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Nature Inspired Algorithms in Cloud Computing: A Survey
Gamal Abd El-Nasser A. Said
Issue:
Volume 5, Issue 5, October 2016
Pages:
60-64
Received:
5 September 2016
Accepted:
23 September 2016
Published:
11 October 2016
Abstract: Cloud Computing consists of many resources, the problem of mapping tasks on unlimited computing resources in cloud computing is NP-hard optimization problem. In this paper, we provide a survey of popular nature inspired algorithms: Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) for solving NP-hard problems in cloud computing.
Abstract: Cloud Computing consists of many resources, the problem of mapping tasks on unlimited computing resources in cloud computing is NP-hard optimization problem. In this paper, we provide a survey of popular nature inspired algorithms: Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) for solving NP-hard probl...
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Tracking Algorithm Based on Channel Propagating Characteristic in Wireless Sensor Network
Ying Li,
Yiliang Wu,
Nina Hu,
Guangsong Yang
Issue:
Volume 5, Issue 5, October 2016
Pages:
65-70
Received:
16 October 2016
Published:
17 October 2016
Abstract: In order to improve the mobile node tracking accuracy of indoor environment, a mobile node tracking algorithm based on channel propagating characteristic is proposed. Channel propagation model is established by actual measurement and fitting analysis in three different scenarios, which included closed corridor, open corridor and laboratory. The anchor node periodically measures the RSSI of the beacons from mobile node, to estimate the coordinates of the mobile node location, speed and direction by using the Maximum Likelihood method and channel model. The simulation results prove that the proposed scheme is effective and can meet the real-time requirements of indoor localization.
Abstract: In order to improve the mobile node tracking accuracy of indoor environment, a mobile node tracking algorithm based on channel propagating characteristic is proposed. Channel propagation model is established by actual measurement and fitting analysis in three different scenarios, which included closed corridor, open corridor and laboratory. The anc...
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Phase Matching Denoising Algorithm and IP Design
Wu Peng,
Xia Hui,
Wang Chen
Issue:
Volume 5, Issue 5, October 2016
Pages:
71-74
Received:
16 October 2016
Published:
17 October 2016
Abstract: At present, there are many kinds of denoising algorithms, but the hardware of these algorithms IP design is very lacked. In this paper, a phase matching denoising algorithm is proposed to remove the noise, and the IP design of this method is realized. Phase matching denoising algorithm is based on the signal phase matching method to obtain the actual signal and remove noise. Mathematical expression and mathematical proof of the method are given here. Using this method, the IP kernel design is given and the design method is given. Through the function simulation, it is proved that the IP kernel design can effectively remove the noise in the signal.
Abstract: At present, there are many kinds of denoising algorithms, but the hardware of these algorithms IP design is very lacked. In this paper, a phase matching denoising algorithm is proposed to remove the noise, and the IP design of this method is realized. Phase matching denoising algorithm is based on the signal phase matching method to obtain the actu...
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An Evolutionary Method of Neural Network in System Identification
Shuming T. Wang,
Chi-Yen Shen,
Yu-Ju Chen,
Chuo-Yean Chang,
Rey-Chue Hwang
Issue:
Volume 5, Issue 5, October 2016
Pages:
75-81
Received:
20 October 2016
Published:
20 October 2016
Abstract: This paper presents an evolutionary method for calculating the important degree (ID) of individual input variable of well-trained neural network (NN). The importance of each input variable of neural network could be distinguished in accordance with ID value obtained. In this research, several linear and nonlinear systems’ identifications were firstly studied and simulated. From the simulation results shown, the evolutionary method proposed is quite promising and accurate for the estimation of system’s parameters. In other worlds, the method proposed could be used for data mining in the real applications. In order to verify our inference view, the evaporation process of thin film was studied either. It is a real case of industrial application. Again, the studied results show that the method proposed indeed has the superiority and potential in the area of data mining.
Abstract: This paper presents an evolutionary method for calculating the important degree (ID) of individual input variable of well-trained neural network (NN). The importance of each input variable of neural network could be distinguished in accordance with ID value obtained. In this research, several linear and nonlinear systems’ identifications were first...
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