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This paper presents the relatively complete theory for the two new numerical algorithms, i.e., E47 algorithm and 94LVI algorithm, for solving the quadratic program (QP) subject to inequality and bound constraints efficiently. Specifically, via the important “Bridge” theorems and with their proofs provided, the QP problem is converted equivalently into a piecewise-linear projection equation (PLPE)...
Fast detection of performance anomalies is critical in Cloud applications, but challenging to implement in a general and effective tool with low operational overload. We propose FSAD, a performance anomaly detection system based on the concept of flow similarity. It stems from the observation that, in general, the number of responses generated by a component closely follows the number of received...
In this paper, a special method called Zhang neuronet (ZN) is proposed and investigated for online solution of complex-valued time-varying linear inequalities (CVTVLI). Instead of employing a norm-based energy function in traditional gradient neuronet (GN) and related methods, the given ZN model is designed using a vector-valued error function and takes advantage of the first-order time-derivative...
Many complex application services are deployed in virtualized Cloud environments. Cloud applications consist of multiple components and the data flow among these components tends to be highly complex and unpredictable. The complexity and heterogeneity make anomaly detection challenging. We propose FlowBox, a distributed anomaly detection system for Cloud applications. FlowBox considers each server...
This paper presents and investigates two new numerical algorithms (i.e., E47 algorithm and 94LVI algorithm) for solving the quadratic programming (QP) problem subject to inequality and bound constraints. Such a constrained QP problem is firstly converted equivalently into a linear variational inequality (LVI), and then converted equivalently into a piecewise-linear projection equation (PLPE). The...
Power management has been increasingly critical for sustainable data centers. One particular aspect that has a strong impact on the power consumed by a data center is how the workload is distributed among its servers. This distribution can be done integrating thermal models that allow balancing cooling needs with computing needs contributing to reduce overall power consumption. In this paper, we present...
Two quadratic programming (QP) based schemes aided with weighting matrices and error feedback, namely the feedback-type minimum-weighted-velocity-norm (FTMWVN) scheme and its acceleration-level scheme, are proposed in this paper for solving the redundancy-resolution (or say, inverse-kinematics) problem. Then, the equivalence between the velocity-level FTMWVN scheme and the acceleration-level scheme...
After widely investigating the velocity-level redundancy resolution schemes for redundant robot manipulators, we focus one of our research directions on the relationship between different-level schemes, e.g., between position-level and velocitylevel redundancy-resolution schemes. In this paper, we propose a novel viewpoint; that is, there exists an equivalence between some position-level and velocity-level...
By following Zhang et al.'s design method, a special class of recurrent neural network termed Zhang neural network (ZNN) has been proposed for online solution of time-varying linear inequalities. For the purpose of digital-hardware implementation, the resultant ZNN model is discretized by employing Euler difference rule in this paper. Thus, three discrete-time ZNN models and numerical algorithms (i...
Since March 2001, a special class of recurrent neural network termed Zhang neural network (ZNN) has been proposed by Zhang et al for time-varying matrix inversion. For the purpose of possible hardware implementation, the resultant ZNN model is discretized by employing Euler forward-difference rule. In this paper, three discrete-time ZNN models using nonlinear activation functions (e.g., power-sigmoid...
Based on the theory of polynomial-interpolation and curve-fitting, a new multiple-input feed-forward neural network activated by Hermit orthogonal polynomials is proposed and investigated. Besides, the design makes the multiple-input Hermit orthogonal polynomials neural network (MIHOPNN) have no weakness of dimension explosion. To determine the optimal weights of the MIHOPNN, the weight direct determination...
In this paper, a numerical method (termed, E47 algorithm) based on linear variational inequalities (LVI) is presented and investigated to solve quadratic programming (QP) problems which are simultaneously subject to linear equality, inequality and bound constraints. Note that such constrained QP problems can be equivalent to linear variational inequalities and then to piecewise-linear projection equations...
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