In this paper the handover procedure in LTE based femtocells is discussed which poses to be one of the major issues as the number of femtocells increases in the urban environment. The concept of proactive and reactive...
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ISBN:
(纸本)9781479906987
In this paper the handover procedure in LTE based femtocells is discussed which poses to be one of the major issues as the number of femtocells increases in the urban environment. The concept of proactive and reactive handovers is discussed and a comparison is carried out between the two using simulations. An optimization algorithm is proposed to prevent too frequent handovers and to minimize the probability of dropped calls. Simulations for the macro-femto and inter-femto handovers have been performed and the comparison is done between the conventional handover procedure and the proposed algorithm.
with the monitoring rang expanded increaingly, the topology of the network environmental monitoring system needs to be developed from the single-layer structure to the multi-layer structure, which branch node function...
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ISBN:
(纸本)9780769550169
with the monitoring rang expanded increaingly, the topology of the network environmental monitoring system needs to be developed from the single-layer structure to the multi-layer structure, which branch node function setting and optimization problems are very important. The structure of the overlay network currently being used in the environmental monitoring system is complex, and its communication modes vary, there are also differences in reliability and accuracy. Only proper management can avoid sending the wrong message, improving the overall environmental monitoring system performance. When the monitoring node reaches a certain magnitude, we can assume that all nodes are the same in statistical sense. Bayesian Network probabilistic graphical models generated by the algorithm can fast correct the data as a whole. The simulation data show that the task of collation of data and uncertain data discrimination given to the branch node in accordance with the Bayesian network model algorithm, can effectively improve system reliability and validity.
Virtualization technology, being the most effective solution to the resource management of cloud computing, excels in it is virtual machine real-time migration technology. One key issue of live migration of virtual ma...
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ISBN:
(纸本)9781479939251
Virtualization technology, being the most effective solution to the resource management of cloud computing, excels in it is virtual machine real-time migration technology. One key issue of live migration of virtual machine is how to quickly and transparently migrate virtual machines to meet Service Level Agreements (SLAs). In this paper an improved time-series based precopy approach technique is proposed. With the time-series prediction technique, frequently updated dirty pages (high dirty pages) are identified more precisely, and transmit them in the last round of iteration, in order to reduce unnecessary, repeated transmission of dirty pages. Doing so can significantly reduce the total migration time.
In this paper we consider the l(1)-compressive sensing problem. We propose an algorithm specifically designed to take advantage of shared memory, vectorized, parallel and many-core microprocessors such as the Cell pro...
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In this paper we consider the l(1)-compressive sensing problem. We propose an algorithm specifically designed to take advantage of shared memory, vectorized, parallel and many-core microprocessors such as the Cell processor, new generation Graphics Processing Units (GPUs) and standard vectorized multi-core processors (e. g. quad-core CPUs). Besides its implementation is easy. We also give evidence of the efficiency of our approach and compare the algorithm on the three platforms, thus exhibiting pros and cons for each of them.
The investigation of motion guidance and its subsequent application using tau (tau) theory relies on the accurate calculation of the coupling term between the tau (time to contact) of the motion and the appropriate ta...
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The investigation of motion guidance and its subsequent application using tau (tau) theory relies on the accurate calculation of the coupling term between the tau (time to contact) of the motion and the appropriate tau guide. However, the traditional approach for this calculation can be numerically unstable, requires experience and skill to execute in a meaningful manner, is sensitive to the data selected, and has limited application when the motion information is incomplete or deviates from the ideal. To deal with these issues, a new approach, based on positive wavelet analysis, is proposed in this paper. The mother wavelet is constructed using the desired tau-guide shapes, with its scale considered to be defined by the maneuver period. The scale and time information of interest are found by searching for the best local correlation within the whitened original signal. An inverse dewhitening process is then used to reconstruct an approximation to the original motion signal. The adequacy of the positive wavelet method has been demonstrated using data obtained from piloted simulation test campaigns. The results show that the approach is not only feasible, but it has better numerical stability, reliability, enhanced performance, and wider applicability than those that have been used to date.
Structural optimization for crashworthiness criteria is of particular significance especially at early stage of design. The comparative study of Kriging and radial basis function network （RBFN） was performed in orde...
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Structural optimization for crashworthiness criteria is of particular significance especially at early stage of design. The comparative study of Kriging and radial basis function network （RBFN） was performed in order to improve the crashworthiness effects of honeycomb. Improving the crashworthiness characteristic of honeycomb was achieved using LS-OPT~ and domain reduction strategy. This optimization is performed on the basis of validated numerical simulation to establish the approximated model to illustrate the relationship between the responses and design variables. The results showed that Kriging meta-model is excelled in accuracy, robustness and efficiency compared to radial basis function （RBF） and crashworthiness characteristic of honeycomb is improved by 4%.
In a hot strip mill, the strip is cooled by spraying water from the top and bottom on the runout table (ROT) before the strip is coiled. The desired mechanical properties and metallurgical structure of the strip are a...
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In a hot strip mill, the strip is cooled by spraying water from the top and bottom on the runout table (ROT) before the strip is coiled. The desired mechanical properties and metallurgical structure of the strip are achieved by controlling the cooling rate and temperature of the strip on the ROT. In this paper, we propose a design method of receding horizon control for controlling the temperature of a strip whose mathematical model is described by a nonlinear partial differential equation (PDE). We provide a fast numerical solution method for solving the nonlinear optimization problem for a class of nonlinear PDEs. Moreover, a state observer with an unscented Kalman filter for estimating the inhomogeneously distributed temperature of the strip is incorporated into the receding horizon controller. The effectiveness of the proposed method is verified by numerical simulation.
In the traditional data-driven data mining process, there are huge gaps between the efficient algorithms and intelligent tools as well as the invalidity of knowledge which is obtained by traditional data-driven data m...
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In the traditional data-driven data mining process, there are huge gaps between the efficient algorithms and intelligent tools as well as the invalidity of knowledge which is obtained by traditional data-driven data mining. Meanwhile, each data in the earth science field contains a solid physical meaning. If there is no corresponding domain knowledge involved in the mining process, the information explored by data-driven data mining will be lack of practicability and not able to effectively solve problems in the earth science area. Therefore, the task-driven data mining is proposed. Additionally, task-driven data mining concepts and principles are elaborated with the help of data mining concepts and techniques. It is divided into seven elements such as data warehousing, data preprocessing, feature subset selection, modeling, model evaluation, model updating and model release. Those constitute a cyclic and iterative process until a predictive model which is capable of effectively achieving the objectives. In order to accurately identify complex lithologies, this paper puts forward a self-organizing feature map neural network based on the task-driven data mining. With the attempt to solve the problem of complex reservoir identification, the decision tree and support vector machine are used to build the fluid predictive model. Meanwhile, the optimization algorithms inclusive of genetic, grid and quadratic are adopted to optimize the important parameters of C-SVC and upsilon-SVC, such as C, upsilon and gamma, so as to improve the classification performance and generalization ability of the predictive model of support vector machine. The conclusions of fine interpretation are compared with the core analysis data and well testing data. As a result, the accuracy of the complex lithology and reservoir identification is more than 90%. Finally, the paper puts forward the understandings, development prospects and key challenges of task-driven data mining facing. (C) 2013 Elsev
For solving Ins-Lambda-CSP (reoptimization of Lambda-CSP under insertion of one constraint) there exists an optimal approximation algorithm with additive error of constant complexity. Approximation ratio of this algor...
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For solving Ins-Lambda-CSP (reoptimization of Lambda-CSP under insertion of one constraint) there exists an optimal approximation algorithm with additive error of constant complexity. Approximation ratio of this algorithm depends on the integrality gap of LP relaxation of the initial problem.
A recently proposed nonlinear antiwindup compensation scheme is implemented and tested on a 1/16 scaled BAe Hawk jet trainer wind-tunnel model, mounted in a one degree of freedom configuration. The Hawk is modeled as ...
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A recently proposed nonlinear antiwindup compensation scheme is implemented and tested on a 1/16 scaled BAe Hawk jet trainer wind-tunnel model, mounted in a one degree of freedom configuration. The Hawk is modeled as a nonlinear affine system subject to input amplitude constraints. The primary control system consists of an inner-loop nonlinear dynamic inversion controller and an outer-loop linear proportional integral derivative controller. The input constraints are addressed by supplementing this nominal controller with two types of nonlinear antiwindup schemes: a nonlinear variant of the well-known internal model, control scheme and a suboptimal L-2 norm-based antiwindup compensator. Wind tunnel results are presented which demonstrate the usefulness of the antiwindup schemes in preventing performance deterioration due to the input constraints and the flexibility of the proposed approach from a practical perspective.
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