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 dep...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
The demand of hydrogen in oil refinery is increasing as market forces and environmental legislation, so hydrogen network management is becoming increasingly important in refineries. Most studies focused on single-obje...The demand of hydrogen in oil refinery is increasing as market forces and environmental legislation, so hydrogen network management is becoming increasingly important in refineries. Most studies focused on single-objective optimization problem for the hydrogen network, but few account for the multi-objective optimization problem. This paper presents a novel approach for modeling and multi-objective optimization for hydrogen network in refineries. An improved multi-objective optimization model is proposed based on the concept of superstructure. The optimization includes minimization of operating cost and minimization of investment cost of equipment. The proposed methodology for the multi-objective optimization of hydrogen network takes into account flow rate constraints, pressure constraints, purity constraints, impurity constraints, payback period, etc. The method considers all the feasible connections and subjects this to mixed-integer nonlinear programming （MINLP）. A deterministic optimization method is applied to solve this multi-objective optimization problem. Finally, a real case study is intro-duced to illustrate the applicability of the approach.展开更多
In order to achieve an intelligent and automated self-management network,dynamic policy configuration and selection are needed.A certain policy only suits to a certain network environment.If the network environment ch...In order to achieve an intelligent and automated self-management network,dynamic policy configuration and selection are needed.A certain policy only suits to a certain network environment.If the network environment changes,the certain policy does not suit any more.Thereby,the policy-based management should also have similar "natural selection" process.Useful policy will be retained,and policies which have lost their effectiveness are eliminated.A policy optimization method based on evolutionary learning was proposed.For different shooting times,the priority of policy with high shooting times is improved,while policy with a low rate has lower priority,and long-term no shooting policy will be dormant.Thus the strategy for the survival of the fittest is realized,and the degree of self-learning in policy management is improved.展开更多
The demands of programmability have become more and more exigent as novel network services appear, such as E-commerce, social softwares, and online videos. Commodity multi-core CPUs have been widely applied in network...The demands of programmability have become more and more exigent as novel network services appear, such as E-commerce, social softwares, and online videos. Commodity multi-core CPUs have been widely applied in network packet processing to get high programmability and reduce the time-to-market. However,there is a great gap between the packet processing performance of commodity multi-core and that of the traditional packet processing hardware, e.g., NP(Network Process). Recently, optimization of the packet processing performance of commodity multi-cores has become a hot topic in industry and academia. In this paper, based on a detailed analysis of the packet processing procedure, firstly we identify two dominating overheads, namely the virtual-to-physical address translation and the packet buffer management. Secondly, we make a comprehensive survey on the current optimization methods. Thirdly, based on the survey, the heterogeneous architecture of the commodity multi-core + FPGA is proposed as a promising way to improve the packet processing performance.Fourthly, a novel Self-Described Buffer(SDB) management technology is introduced to eliminate the overheads of the allocation and deallocation of the packet buffers offloaded to FPGA. Then, an evaluation testbed, named PIOT(Packet I/O Testbed), is designed and implemented to evaluate the packet forwarding performance. I/O capacity of different commodity multi-core CPUs and the performance of optimization methods are assessed and compared based on PIOT. At last, the future work of packet processing optimization on multi-core CPUs is discussed.展开更多
基金supported in part by the National High Technology Research and Development Program(863 Program)of China under Grant No.2011AA01A101the National High Technology Research and Development Program(863 Program)of China under Grant No.2013AA01330the National High Technology Research and Development Program(863 Program)of China under Grant No.2013AA013303
文摘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.
基金Supported by the National High Technology Research and Development Program of China （2008AA042902, 2009AA04Z162）, the Program of Introducing Talents of Discipline to University （B07031） and the National Natural Science Foundation of China （21106129）.
文摘The demand of hydrogen in oil refinery is increasing as market forces and environmental legislation, so hydrogen network management is becoming increasingly important in refineries. Most studies focused on single-objective optimization problem for the hydrogen network, but few account for the multi-objective optimization problem. This paper presents a novel approach for modeling and multi-objective optimization for hydrogen network in refineries. An improved multi-objective optimization model is proposed based on the concept of superstructure. The optimization includes minimization of operating cost and minimization of investment cost of equipment. The proposed methodology for the multi-objective optimization of hydrogen network takes into account flow rate constraints, pressure constraints, purity constraints, impurity constraints, payback period, etc. The method considers all the feasible connections and subjects this to mixed-integer nonlinear programming （MINLP）. A deterministic optimization method is applied to solve this multi-objective optimization problem. Finally, a real case study is intro-duced to illustrate the applicability of the approach.
基金National Natural Science Foundation of China(No.60534020)Cultivation Fund of the Key Scientific and Technical Innovation Project from Ministry of Education of China(No.706024)International Science Cooperation Foundation of Shanghai,China(No.061307041)
文摘In order to achieve an intelligent and automated self-management network,dynamic policy configuration and selection are needed.A certain policy only suits to a certain network environment.If the network environment changes,the certain policy does not suit any more.Thereby,the policy-based management should also have similar "natural selection" process.Useful policy will be retained,and policies which have lost their effectiveness are eliminated.A policy optimization method based on evolutionary learning was proposed.For different shooting times,the priority of policy with high shooting times is improved,while policy with a low rate has lower priority,and long-term no shooting policy will be dormant.Thus the strategy for the survival of the fittest is realized,and the degree of self-learning in policy management is improved.
基金supported by National High-tech R&D Program of China(863 Program)(Grant No.2015AA0156-03)National Natural Science Foundation of China(Grant No.61202483)
文摘The demands of programmability have become more and more exigent as novel network services appear, such as E-commerce, social softwares, and online videos. Commodity multi-core CPUs have been widely applied in network packet processing to get high programmability and reduce the time-to-market. However,there is a great gap between the packet processing performance of commodity multi-core and that of the traditional packet processing hardware, e.g., NP(Network Process). Recently, optimization of the packet processing performance of commodity multi-cores has become a hot topic in industry and academia. In this paper, based on a detailed analysis of the packet processing procedure, firstly we identify two dominating overheads, namely the virtual-to-physical address translation and the packet buffer management. Secondly, we make a comprehensive survey on the current optimization methods. Thirdly, based on the survey, the heterogeneous architecture of the commodity multi-core + FPGA is proposed as a promising way to improve the packet processing performance.Fourthly, a novel Self-Described Buffer(SDB) management technology is introduced to eliminate the overheads of the allocation and deallocation of the packet buffers offloaded to FPGA. Then, an evaluation testbed, named PIOT(Packet I/O Testbed), is designed and implemented to evaluate the packet forwarding performance. I/O capacity of different commodity multi-core CPUs and the performance of optimization methods are assessed and compared based on PIOT. At last, the future work of packet processing optimization on multi-core CPUs is discussed.
