtualization(NFV),service function chain(SFC)placement becomes a crucial enabler for flexible resource scheduling in low earth orbit(LEO)satellite networks.While due to the scarcity of bandwidth resources and dynamic topology of LEO satellites,the static SFC placement schemes may cause performance degradation,resource waste and even service failure.In this paper,we consider migration and establish an online migration model,especially considering the dynamic topology.Given the scarcity of bandwidth resources,the model aims to maximize the total number of accepted SFCs while incurring as little bandwidth cost of SFC transmission and migration as possible.Due to its NP-hardness,we propose a heuristic minimized dynamic SFC migration(MDSM)algorithm that only triggers the migration procedure when new SFCs are rejected.Simulation results demonstrate that MDSM achieves a performance close to the upper bound with lower complexity.
基金supported by UniversitiKebangsaan Malaysia,under Dana Impak Perdana 2.0.(Ref:DIP–2022–020).
文摘Software Defined Networking(SDN)is programmable by separation of forwarding control through the centralization of the controller.The controller plays the role of the‘brain’that dictates the intelligent part of SDN technology.Various versions of SDN controllers exist as a response to the diverse demands and functions expected of them.There are several SDN controllers available in the open market besides a large number of commercial controllers;some are developed tomeet carrier-grade service levels and one of the recent trends in open-source SDN controllers is the Open Network Operating System(ONOS).This paper presents a comparative study between open source SDN controllers,which are known as Network Controller Platform(NOX),Python-based Network Controller(POX),component-based SDN framework(Ryu),Java-based OpenFlow controller(Floodlight),OpenDayLight(ODL)and ONOS.The discussion is further extended into ONOS architecture,as well as,the evolution of ONOS controllers.This article will review use cases based on ONOS controllers in several application deployments.Moreover,the opportunities and challenges of open source SDN controllers will be discussed,exploring carriergrade ONOS for future real-world deployments,ONOS unique features and identifying the suitable choice of SDN controller for service providers.In addition,we attempt to provide answers to several critical questions relating to the implications of the open-source nature of SDN controllers regarding vendor lock-in,interoperability,and standards compliance,Similarly,real-world use cases of organizations using open-source SDN are highlighted and how the open-source community contributes to the development of SDN controllers.Furthermore,challenges faced by open-source projects,and considerations when choosing an open-source SDN controller are underscored.Then the role of Artificial Intelligence(AI)and Machine Learning(ML)in the evolution of open-source SDN controllers in light of recent research is indicated.In addition,the challenges and limitations associated with deploying open-source SDN controllers in production networks,how can they be mitigated,and finally how opensource SDN controllers handle network security and ensure that network configurations and policies are robust and resilient are presented.Potential opportunities and challenges for future Open SDN deployment are outlined to conclude the article.
基金extend their appreciation to Researcher Supporting Project Number(RSPD2023R582)King Saud University,Riyadh,Saudi Arabia.
文摘The healthcare sector holds valuable and sensitive data.The amount of this data and the need to handle,exchange,and protect it,has been increasing at a fast pace.Due to their nature,software-defined networks(SDNs)are widely used in healthcare systems,as they ensure effective resource utilization,safety,great network management,and monitoring.In this sector,due to the value of thedata,SDNs faceamajor challengeposed byawide range of attacks,such as distributed denial of service(DDoS)and probe attacks.These attacks reduce network performance,causing the degradation of different key performance indicators(KPIs)or,in the worst cases,a network failure which can threaten human lives.This can be significant,especially with the current expansion of portable healthcare that supports mobile and wireless devices for what is called mobile health,or m-health.In this study,we examine the effectiveness of using SDNs for defense against DDoS,as well as their effects on different network KPIs under various scenarios.We propose a threshold-based DDoS classifier(TBDC)technique to classify DDoS attacks in healthcare SDNs,aiming to block traffic considered a hazard in the form of a DDoS attack.We then evaluate the accuracy and performance of the proposed TBDC approach.Our technique shows outstanding performance,increasing the mean throughput by 190.3%,reducing the mean delay by 95%,and reducing packet loss by 99.7%relative to normal,with DDoS attack traffic.
文摘Software-Defined Networking(SDN),with segregated data and control planes,provides faster data routing,stability,and enhanced quality metrics,such as throughput(Th),maximum available bandwidth(Bd(max)),data transfer(DTransfer),and reduction in end-to-end delay(D(E-E)).This paper explores the critical work of deploying SDN in large-scale Data Center Networks(DCNs)to enhance its Quality of Service(QoS)parameters,using logically distributed control configurations.There is a noticeable increase in Delay(E-E)when adopting SDN with a unified(single)control structure in big DCNs to handle Hypertext Transfer Protocol(HTTP)requests causing a reduction in network quality parameters(Bd(max),Th,DTransfer,D(E-E),etc.).This article examines the network performance in terms of quality matrices(bandwidth,throughput,data transfer,etc.),by establishing a large-scale SDN-based virtual network in the Mininet environment.The SDN network is simulated in three stages:(1)An SDN network with unitary controller-POX to manage the data traffic flow of the network without the server load management algorithm.(2)An SDN network with only one controller to manage the data traffic flow of the network with a server load management algorithm.(3)Deployment of SDN in proposed control arrangement(logically distributed controlled framework)with multiple controllers managing data traffic flow under the proposed Intelligent Sensing Server Load Management(ISSLM)algorithm.As a result of this approach,the network quality parameters in large-scale networks are enhanced.
基金supported in part by the National Key R&D Program of China under Grant 2018YFA0701601in part by the National Natural Science Foundation of China(Grant No.62201605,62341110,U22A2002)in part by Tsinghua University-China Mobile Communications Group Co.,Ltd.Joint Institute。
文摘Link flooding attack(LFA)is a type of covert distributed denial of service(DDoS)attack.The attack mechanism of LFAs is to flood critical links within the network to cut off the target area from the Internet.Recently,the proliferation of Internet of Things(IoT)has increased the quantity of vulnerable devices connected to the network and has intensified the threat of LFAs.In LFAs,attackers typically utilize low-speed flows that do not reach the victims,making the attack difficult to detect.Traditional LFA defense methods mainly reroute the attack traffic around the congested link,which encounters high complexity and high computational overhead due to the aggregation of massive attack traffic.To address these challenges,we present an LFA defense framework which can mitigate the attack flows at the border switches when they are small in scale.This framework is lightweight and can be deployed at border switches of the network in a distributed manner,which ensures the scalability of our defense system.The performance of our framework is assessed in an experimental environment.The simulation results indicate that our method is effective in detecting and mitigating LFAs with low time complexity.
基金the Organization for Women in Science for the Developing World(OWSD)and the Swedish International Development Cooperation Agency(SIDA)under grant No.3240291613 for their financial support.
文摘The deployment of distributed multi-controllers for Software-Defined Networking(SDN)architecture is an emerging solution to improve network scalability and management.However,the network control failure affects the dynamic resource allocation in distributed networks resulting in network disruption and low resilience.Thus,we consider the control plane fault tolerance for cost-effective and accurate controller location models during control plane failures.This fault-tolerance strategy has been applied to distributed SDN control architecture,which allows each switch to migrate to next controller to enhance network performance.In this paper,the Reliable and Dynamic Mapping-based Controller Placement(RDMCP)problem in distributed architecture is framed as an optimization problem to improve the system reliability,quality,and availability.By considering the bound constraints,a heuristic state-of-the-art Controller Placement Problem(CPP)algorithm is used to address the optimal assignment and reassignment of switches to nearby controllers other than their regular controllers.The algorithm identifies the optimal controller location,minimum number of controllers,and the expected assignment costs after failure at the lowest effective cost.A metaheuristic Particle Swarm Optimization(PSO)algorithm was combined with RDMCP to form a hybrid approach that improves objective function optimization in terms of reliability and cost-effectiveness.The effectiveness of our hybrid RDMCP-PSO was then evaluated using extensive experiments and compared with other baseline algorithms.The findings demonstrate that the proposed hybrid technique significantly increases the network performance regarding the controller number and load balancing of the standalone heuristic CPP algorithm.
基金Supported by the National Natural Science Foundation of China(62102241)。
文摘Software Defined Network(SDN)has been developed rapidly in technology and popularized in application due to its efficiency and flexibility in network management.In multi-controller SDN architecture,the Controller Placement Problem(CPP)must be solved carefully as it directly affects the whole network performance.This paper proposes a Multi-objective Greedy Optimized K-means Algorithm(MGOKA)to solve this problem to optimize worst-case and average delay between switches and controllers as well as synchronization delay and load balance among controllers for Wide Area Networks(WAN).MGOKA combines the process of network partition based on the K-means algorithm with cluster fusion based on the greedy algorithm and designs a normalization strategy to convert a multi-objective into a single-objective optimization problem.The simulation results depict that in different network scales with different numbers of controllers,the relative optimization rate of our proposed algorithm compared with K-means,K-means++,and GOKA can reach up to 101.5%,109.9%,and 79.8%,respectively.Moreover,the error rate between MGOKA and the global optimal solution is always less than 4%.
