The combination of traditional processors and Field Programmable Gate Arrays(FPGA)is shaping the future networking platform for intensive computation in resource-constrained networks and devices.These networks present...The combination of traditional processors and Field Programmable Gate Arrays(FPGA)is shaping the future networking platform for intensive computation in resource-constrained networks and devices.These networks present two key challenges of security and resource limitations.Lightweight ciphers are suitable to provide data security in such constrained environments.Implementing the lightweight PRESENT encryption algorithm in a reconfigurable platform(FPGAs)can offer secure communication service and flexibility.This paper presents hardware acceleration of security primitives in SDN using NETFPGA-10G.We implement an efficient design of the PRESENT algorithm for faster,smaller and lower power consumption hardware circuit using Verilog.We evaluate the performance of the hardware and software implementations of PRESENT.Experimental results prove that the proposed hardware design is a viable option for use in resource constrained devices in future networks and their applications.展开更多
Based on the method of symplectic geometry and variational calculation,the method for some PDEs to be ordered and analytically represented by Hamiltonian canonical system is discussed.Meanwhile some related necessar...Based on the method of symplectic geometry and variational calculation,the method for some PDEs to be ordered and analytically represented by Hamiltonian canonical system is discussed.Meanwhile some related necessary and sufficient conditions are obtained展开更多
Dimensionality reduction （DR） methods based on sparse representation as one of the hottest research topics have achieved remarkable performance in many applications in recent years. However, it＇s a challenge for ex...Dimensionality reduction （DR） methods based on sparse representation as one of the hottest research topics have achieved remarkable performance in many applications in recent years. However, it＇s a challenge for existing sparse representation based methods to solve nonlinear problem due to the limitations of seeking sparse representation of data in the original space. Motivated by kernel tricks, we proposed a new framework called empirical kernel sparse representation （EKSR） to solve nonlinear problem. In this framework, non- linear separable data are mapped into kernel space in which the nonlinear similarity can be captured, and then the data in kernel space is reconstructed by sparse representation to preserve the sparse structure, which is obtained by minimiz- ing a ~1 regularization-related objective function. EKSR pro- vides new insights into dimensionality reduction and extends two models： 1） empirical kernel sparsity preserving projec- tion （EKSPP）, which is a feature extraction method based on sparsity preserving projection （SPP）; 2） empirical kernel sparsity score （EKSS）, which is a feature selection method based on sparsity score （SS）. Both of the two methods can choose neighborhood automatically as the natural discrimi- native power of sparse representation. Compared with sev- eral existing approaches, the proposed framework can reduce computational complexity and be more convenient in prac- tice.展开更多
From the very beginning process algebra introduced the dichotomy between channels and processes. This dichotomy prevails in all present process calculi. The situation is in contrast to that withlambda calculus which h...From the very beginning process algebra introduced the dichotomy between channels and processes. This dichotomy prevails in all present process calculi. The situation is in contrast to that withlambda calculus which has only one class of entities-the lambda terms. We introduce in this papera process calculus called Lamp in which channels are process names. The language is more uniform than existing process calculi in two aspects: First it has a unified treatment of channels and processes.There is only one class of syntactical entities-processes. Second it has a unified presentation ofboth first order and higher order process calculi. The language is functional in the sense that lambda calculus is functional. Two bisimulation equivalences, barbed and closed bisimilarities, are proved to coincide.A natural translation from Pi calculus to Lamp is shown to preserve both operational and algebraic semantics. The relationship between lazy lambda calculus and Lamp is discussed.展开更多
基金This work was supported by the National Natural Science Foundation of China under grant number 61471055European Horizon 2020 INPUT project“In-Network Programmability for next-generation personal Cloud service support”,www.input-project.eu,under grant agreement number 644672.
文摘The combination of traditional processors and Field Programmable Gate Arrays(FPGA)is shaping the future networking platform for intensive computation in resource-constrained networks and devices.These networks present two key challenges of security and resource limitations.Lightweight ciphers are suitable to provide data security in such constrained environments.Implementing the lightweight PRESENT encryption algorithm in a reconfigurable platform(FPGAs)can offer secure communication service and flexibility.This paper presents hardware acceleration of security primitives in SDN using NETFPGA-10G.We implement an efficient design of the PRESENT algorithm for faster,smaller and lower power consumption hardware circuit using Verilog.We evaluate the performance of the hardware and software implementations of PRESENT.Experimental results prove that the proposed hardware design is a viable option for use in resource constrained devices in future networks and their applications.
基金Supported in part by the National Natural Science Foundation of China (1 0 0 71 0 2 1 ) the Foundationfor University Key Teacher by MEC and Shanghai Priority Academic Discipline Foundation
文摘Based on the method of symplectic geometry and variational calculation,the method for some PDEs to be ordered and analytically represented by Hamiltonian canonical system is discussed.Meanwhile some related necessary and sufficient conditions are obtained
文摘Dimensionality reduction （DR） methods based on sparse representation as one of the hottest research topics have achieved remarkable performance in many applications in recent years. However, it＇s a challenge for existing sparse representation based methods to solve nonlinear problem due to the limitations of seeking sparse representation of data in the original space. Motivated by kernel tricks, we proposed a new framework called empirical kernel sparse representation （EKSR） to solve nonlinear problem. In this framework, non- linear separable data are mapped into kernel space in which the nonlinear similarity can be captured, and then the data in kernel space is reconstructed by sparse representation to preserve the sparse structure, which is obtained by minimiz- ing a ~1 regularization-related objective function. EKSR pro- vides new insights into dimensionality reduction and extends two models： 1） empirical kernel sparsity preserving projec- tion （EKSPP）, which is a feature extraction method based on sparsity preserving projection （SPP）; 2） empirical kernel sparsity score （EKSS）, which is a feature selection method based on sparsity score （SS）. Both of the two methods can choose neighborhood automatically as the natural discrimi- native power of sparse representation. Compared with sev- eral existing approaches, the proposed framework can reduce computational complexity and be more convenient in prac- tice.
基金the National Natural Science Foundation of China ( Grant No. 69873032) ,863 Hi-Tech Project (863-306-ZT06-02-2) Excellent Young Scholar Fund, and was also supported by BASICS, Center of Basic Studies in Computing Science, sponsored by Shanghai Educa
文摘From the very beginning process algebra introduced the dichotomy between channels and processes. This dichotomy prevails in all present process calculi. The situation is in contrast to that withlambda calculus which has only one class of entities-the lambda terms. We introduce in this papera process calculus called Lamp in which channels are process names. The language is more uniform than existing process calculi in two aspects: First it has a unified treatment of channels and processes.There is only one class of syntactical entities-processes. Second it has a unified presentation ofboth first order and higher order process calculi. The language is functional in the sense that lambda calculus is functional. Two bisimulation equivalences, barbed and closed bisimilarities, are proved to coincide.A natural translation from Pi calculus to Lamp is shown to preserve both operational and algebraic semantics. The relationship between lazy lambda calculus and Lamp is discussed.
