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Accurate and efficient elephant-flow classification based on co-trained models in evolved software-defined networks 认领 引用 被引量：1
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作者 Ling Xia Liao Changqing Zhao +2 位作者 Jian Wang Roy Xiaorong Lai Steve Drew 《Digital Communications and Networks》 SCIE EI CSCD 2025年第4期1090-1101,共12页
Accurate early classification of elephant flows(elephants)is important for network management and resource optimization.Elephant models,mainly based on the byte count of flows,can always achieve high accuracy,but not ... Accurate early classification of elephant flows(elephants)is important for network management and resource optimization.Elephant models,mainly based on the byte count of flows,can always achieve high accuracy,but not in a time-efficient manner.The time efficiency becomes even worse when the flows to be classified are sampled by flow entry timeout over Software-Defined Networks(SDNs)to achieve a better resource efficiency.This paper addresses this situation by combining co-training and Reinforcement Learning(RL)to enable a closed-loop classification approach that divides the entire classification process into episodes,each involving two elephant models.One predicts elephants and is retrained by a selection of flows automatically labeled online by the other.RL is used to formulate a reward function that estimates the values of the possible actions based on the current states of both models and further adjusts the ratio of flows to be labeled in each phase.Extensive evaluation based on real traffic traces shows that the proposed approach can stably predict elephants using the packets received in the first 10% of their lifetime with an accuracy of over 80%,and using only about 10% more control channel bandwidth than the baseline over the evolved SDNs. 展开更多
关键词 Software-defined network Flow classification Co-training Reinforcement learning Flow entry timeout
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Detecting and Mitigating Distributed Denial of Service Attacks in Software-Defined Networking 认领 引用
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作者 Abdullah M.Alnajim Faisal Mohammed Alotaibi Sheroz Khan 《Computers, Materials & Continua》 SCIE EI 2025年第6期4515-4535,共21页
Distributed denial of service(DDoS)attacks are common network attacks that primarily target Internet of Things(IoT)devices.They are critical for emerging wireless services,especially for applications with limited late... Distributed denial of service(DDoS)attacks are common network attacks that primarily target Internet of Things(IoT)devices.They are critical for emerging wireless services,especially for applications with limited latency.DDoS attacks pose significant risks to entrepreneurial businesses,preventing legitimate customers from accessing their websites.These attacks require intelligent analytics before processing service requests.Distributed denial of service(DDoS)attacks exploit vulnerabilities in IoT devices by launchingmulti-point distributed attacks.These attacks generate massive traffic that overwhelms the victim’s network,disrupting normal operations.The consequences of distributed denial of service(DDoS)attacks are typically more severe in software-defined networks(SDNs)than in traditional networks.The centralised architecture of these networks can exacerbate existing vulnerabilities,as these weaknesses may not be effectively addressed in this model.The preliminary objective for detecting and mitigating distributed denial of service(DDoS)attacks in software-defined networks(SDN)is to monitor traffic patterns and identify anomalies that indicate distributed denial of service(DDoS)attacks.It implements measures to counter the effects ofDDoS attacks,and ensure network reliability and availability by leveraging the flexibility and programmability of SDN to adaptively respond to threats.The authors present a mechanism that leverages the OpenFlow and sFlow protocols to counter the threats posed by DDoS attacks.The results indicate that the proposed model effectively mitigates the negative effects of DDoS attacks in an SDN environment. 展开更多
关键词 Software-defined networking(SDN) distributed denial of service(DDoS)attack sampling Flow(sFlow) OpenFlow OpenDaylight controller
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A Survey of Link Failure Detection and Recovery in Software-Defined Networks 认领 引用
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作者 Suheib Alhiyari Siti Hafizah AB Hamid Nur Nasuha Daud 《Computers, Materials & Continua》 SCIE EI 2025年第1期103-137,共35页
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
关键词 Software defined networking failure detection failure recovery restoration protection
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On Reliability-optimized Controller Placement for Software-Defined Networks 认领 引用 被引量：30
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作者 HU Yannan WANG Wendong +2 位作者 GONG Xiangyang QUE Xirong CHENG Shiduan 《China Communications》 SCIE CSCD 2014年第2期38-54,共17页
By decoupling control plane and data plane,Software-Defined Networking(SDN)approach simplifies network management and speeds up network innovations.These benefits have led not only to prototypes,but also real SDN depl... By decoupling control plane and data plane,Software-Defined Networking(SDN)approach simplifies network management and speeds up network innovations.These benefits have led not only to prototypes,but also real SDN deployments.For wide-area SDN deployments,multiple controllers are often required,and the placement of these controllers becomes a particularly important task in the SDN context.This paper studies the problem of placing controllers in SDNs,so as to maximize the reliability of SDN control networks.We present a novel metric,called expected percentage of control path loss,to characterize the reliability of SDN control networks.We formulate the reliability-aware control placement problem,prove its NP-hardness,and examine several placement algorithms that can solve this problem.Through extensive simulations using real topologies,we show how the number of controllers and their placement influence the reliability of SDN control networks.Besides,we also found that,through strategic controller placement,the reliability of SDN control networks can be significantly improved without introducing unacceptable switch-to-controller latencies. 展开更多
关键词 Software-Defined Networking controller placement reliability networkoptimization
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EARS: Intelligence-Driven Experiential Network Architecture for Automatic Routing in Software-Defined Networking 认领 引用 被引量：9
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作者 Yuxiang Hu Ziyong Li +2 位作者 Julong Lan Jiangxing Wu Lan Yao 《China Communications》 SCIE CSCD 2020年第2期149-162,共14页
Software-Defined Networking(SDN)adapts logically-centralized control by decoupling control plane from data plane and provides the efficient use of network resources.However,due to the limitation of traditional routing... Software-Defined Networking(SDN)adapts logically-centralized control by decoupling control plane from data plane and provides the efficient use of network resources.However,due to the limitation of traditional routing strategies relying on manual configuration,SDN may suffer from link congestion and inefficient bandwidth allocation among flows,which could degrade network performance significantly.In this paper,we propose EARS,an intelligence-driven experiential network architecture for automatic routing.EARS adapts deep reinforcement learning(DRL)to simulate the human methods of learning experiential knowledge,employs the closed-loop network control mechanism incorporating with network monitoring technologies to realize the interaction with network environment.The proposed EARS can learn to make better control decision from its own experience by interacting with network environment and optimize the network intelligently by adjusting services and resources offered based on network requirements and environmental conditions.Under the network architecture,we design the network utility function with throughput and delay awareness,differentiate flows based on their size characteristics,and design a DDPGbased automatic routing algorithm as DRL decision brain to find the near-optimal paths for mice and elephant flows.To validate the network architecture,we implement it on a real network environment.Extensive simulation results show that EARS significantly improve the network throughput and reduces the average packet delay in comparison with baseline schemes(e.g.OSPF,ECMP). 展开更多
关键词 software-defined networking(SDN) intelligence-driven experiential network deep reinforcement learning(DRL) automatic routing
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Challenge-based collaborative intrusion detection in software-defined networking: An evaluation 认领 引用 被引量：6
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作者 Wenjuan Li Yu Wang +3 位作者 Zhiping Jin Keping Yu Jin Li Yang Xiang 《Digital Communications and Networks》 SCIE EI CSCD 2021年第2期257-263,共7页
Software-Defined Networking(SDN)is an emerging architecture that enables a computer network to be intelligently and centrally controlled via software applications.It can help manage the whole network environment in a ... Software-Defined Networking(SDN)is an emerging architecture that enables a computer network to be intelligently and centrally controlled via software applications.It can help manage the whole network environment in a consistent and holistic way,without the need of understanding the underlying network structure.At present,SDN may face many challenges like insider attacks,i.e.,the centralized control plane would be attacked by malicious underlying devices and switches.To protect the security of SDN,effective detection approaches are indispensable.In the literature,challenge-based collaborative intrusion detection networks(CIDNs)are an effective detection framework in identifying malicious nodes.It calculates the nodes'reputation and detects a malicious node by sending out a special message called a challenge.In this work,we devise a challenge-based CIDN in SDN and measure its performance against malicious internal nodes.Our results demonstrate that such a mechanism can be effective in SDN environments. 展开更多
关键词 Software-defined networking Trust management Collaborative intrusion detection Insider attack Challenge mechanism
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Quality of Service Improvement with Optimal Software-Defined Networking Controller and Control Plane Clustering 认领 引用 被引量：12
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作者 Jehad Ali Byeong-hee Roh 《Computers, Materials & Continua》 SCIE EI 2021年第4期849-875,共27页
The controller is indispensable in software-defined networking(SDN).With several features,controllers monitor the network and respond promptly to dynamic changes.Their performance affects the quality-of-service(QoS)in... The controller is indispensable in software-defined networking(SDN).With several features,controllers monitor the network and respond promptly to dynamic changes.Their performance affects the quality-of-service(QoS)in SDN.Every controller supports a set of features.However,the support of the features may be more prominent in one controller.Moreover,a single controller leads to performance,single-point-of-failure(SPOF),and scalability problems.To overcome this,a controller with an optimum feature set must be available for SDN.Furthermore,a cluster of optimum feature set controllers will overcome an SPOF and improve the QoS in SDN.Herein,leveraging an analytical network process(ANP),we rank SDN controllers regarding their supporting features and create a hierarchical control plane based cluster(HCPC)of the highly ranked controller computed using the ANP,evaluating their performance for the OS3E topology.The results demonstrated in Mininet reveal that a HCPC environment with an optimum controller achieves an improved QoS.Moreover,the experimental results validated in Mininet show that our proposed approach surpasses the existing distributed controller clustering(DCC)schemes in terms of several performance metrics i.e.,delay,jitter,throughput,load balancing,scalability and CPU(central processing unit)utilization. 展开更多
关键词 Quality-of-service software-defined networking controller hierarchical control plane clustering scalability
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On the use of the genetic programming for balanced load distribution in software-defined networks 认领 引用 被引量：4
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作者 Shahram Jamali Amin Badirzadeh Mina Soltani Siapoush 《Digital Communications and Networks》 SCIE 2019年第4期288-296,共9页
As a new networking paradigm,Software-Defined Networking(SDN)enables us to cope with the limitations of traditional networks.SDN uses a controller that has a global view of the network and switch devices which act as ... As a new networking paradigm,Software-Defined Networking(SDN)enables us to cope with the limitations of traditional networks.SDN uses a controller that has a global view of the network and switch devices which act as packet forwarding hardware,known as“OpenFlow switches”.Since load balancing service is essential to distribute workload across servers in data centers,we propose an effective load balancing scheme in SDN,using a genetic programming approach,called Genetic Programming based Load Balancing(GPLB).We formulate the problem to find a path:1)with the best bottleneck switch which has the lowest capacity within bottleneck switches of each path,2)with the shortest path,and 3)requiring the less possible operations.For the purpose of choosing the real-time least loaded path,GPLB immediately calculates the integrated load of paths based on the information that receives from the SDN controller.Hence,in this design,the controller sends the load information of each path to the load balancing algorithm periodically and then the load balancing algorithm returns a least loaded path to the controller.In this paper,we use the Mininet emulator and the OpenDaylight controller to evaluate the effectiveness of the GPLB.The simulative study of the GPLB shows that there is a big improvement in performance metrics and the latency and the jitter are minimized.The GPLB also has the maximum throughput in comparison with related works and has performed better in the heavy traffic situation.The results show that our model stands smartly while not increasing further overhead. 展开更多
关键词 Software-defined networking OpenFlow Mininet OpenDaylight Load balancing
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Orchestrating Network Functions in Software-Defined Networks 认领 引用 被引量：2
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作者 Hongchao Hu Lin Pang +1 位作者 Zhenpeng Wang Guozhen Cheng 《China Communications》 SCIE CSCD 2017年第2期104-117,共14页
Software.defined networking(SDN) enables third.part companies to participate in the network function innovations. A number of instances for one network function will inevitably co.exist in the network. Although some o... Software.defined networking(SDN) enables third.part companies to participate in the network function innovations. A number of instances for one network function will inevitably co.exist in the network. Although some orchestration architecture has been proposed to chain network functions, rare works are focused on how to optimize this process. In this paper, we propose an optimized model for network function orchestration, function combination model(FCM). Our main contributions are as following. First, network functions are featured with a new abstraction, and are open to external providers. And FCM identifies network functions using unique type, and organizes their instances distributed over the network with the appropriate way. Second, with the specialized demands, we can combine function instances under the global network views, and formulate it into the problem of Boolean linear program(BLP). A simulated annealing algorithm is designed to approach optimal solution for this BLP. Finally, the numerical experiment demonstrates that our model can create outstanding composite schemas efficiently. 展开更多
关键词 software-defined network network function function orchestrating
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A Novel Features Prioritization Mechanism for Controllers in Software-Defined Networking 认领 引用 被引量：1
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作者 Jehad Ali Byungkyu Lee +2 位作者 Jimyung Oh Jungtae Lee Byeong-hee Roh 《Computers, Materials & Continua》 SCIE EI 2021年第10期267-282,共16页
The controller in software-defined networking(SDN)acts as strategic point of control for the underlying network.Multiple controllers are available,and every single controller retains a number of features such as the O... The controller in software-defined networking(SDN)acts as strategic point of control for the underlying network.Multiple controllers are available,and every single controller retains a number of features such as the OpenFlow version,clustering,modularity,platform,and partnership support,etc.They are regarded as vital when making a selection among a set of controllers.As such,the selection of the controller becomes a multi-criteria decision making(MCDM)problem with several features.Hence,an increase in this number will increase the computational complexity of the controller selection process.Previously,the selection of controllers based on features has been studied by the researchers.However,the prioritization of features has gotten less attention.Moreover,several features increase the computational complexity of the selection process.In this paper,we propose a mathematical modeling for feature prioritization with analytical network process(ANP)bridge model for SDN controllers.The results indicate that a prioritized features model lead to a reduction in the computational complexity of the selection of SDN controller.In addition,our model generates prioritized features for SDN controllers. 展开更多
关键词 Software-defined networking controllers feature-based selection quality-of-service analytical network process analytical hierarchy process
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A Game-Theoretic Approach to Elastic Control in Software-Defined Networking 认领 引用 被引量：7
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作者 Hongchang Chen Guozhen Cheng Zhiming Wang 《China Communications》 SCIE CSCD 2016年第5期103-109,共7页
Elastic control could balance the distributed control plane in Software-Defined Networking(SDN). Dynamic switch migration has been proposed to achieve it. However, existing schemes mainly focus on how to execute migra... Elastic control could balance the distributed control plane in Software-Defined Networking(SDN). Dynamic switch migration has been proposed to achieve it. However, existing schemes mainly focus on how to execute migration operation, but not why. This paper designs a decision-making mechanism based on zero-sum game theory to reelect a new controller as the master for migrated switches. It first chooses a switch for migration in the heavy controller which invites its neighbors as the game players to compete for the master role of this switch in the game-playing field(GPF) which is an occasional and loose domain for game-playing. Second, based on the concept of GPF, we design a decentralized strategy to play the game and determine which player as the final master. We implement it by extending the Open Flow protocol. Finally, numerical results demonstrate that our distributed strategy can approach elastic control plane with better performance. 展开更多
关键词 software-defined networking master election game theory OpenFlow
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Artificial Intelligence Based Reliable Load Balancing Framework in Software-Defined Networks 认领 引用 被引量：1
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作者 Mohammad Riyaz Belgaum Fuead Ali +3 位作者 Zainab Alansari Shahrulniza Musa Muhammad Mansoor Alam M.S.Mazliham 《Computers, Materials & Continua》 SCIE EI 2022年第1期251-266,共16页
Software-defined networking(SDN)plays a critical role in transforming networking from traditional to intelligent networking.The increasing demand for services from cloud users has increased the load on the network.An ... Software-defined networking(SDN)plays a critical role in transforming networking from traditional to intelligent networking.The increasing demand for services from cloud users has increased the load on the network.An efficient system must handle various loads and increasing needs representing the relationships and dependence of businesses on automated measurement systems and guarantee the quality of service(QoS).Themultiple paths from source to destination give a scope to select an optimal path by maintaining an equilibrium of load using some best algorithms.Moreover,the requests need to be transferred to reliable network elements.To address SDN’s current and future challenges,there is a need to know how artificial intelligence(AI)optimization techniques can efficiently balance the load.This study aims to explore two artificial intelligence optimization techniques,namely Ant Colony Optimization(ACO)and Particle Swarm Optimization(PSO),used for load balancing in SDN.Further,we identified that a modification to the existing optimization technique could improve the performance by using a reliable link and node to form the path to reach the target node and improve load balancing.Finally,we propose a conceptual framework for SDN futurology by evaluating node and link reliability,which can balance the load efficiently and improve QoS in SDN. 展开更多
关键词 Ant colony optimization load balancing particle swarm optimization quality of service reliability software-defined networking
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Achieving Consistence for Cross-Domain WAN Control in Software-Defined Networks 认领 引用 被引量：3
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作者 ZHOU Boyang WU Chunming +3 位作者 GAO Wen HONG Xiaoyan JIANG Ming CHEN Shuangxi 《China Communications》 SCIE CSCD 2015年第10期136-146,共11页
When applying Software-Defined Networks(SDN) to WANs,the SDN flexibility enables the cross-domain control to achieve a better control scalability.However,the control consistence is required by all the cross-domain ser... When applying Software-Defined Networks(SDN) to WANs,the SDN flexibility enables the cross-domain control to achieve a better control scalability.However,the control consistence is required by all the cross-domain services,to ensure the data plane configured in consensus for different domains.Such consistence process is complicated by potential failure and errors of WANs.In this paper,we propose a consistence layer to actively and passively snapshot the cross-domain control states,to reduce the complexities of service realizations.We implement the layer and evaluate performance in the PlanetLab testbed for the WAN emulation.The testbed conditions are extremely enlarged comparing to the real network.The results show its scalability,reliability and responsiveness in dealing with the control dynamics.In the normalized results,the active and passive snapshots are executed with the mean times of 1.873 s and 105 ms in135 controllers,indicating its readiness to be used in the real network. 展开更多
关键词 software-defined networking distributed control plane cross-domain control
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AQROM:A quality of service aware routing optimization mechanism based on asynchronous advantage actor-critic in software-defined networks 认领 引用 被引量：1
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作者 Wei Zhou Xing Jiang +4 位作者 Qingsong Luo Bingli Guo Xiang Sun Fengyuan Sun Lingyu Meng 《Digital Communications and Networks》 SCIE CSCD 2024年第5期1405-1414,共10页
In Software-Defined Networks(SDNs),determining how to efficiently achieve Quality of Service(QoS)-aware routing is challenging but critical for significantly improving the performance of a network,where the metrics of... In Software-Defined Networks(SDNs),determining how to efficiently achieve Quality of Service(QoS)-aware routing is challenging but critical for significantly improving the performance of a network,where the metrics of QoS can be defined as,for example,average latency,packet loss ratio,and throughput.The SDN controller can use network statistics and a Deep Reinforcement Learning(DRL)method to resolve this challenge.In this paper,we formulate dynamic routing in an SDN as a Markov decision process and propose a DRL algorithm called the Asynchronous Advantage Actor-Critic QoS-aware Routing Optimization Mechanism(AQROM)to determine routing strategies that balance the traffic loads in the network.AQROM can improve the QoS of the network and reduce the training time via dynamic routing strategy updates;that is,the reward function can be dynamically and promptly altered based on the optimization objective regardless of the network topology and traffic pattern.AQROM can be considered as one-step optimization and a black-box routing mechanism in high-dimensional input and output sets for both discrete and continuous states,and actions with respect to the operations in the SDN.Extensive simulations were conducted using OMNeT++and the results demonstrated that AQROM 1)achieved much faster and stable convergence than the Deep Deterministic Policy Gradient(DDPG)and Advantage Actor-Critic(A2C),2)incurred a lower packet loss ratio and latency than Open Shortest Path First(OSPF),DDPG,and A2C,and 3)resulted in higher and more stable throughput than OSPF,DDPG,and A2C. 展开更多
关键词 Software-defined networks Asynchronous advantage actor-critic QoS-aware routing optimization mechanism
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A Novel Method for Routing Optimization in Software-Defined Networks 认领 引用 被引量：1
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作者 Salem Alkhalaf Fahad Alturise 《Computers, Materials & Continua》 SCIE EI 2022年第12期6393-6405,共13页
Software-defined network(SDN)is a new form of network architecture that has programmability,ease of use,centralized control,and protocol independence.It has received high attention since its birth.With SDN network arc... Software-defined network(SDN)is a new form of network architecture that has programmability,ease of use,centralized control,and protocol independence.It has received high attention since its birth.With SDN network architecture,network management becomes more efficient,and programmable interfaces make network operations more flexible and can meet the different needs of various users.The mainstream communication protocol of SDN is OpenFlow,which contains aMatch Field in the flow table structure of the protocol,which matches the content of the packet header of the data received by the switch,and completes the corresponding actions according to the matching results,getting rid of the dependence on the protocol to avoid designing a new protocol.In order to effectively optimize the routing forSDN,this paper proposes a novel algorithm based on reinforcement learning.The proposed technique canmaximize numerous objectives to dynamically update the routing strategy,and it has great generality and is not reliant on any specific network state.The control of routing strategy is more complicated than many Q-learning-based algorithms due to the employment of reinforcement learning.The performance of the method is tested by experiments using the OMNe++simulator.The experimental results reveal that our PPO-based SDN routing control method has superior performance and stability than existing algorithms. 展开更多
关键词 Reinforcement learning routing algorithm software-defined network optimization
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Performance Evaluation of Topologies for Multi-Domain Software-Defined Networking 认领 引用
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作者 Jiangyuan Yao Weiping Yang +5 位作者 Shuhua Weng Minrui Wang Zheng Jiang Deshun Li Yahui Li Xingcan Cao 《Computer Systems Science & Engineering》 SCIE EI 2023年第10期741-755,共15页
Software-defined networking(SDN)is widely used in multiple types of data center networks,and these distributed data center networks can be integrated into a multi-domain SDN by utilizing multiple controllers.However,t... Software-defined networking(SDN)is widely used in multiple types of data center networks,and these distributed data center networks can be integrated into a multi-domain SDN by utilizing multiple controllers.However,the network topology of each control domain of SDN will affect the performance of the multidomain network,so performance evaluation is required before the deployment of the multi-domain SDN.Besides,there is a high cost to build real multi-domain SDN networks with different topologies,so it is necessary to use simulation testing methods to evaluate the topological performance of the multi-domain SDN network.As there is a lack of existing methods to construct a multi-domain SDN simulation network for the tool to evaluate the topological performance automatically,this paper proposes an automated multi-domain SDN topology performance evaluation framework,which supports multiple types of SDN network topologies in cooperating to construct a multi-domain SDN network.The framework integrates existing single-domain SDN simulation tools with network performance testing tools to realize automated performance evaluation of multidomain SDN network topologies.We designed and implemented a Mininet-based simulation tool that can connect multiple controllers and run user-specified topologies in multiple SDN control domains to build and test multi-domain SDN networks faster.Then,we used the tool to perform performance tests on various data center network topologies in single-domain and multi-domain SDN simulation environments.Test results show that Space Shuffle has the most stable performance in a single-domain environment,and Fat-tree has the best performance in a multi-domain environment.Also,this tool has the characteristics of simplicity and stability,which can meet the needs of multi-domain SDN topology performance evaluation. 展开更多
关键词 Software-defined networking emulation network multi-domain SDN data center network topology
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Toward Secure Software-Defined Networks Using Machine Learning: A Review, Research Challenges, and Future Directions 认领 引用
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作者 Muhammad Waqas Nadeem Hock Guan Goh +1 位作者 Yichiet Aun Vasaki Ponnusamy 《Computer Systems Science & Engineering》 SCIE EI 2023年第11期2201-2217,共17页
Over the past few years,rapid advancements in the internet and communication technologies have led to increasingly intricate and diverse networking systems.As a result,greater intelligence is necessary to effectively ... Over the past few years,rapid advancements in the internet and communication technologies have led to increasingly intricate and diverse networking systems.As a result,greater intelligence is necessary to effectively manage,optimize,and maintain these systems.Due to their distributed nature,machine learning models are challenging to deploy in traditional networks.However,Software-Defined Networking(SDN)presents an opportunity to integrate intelligence into networks by offering a programmable architecture that separates data and control planes.SDN provides a centralized network view and allows for dynamic updates of flow rules and softwarebased traffic analysis.While the programmable nature of SDN makes it easier to deploy machine learning techniques,the centralized control logic also makes it vulnerable to cyberattacks.To address these issues,recent research has focused on developing powerful machine-learning methods for detecting and mitigating attacks in SDN environments.This paper highlighted the countermeasures for cyberattacks on SDN and how current machine learningbased solutions can overcome these emerging issues.We also discuss the pros and cons of using machine learning algorithms for detecting and mitigating these attacks.Finally,we highlighted research issues,gaps,and challenges in developing machine learning-based solutions to secure the SDN controller,to help the research and network community to develop more robust and reliable solutions. 展开更多
关键词 Botnet attack deep learning distributed denial of service machine learning network security software-defined network
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A Novel Floodless Service Discovery Mechanism Designed for Software-Defined Networking 认领 引用
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作者 WANG Jian HUANG Tao +1 位作者 LIU Jiang LIU Yunjie 《China Communications》 SCIE CSCD 2014年第2期12-25,共14页
The low-cost,self-configuration capability and"plug-and-play"feature of Ethernet establishes its dominant position in the local area networks(LAN).However,it is hard to extend to large scale because of the l... The low-cost,self-configuration capability and"plug-and-play"feature of Ethernet establishes its dominant position in the local area networks(LAN).However,it is hard to extend to large scale because of the legacy broadcast-based service discovery mechanism.Therefore,to solve this problem,a new split network architecture named Software-Defined Networking(SDN)is introduced in this paper,and a novel floodless service discovery mechanism(FSDM)for SDN is designed.For the FSDM,the widespread broadcast messages for Dynamic Host Configuration Protocol(DHCP)and Address Resolution Protocol(ARP)are considered especially,respectively.Then the DHCP relay and ARP proxy are proposed to handle DHCP broadcast messages and ARP broadcast messages,respectively.The proposed FSDM in this paper can eliminate flooding completely,reserve the autoconfiguration characteristics.Particularly,there is no need to change the existing hardware,software and protocols of hosts for the proposed scheme.Finally,the simulation results are demonstrated to show that our proposed model allows redundant links existed in network and has the property of scalability,which can significantly reduce network traffic in data plane and control traffic in control plane,and decrease the overhead of control plane. 展开更多
关键词 Software-Defined Networking flooding DHCP ARP
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Workload-aware request routing in cloud data center using software-defined networking 认领 引用
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作者 Haitao Yuan Jing Bi Bohu Li 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2015年第1期151-160,共10页
Large latency of applications will bring revenue loss to cloud infrastructure providers in the cloud data center. The existing controllers of software-defined networking architecture can fetch and process traffic info... Large latency of applications will bring revenue loss to cloud infrastructure providers in the cloud data center. The existing controllers of software-defined networking architecture can fetch and process traffic information in the network. Therefore, the controllers can only optimize the network latency of applications. However, the serving latency of applications is also an important factor in delivered user-experience for arrival requests. Unintelligent request routing will cause large serving latency if arrival requests are allocated to overloaded virtual machines. To deal with the request routing problem, this paper proposes the workload-aware software-defined networking controller architecture. Then, request routing algorithms are proposed to minimize the total round trip time for every type of request by considering the congestion in the network and the workload in virtual machines（VMs）. This paper finally provides the evaluation of the proposed algorithms in a simulated prototype. The simulation results show that the proposed methodology is efficient compared with the existing approaches. 展开更多
关键词 cloud data center（CDC） software-defined networking request routing resource allocation network latency optimization
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Migration to Software-Defined Networks:the Customers' View 认领 引用
20
作者 Tingting Yuan Xiaohong Huang +1 位作者 Maode Ma Pei Zhang 《China Communications》 SCIE CSCD 2017年第10期1-11,共11页
Software Defined Networking(SDN) provides a flexible and convenient way to support fine-grained traffic-engineering(TE). Besides, SDN also provides better Quality of Experience(QoE) for customers. However, the policy ... Software Defined Networking(SDN) provides a flexible and convenient way to support fine-grained traffic-engineering(TE). Besides, SDN also provides better Quality of Experience(QoE) for customers. However, the policy of the evolution from legacy networks to the SDNs overemphasizes the controllability of the network or TE while ignoring the customers' benefit. Standing in the customers' position, we propose an optimization scheme, named as Optimal Migration Schedule based on Customers' Benefit(OMSB), to produce an optimized migration schedule and maximize the benefit of customers. Not only the quality and quantity of paths availed by migration, but also the number of flows from the customers that can use these multi-paths are taken into consideration for the scheduling. We compare the OMSB with other six migration schemes in terms of the benefit of customers. Our results suggest that the sequence of the migration plays a vital role for customers, especially in the early stages of the network migration to the SDN. 展开更多
关键词 network management network migration software-defined networking traffic engineering
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