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The Network Function Placement (NFP) problem involves placing Virtual Network Functions (VNFs) in a network in order to meet the Service Function Chain (SFC) requirements of the flows through the network. Simultaneously, the usage of network resources by the VNF instances must be optimized. Prior work primarily treated this as a constraint satisfaction problem, using linear programming to find optimal...
Dual methods can handle easily complicated constraints in convex problems, but they have typically slow (sublinear) convergence rate in an average primal point, even when the original problem has smooth strongly convex objective function. Primal projected gradient-based methods achieve linear convergence for constrained, smooth and strongly convex optimization, but it is difficult to implement them,...
TCP LoLa is a new delay-based congestion control that supports both, low queuing delay and high network utilization in high speed wide-area networks. This is particularly useful for traffic mixes consisting of bandwidth demanding and delay sensitive flows (e.g., long file transfer and interactive "web 2.0" traffic). TCP LoLa keeps the queuing delay at the bottleneck link low around a fixed...
We show that high dimensional expanders imply derandomized direct product tests, with a number of subsets that is linear in the size of the universe.Direct product tests belong to a family of tests called agreement tests that are important components in PCP constructions and include, for example, low degree tests such as line vs. line and plane vs. plane.For a generic hypergraph, we introduce the...
Diffraction of the H — polarized electromagnetic wave by semi-infinite knife-type grating which consists of material strips is considered. The operator method is used for solution. As a result nonlinear operator equation relatively unknown reflection operator is obtained. The convergence of solution of nonlinear operator equation for the gratings of perfectly electric conductor strips and material...
In this paper sliding mode controller is designed in comparison with the linear state space feedback controllers namely the pole placement controller and linear quadratic regulator to eliminate the chaotic limit cycle oscillations in Van der Pol system induced by an external sinusoidal excitation in order to avoid failure in physical structures. The controller design is based on the mathematical model...
Quantum-behaved particle swarm optimization (QPSO) is a novel variant of particle swarm optimization (PSO), inspired by quantum mechanics. Compared with traditional PSO, the QPSO algorithm guarantees global convergence and has less number of controlling parameters. However, QPSO is likely to get trapped into a local optimum because of using a single search strategy. This paper proposes a cooperative...
The bare bones particle swarm optimization (BBPSO) is a population-based algorithm. The BBPSO is famous for easy coding and fast applying. A Gaussian distribution is used to control the behavior of the particles. However, every particle learning from a same particle may cause the premature convergence. To solve this problem, a new hierarchical bare bones particle swarm optimization algorithm is proposed...
This paper focuses on solving the ship course tracking problem by using Zhang dynamics (ZD) method and a new Zhang finite difference (ZFD) formula. Via ZD method, which is a powerful class of dynamics to solve online time-varying problems, the so called ZD controller of ship course tracking is designed. Then, a 1-node-ahead differentiation formula within ZFD framework termed as 4-node g-square finite...
The dynamic characteristics of a hydraulic turbine governing system is determined by the parameters of the hydraulic turbine governor. There are several drawbacks of the conventional particle swarm algorithm in parameter optimization, such as low speed of convergence, low accuracy and being inclined to result in partial optimization during the process of optimization. This paper introduced concave...
Wavelet neural network has a slow convergence rate, weak global search capability and easy to search the search results to a minimum, while the genetic algorithm has a high degree of parallelism, randomness, adaptive search and global optimization. The wavelet neural network is transformed and transformed to obtain the discretized wavelet neural network. In this paper, the three-layer wavelet neural...
Metro-scale TDM-DWDM PONs can enable consolidation of network resources and the convergence of multiple service types on the same infrastructure. Two different SDN enabled metro-scale PON configurations are reported, for densely and sparsely populated areas, supporting 10G PON channels, wireless fronthaul and 100G enterprise services.
Fuzzy logic systems have been extensively applied for solving many real world application problems because they are found to be universal approximators and many methods, particularly, gradient descent (GD) methods have been widely adopted for the optimization of fuzzy membership functions. Despite its popularity, GD still suffers some drawbacks in terms of its slow learning and convergence. In this...
Least-squares temporal difference learning (LSTD) has been used mainly for improving the data efficiency of the critic in actor-critic (AC). However, convergence analysis of the resulted algorithms is difficult when policy is changing. In this paper, a new AC method is proposed based on LSTD under discount criterion. The method comprises two components as the contribution: (1) LSTD works in an on-policy...
In this paper, we consider the privacy preserving problem in an agreement network under interception attacks. First, we introduce a consensus protocol with privacy preserving, where each node hides their initial states into a set of random sequences, and then injects the sequences into the process of consensus. Second, we assume that an attacker with limited power can intercept the data transmitted...
This paper addresses a terminal sliding mode strategy to control the attitude of quadrotor while achieving the finite time convergence. To deal with system uncertainty and time-varying disturbance, a hybrid controller using single-hidden layer feedforward network (SLFN) and disturbance observer (DOB) is proposed. Fast terminal sliding mode surface is designed to construct the sliding mode control...
In this paper, we address the finite-time tracking consensus control problem for nonlinear multi-agent systems under no-cycle communication graph. Unlike most existing works of finite-time consensus, we focus on nonlinear multi-agent systems with lower triangular subsystems. Based on the local cooperative information among neighboring agents, we propose a tracking consensus protocol ensuring that...
This paper presents a generalized iterative learning control (ILC) design in the frequency domain with experimental validation. The optimal ILC learning function and robustness filter function are simultaneously optimized by solving a linear programming problem using frequency response functions. Moreover, the design realizes an optimal trade-off between robust convergence, converged tracking performance,...
This paper addresses the problem of speech quality enhancement and acoustic noise reduction by adaptive filtering algorithms. In this paper, we propose a new version of the set-membership partial-update normalized least mean square (SM-PU-NLMS) algorithm. The proposed algorithm is based on the use of the cross-correlation of the output error signal and the noisy to control the variable-step-size in...
These article shows efficiency of Problem-Based Learning (PBL) in academic performance of course “Physics I”, specifically in how learning arises across experience. For this, existing methodologies were adapted in PBL in order to generate six methodological proposals, developed during an academic semester. Impact of PBL was evident at end of semester. It was validated through non-parametric test from...
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