Solving the controller placement problem (CPP) in an SDN architecture with multiple controllers has a significant impact on control overhead in the network, especially in multihop wireless networks (MWNs). The generat...Solving the controller placement problem (CPP) in an SDN architecture with multiple controllers has a significant impact on control overhead in the network, especially in multihop wireless networks (MWNs). The generated control overhead consists of controller-device and inter-controller communications to discover the network topology, exchange configurations, and set up and modify flow tables in the control plane. However, due to the high complexity of the proposed optimization model to the CPP, heuristic algorithms have been reported to find near-optimal solutions faster for large-scale wired networks. In this paper, the objective is to extend those existing heuristic algorithms to solve a proposed optimization model to the CPP in software-<span>defined multihop wireless networking</span><span> (SDMWN).</span>Our results demonstrate that using ranking degrees assigned to the possible controller placements, including the average distance to other devices as a degree or the connectivity degree of each placement, the extended heuristic algorithms are able to achieve the optimal solution in small-scale networks in terms of the generated control overhead and the number of controllers selected in the network. As a result, using extended heuristic algorithms, the average number of hops among devices and their assigned controllers as well as among controllers will be reduced. Moreover, these algorithms are able tolower<span "=""> </span>the control overhead in large-scale networks and select fewer controllers compared to an extended algorithm that solves the CPP in SDMWN based on a randomly selected controller placement approach.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
In SDN,the control logic of packet processing devices is moved onto the SDN centralized controller.This decoupled networking architecture creates some critical concerns when compared to traditional distributed archite...In SDN,the control logic of packet processing devices is moved onto the SDN centralized controller.This decoupled networking architecture creates some critical concerns when compared to traditional distributed architectures.One primary concern in this architecture is the placement of the controller,which is commonly known as the CPP.From our extensive literature review,we identify that there is no strict placement rule that best fits every network in SDN.Dynamic addition and deletion of controllers is inevitable.Motivated from this,in this paper,we attempt to transform the CPP into a CSP.We show that,in the dynamic SDN environment,researchers need to pay attention to CSP issues.The clear advantage of CSP over CPP is that,in the dynamic SDN ecosystem,we can answer fundamental questions about the control plane performance,i.e.,minimum number of controllers,their workload distribution,and placement/locations.Furthermore,we can meet strict,application-specific,QoS constraints.展开更多
This review article provides a comprehensive analysis of the latest advancements and persistent challenges in Software-Defined Wide Area Networks(SD-WANs),with a particular emphasis on the multi-objective Controller P...This review article provides a comprehensive analysis of the latest advancements and persistent challenges in Software-Defined Wide Area Networks(SD-WANs),with a particular emphasis on the multi-objective Controller Placement Problem(CPP).As SD-WAN technology continues to gain prominence for its capacity to offer flexible and efficient network management,the task of 36optimally placing controllers—responsible for orchestrating and managing network traffic—remains a critical yet complex challenge.This review delves into recent innovations in multi-objective controller placement strategies,including clustering techniques,heuristic-based approaches,and the integration of machine learning and deep learning models.Each methodology is critically evaluated in terms of its ability to minimize network latency,enhance fault tolerance,and improve overall network performance.Furthermore,this paper discusses the inherent limitations and challenges associated with these techniques,providing a critical evaluation of their current utility and outlining potential avenues for future research.By offering a thorough overview of state-of-the-art approaches to multi-objective controller placement in SD-WANs,this review aims to inform ongoing advancements and highlight emerging research opportunities in this evolving field.展开更多
Software-defined networking(SDN)algorithms are gaining increas-ing interest and are making networks flexible and agile.The basic idea of SDN is to move the control planes to more than one server’s named controllers a...Software-defined networking(SDN)algorithms are gaining increas-ing interest and are making networks flexible and agile.The basic idea of SDN is to move the control planes to more than one server’s named controllers and limit the data planes to numerous sending network components,enabling flexible and dynamic network management.A distinctive characteristic of SDN is that it can logically centralize the control plane by utilizing many physical controllers.The deployment of the controller—that is,the controller placement problem(CPP)—becomes a vital model challenge.Through the advancements of blockchain technology,data integrity between nodes can be enhanced with no requirement for a trusted third party.Using the lat-est developments in blockchain technology,this article designs a novel sea turtle foraging optimization algorithm for the controller placement problem(STFOA-CPP)with blockchain-based intrusion detection in an SDN environ-ment.The major intention of the STFOA-CPP technique is the maximization of lifetime,network connectivity,and load balancing with the minimization of latency.In addition,the STFOA-CPP technique is based on the sea turtles’food-searching characteristics of tracking the odour path of dimethyl sulphide(DMS)released from food sources.Moreover,the presented STFOA-CPP technique can adapt with the controller’s count mandated and the shift to controller mapping to variable network traffic.Finally,the blockchain can inspect the data integrity,determine significantly malicious input,and improve the robust nature of developing a trust relationship between sev-eral nodes in the SDN.To demonstrate the improved performance of the STFOA-CPP algorithm,a wide-ranging experimental analysis was carried out.The extensive comparison study highlighted the improved outcomes of the STFOA-CPP technique over other recent approaches.展开更多
The current and future status of the internet is represented by the upcoming Internet of Things(IoT).The internet can connect the huge amount of data,which contains lot of processing operations and efforts to transfer...The current and future status of the internet is represented by the upcoming Internet of Things(IoT).The internet can connect the huge amount of data,which contains lot of processing operations and efforts to transfer the pieces of information.The emerging IoT technology in which the smart ecosystem is enabled by the physical object fixed with software electronics,sensors and network connectivity.Nowadays,there are two trending technologies that take the platform i.e.,Software Defined Network(SDN)and IoT(SD-IoT).The main aim of the IoT network is to connect and organize different objects with the internet,which is managed with the control panel and data panel in the SD network.The main issue and the challenging factors in this network are the increase in the delay and latency problem between the controllers.It is more significant for wide area networks,because of the large packet propagation latency and the controller placement problem is more important in every network.In the proposed work,IoT is implementing with adaptive fuzzy controller placement using the enhanced sunflower optimization(ESFO)algorithm and Pareto Optimal Controller placement tool(POCO)for the placement problem of the controller.In order to prove the efficiency of the proposed system,it is compared with other existing methods like PASIN,hybrid SD and PSO in terms of load balance,reduced number of controllers and average latency and delay.With 2 controllers,the proposed method obtains 400 miles as average latency,which is 22.2%smaller than PSO,76.9%lesser than hybrid SD and 91.89%lesser than PASIN.展开更多
Controller placement problem(CPP)is a critical issue in software defined wireless networks(SDWN).Due to the limited power of wireless devices,CPP is facing the challenge of energy efficiency in SDWN.Nevertheless,the r...Controller placement problem(CPP)is a critical issue in software defined wireless networks(SDWN).Due to the limited power of wireless devices,CPP is facing the challenge of energy efficiency in SDWN.Nevertheless,the related research on CPP in SDWN hasn’t modeled the energy consumption of controllers so far.To prolong the lifetime of SDWN and improve the practicability of research,we rebuilt a CPP model considering the minimal transmitted power of controllers.An adaptive controller placement algorithm(ACPA)is proposed with the following two stages.First,data field method is adopted to determine sub-networks for different network topologies.Second,for each sub-network we adopt an exhaustive method to find the optimal location which meets the minimal average transmitted power to place controller.Compared with the other algorithms,the effectiveness and efficiency of the proposed scheme are validated through simulation.展开更多
This paper investigates the exact and approximate spectrum assignment properties associated with realizable output-feedback pole-placement type controllers for single-input single-output linear time-invariant time-del...This paper investigates the exact and approximate spectrum assignment properties associated with realizable output-feedback pole-placement type controllers for single-input single-output linear time-invariant time-delay systems with commensurate point delays. The controller synthesis problem is discussed through the solvability of a set of coupled diophantine equations of polynomials. An extra complexity is incorporated to the above design to cancel extra unsuitable dynamics being generated when solving the above diophantine equations. Thus, the complete controller tracks any arbitrary prefixed (either finite or delay-dependent) closed-loop spectrum. However, if the controller is simplified by deleting the above mentioned extra complexity, then the robust stability and approximated spectrum assignment are still achievable for a certain sufficiently small amount of delayed dynamics. Finally, the approximate spectrum assignment and robust stability problems are revisited under plant disturbances if the nominal controller is maintained. In the current approach, the finite spectrum assignment is only considered as a particular case to the designer's choice of a (delay-dependent) arbitrary spectrum assignment objective.展开更多
针对软件定义网络中控制平面容错布局问题,提出一种基于随机生成树的控制器布局算法DRT2CA(Minimum Two Covering Algorithm Based on Dynamic Random Spanning Tree)。该算法旨在保证冗余容错的前提下,最小化控制器数量,降低控制平面...针对软件定义网络中控制平面容错布局问题,提出一种基于随机生成树的控制器布局算法DRT2CA(Minimum Two Covering Algorithm Based on Dynamic Random Spanning Tree)。该算法旨在保证冗余容错的前提下,最小化控制器数量,降低控制平面的部署成本。通过不断生成随机生成树,并在树上采用贪心策略进行控制器布局搜索,DRT2CA算法以更少的控制器实现最小的冗余容错覆盖,有效提高系统资源利用率。实验结果表明,在不同网络规模和控制器容量下,DRT2CA算法相较于现有的冗余控制器部署算法,能够以更少的控制器部署数量实现容错控制平面布局,具有更高的冗余布局效率,为构建高效、可靠的SDN控制平面提供了创新性的解决方案。展开更多
文摘Solving the controller placement problem (CPP) in an SDN architecture with multiple controllers has a significant impact on control overhead in the network, especially in multihop wireless networks (MWNs). The generated control overhead consists of controller-device and inter-controller communications to discover the network topology, exchange configurations, and set up and modify flow tables in the control plane. However, due to the high complexity of the proposed optimization model to the CPP, heuristic algorithms have been reported to find near-optimal solutions faster for large-scale wired networks. In this paper, the objective is to extend those existing heuristic algorithms to solve a proposed optimization model to the CPP in software-<span>defined multihop wireless networking</span><span> (SDMWN).</span>Our results demonstrate that using ranking degrees assigned to the possible controller placements, including the average distance to other devices as a degree or the connectivity degree of each placement, the extended heuristic algorithms are able to achieve the optimal solution in small-scale networks in terms of the generated control overhead and the number of controllers selected in the network. As a result, using extended heuristic algorithms, the average number of hops among devices and their assigned controllers as well as among controllers will be reduced. Moreover, these algorithms are able tolower<span "=""> </span>the control overhead in large-scale networks and select fewer controllers compared to an extended algorithm that solves the CPP in SDMWN based on a randomly selected controller placement approach.
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%.
文摘In SDN,the control logic of packet processing devices is moved onto the SDN centralized controller.This decoupled networking architecture creates some critical concerns when compared to traditional distributed architectures.One primary concern in this architecture is the placement of the controller,which is commonly known as the CPP.From our extensive literature review,we identify that there is no strict placement rule that best fits every network in SDN.Dynamic addition and deletion of controllers is inevitable.Motivated from this,in this paper,we attempt to transform the CPP into a CSP.We show that,in the dynamic SDN environment,researchers need to pay attention to CSP issues.The clear advantage of CSP over CPP is that,in the dynamic SDN ecosystem,we can answer fundamental questions about the control plane performance,i.e.,minimum number of controllers,their workload distribution,and placement/locations.Furthermore,we can meet strict,application-specific,QoS constraints.
文摘This review article provides a comprehensive analysis of the latest advancements and persistent challenges in Software-Defined Wide Area Networks(SD-WANs),with a particular emphasis on the multi-objective Controller Placement Problem(CPP).As SD-WAN technology continues to gain prominence for its capacity to offer flexible and efficient network management,the task of 36optimally placing controllers—responsible for orchestrating and managing network traffic—remains a critical yet complex challenge.This review delves into recent innovations in multi-objective controller placement strategies,including clustering techniques,heuristic-based approaches,and the integration of machine learning and deep learning models.Each methodology is critically evaluated in terms of its ability to minimize network latency,enhance fault tolerance,and improve overall network performance.Furthermore,this paper discusses the inherent limitations and challenges associated with these techniques,providing a critical evaluation of their current utility and outlining potential avenues for future research.By offering a thorough overview of state-of-the-art approaches to multi-objective controller placement in SD-WANs,this review aims to inform ongoing advancements and highlight emerging research opportunities in this evolving field.
文摘Software-defined networking(SDN)algorithms are gaining increas-ing interest and are making networks flexible and agile.The basic idea of SDN is to move the control planes to more than one server’s named controllers and limit the data planes to numerous sending network components,enabling flexible and dynamic network management.A distinctive characteristic of SDN is that it can logically centralize the control plane by utilizing many physical controllers.The deployment of the controller—that is,the controller placement problem(CPP)—becomes a vital model challenge.Through the advancements of blockchain technology,data integrity between nodes can be enhanced with no requirement for a trusted third party.Using the lat-est developments in blockchain technology,this article designs a novel sea turtle foraging optimization algorithm for the controller placement problem(STFOA-CPP)with blockchain-based intrusion detection in an SDN environ-ment.The major intention of the STFOA-CPP technique is the maximization of lifetime,network connectivity,and load balancing with the minimization of latency.In addition,the STFOA-CPP technique is based on the sea turtles’food-searching characteristics of tracking the odour path of dimethyl sulphide(DMS)released from food sources.Moreover,the presented STFOA-CPP technique can adapt with the controller’s count mandated and the shift to controller mapping to variable network traffic.Finally,the blockchain can inspect the data integrity,determine significantly malicious input,and improve the robust nature of developing a trust relationship between sev-eral nodes in the SDN.To demonstrate the improved performance of the STFOA-CPP algorithm,a wide-ranging experimental analysis was carried out.The extensive comparison study highlighted the improved outcomes of the STFOA-CPP technique over other recent approaches.
文摘The current and future status of the internet is represented by the upcoming Internet of Things(IoT).The internet can connect the huge amount of data,which contains lot of processing operations and efforts to transfer the pieces of information.The emerging IoT technology in which the smart ecosystem is enabled by the physical object fixed with software electronics,sensors and network connectivity.Nowadays,there are two trending technologies that take the platform i.e.,Software Defined Network(SDN)and IoT(SD-IoT).The main aim of the IoT network is to connect and organize different objects with the internet,which is managed with the control panel and data panel in the SD network.The main issue and the challenging factors in this network are the increase in the delay and latency problem between the controllers.It is more significant for wide area networks,because of the large packet propagation latency and the controller placement problem is more important in every network.In the proposed work,IoT is implementing with adaptive fuzzy controller placement using the enhanced sunflower optimization(ESFO)algorithm and Pareto Optimal Controller placement tool(POCO)for the placement problem of the controller.In order to prove the efficiency of the proposed system,it is compared with other existing methods like PASIN,hybrid SD and PSO in terms of load balance,reduced number of controllers and average latency and delay.With 2 controllers,the proposed method obtains 400 miles as average latency,which is 22.2%smaller than PSO,76.9%lesser than hybrid SD and 91.89%lesser than PASIN.
基金supported by the Open Research Fund of Key Laboratory of Space Utilization,Chinese Academy of Sciences(No.LSU-KFJJ-2018-06)the International Research Cooperation Seed Fund of Beijing University of Technology(No.2018B41)
文摘Controller placement problem(CPP)is a critical issue in software defined wireless networks(SDWN).Due to the limited power of wireless devices,CPP is facing the challenge of energy efficiency in SDWN.Nevertheless,the related research on CPP in SDWN hasn’t modeled the energy consumption of controllers so far.To prolong the lifetime of SDWN and improve the practicability of research,we rebuilt a CPP model considering the minimal transmitted power of controllers.An adaptive controller placement algorithm(ACPA)is proposed with the following two stages.First,data field method is adopted to determine sub-networks for different network topologies.Second,for each sub-network we adopt an exhaustive method to find the optimal location which meets the minimal average transmitted power to place controller.Compared with the other algorithms,the effectiveness and efficiency of the proposed scheme are validated through simulation.
文摘This paper investigates the exact and approximate spectrum assignment properties associated with realizable output-feedback pole-placement type controllers for single-input single-output linear time-invariant time-delay systems with commensurate point delays. The controller synthesis problem is discussed through the solvability of a set of coupled diophantine equations of polynomials. An extra complexity is incorporated to the above design to cancel extra unsuitable dynamics being generated when solving the above diophantine equations. Thus, the complete controller tracks any arbitrary prefixed (either finite or delay-dependent) closed-loop spectrum. However, if the controller is simplified by deleting the above mentioned extra complexity, then the robust stability and approximated spectrum assignment are still achievable for a certain sufficiently small amount of delayed dynamics. Finally, the approximate spectrum assignment and robust stability problems are revisited under plant disturbances if the nominal controller is maintained. In the current approach, the finite spectrum assignment is only considered as a particular case to the designer's choice of a (delay-dependent) arbitrary spectrum assignment objective.
文摘针对软件定义网络中控制平面容错布局问题,提出一种基于随机生成树的控制器布局算法DRT2CA(Minimum Two Covering Algorithm Based on Dynamic Random Spanning Tree)。该算法旨在保证冗余容错的前提下,最小化控制器数量,降低控制平面的部署成本。通过不断生成随机生成树,并在树上采用贪心策略进行控制器布局搜索,DRT2CA算法以更少的控制器实现最小的冗余容错覆盖,有效提高系统资源利用率。实验结果表明,在不同网络规模和控制器容量下,DRT2CA算法相较于现有的冗余控制器部署算法,能够以更少的控制器部署数量实现容错控制平面布局,具有更高的冗余布局效率,为构建高效、可靠的SDN控制平面提供了创新性的解决方案。
