摘要：
Cloud computing provides the scalable computation capability based on a virtualization technique. The energy conservation for green computing is one of the vital issues while allocating resources. To improve energy efficiency, the dynamic power-saving resource allocation (DPRA) mechanism based on a particle swarm optimization algorithm is proposed. The DPRA mechanism not only considers the energy consumption of physical machine (PM) and virtual machine (VM) but also newly tackles the energy efficiency ratio of air conditioner. Moreover, the least squares regression method is utilized to forecast PM's resource utilization for allocating VM and eliminating VM migrations. In simulation, the proposed DPRA mechanism is compared with three familiar allocation schemes and one previous solution. Simulation results show that in the presence of VM number, DPRA outperforms traditional schemes and previous solution in terms of total energy consumption (includes PMs and air conditioners), total electric bill, VM migration, and the number of shutdown PMs, chosen as objective performance metrics.
期刊：
Journal of Electronic Imaging,2018年27(2):023018 ISSN：1017-9909
通讯作者：
Sun, Kaiqiong
作者机构：
[Li, Yaqin; Sun, Kaiqiong; Zang, Shan] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan, Hubei, Peoples R China.;[Wang, Jun] China Shipbldg Ind Corp, Inst 722, Wuhan, Hubei, Peoples R China.
通讯机构：
[Sun, Kaiqiong] W;Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan, Hubei, Peoples R China.
关键词：
active contour model;level-set method;inhomogeneous image;local image information;difference image
摘要：
This paper proposes a hybrid active contour model for inhomogeneous image segmentation. The data term of the energy function in the active contour consists of a global region fitting term in a difference image and a local region fitting term in the original image. The difference image is obtained by subtracting the background from the original image. The background image is dynamically estimated from a linear filtered result of the original image on the basis of the varying curve locations during the active contour evolution process. As in existing local models, fitting the image to local region information makes the proposed model robust against an inhomogeneous background and maintains the accuracy of the segmentation result. Furthermore, fitting the difference image to the global region information makes the proposed model robust against the initial contour location, unlike existing local models. Experimental results show that the proposed model can obtain improved segmentation results compared with related methods in terms of both segmentation accuracy and initial contour sensitivity. (C) 2018 SPIE and IS&T
关键词：
Cloud computing;fog computing;industrial Internet of things (IIoT);secure data storage and retrieval
摘要：
With the fast development of industrial Internet of things (IIoT), a large amount of data is being generated continuously by different sources. Storing all the raw data in the IIoT devices locally is unwise considering that the end devices' energy and storage spaces are strictly limited. In addition, the devices are unreliable and vulnerable to many threats because the networks may be deployed in remote and unattended areas. In this paper, we discuss the emerging challenges in the aspects of data processing, secure data storage, efficient data retrieval and dynamic data collection in IIoT. Then, we design a flexible and economical framework to solve the problems above by integrating the fog computing and cloud computing. Based on the time latency requirements, the collected data are processed and stored by the edge server or the cloud server. Specifically, all the raw data are first preprocessed by the edge server and then the time-sensitive data (e.g., control information) are used and stored locally. The non-time-sensitive data (e.g., monitored data) are transmitted to the cloud server to support data retrieval and mining in the future. A series of experiments and simulation are conducted to evaluate the performance of our scheme. The results illustrate that the proposed framework can greatly improve the efficiency and security of data storage and retrieval in IIoT.
摘要：
Generalized bilinear model (GBM) has been one of the most representative models for nonlinear unmixing of hyperspectral image (HSI), which can take the second-order scattering of photons into consideration. However, the GBM is implicitly developed for the additive white Gaussian noise. Besides, the performances of traditional GBM based unmixing methods are not that satisfying since the spatial correlation of HSI is not considered. In this paper, to overcome the two problems mentioned above, we propose a robust GBM (RGBM) for nonlinear unmixing of HSI, which can simultaneously take the Gaussian noise and sparse noise into account. Besides, we propose a new unmixing method with superpixel segmentation (SS) and low-rank representation (LRR) based on RGBM, which can take the spatial correlation of HSI into consideration. First, we adopt the principal component analysis (PCA) to get the first principal component of HSI, which contains the most information for the whole HSI. Then we adopt the SS in the first principal component of HSI to get the homogeneous regions, and the abundances in each homogeneous region have the underlying low-rank property. Finally, we unmix the pixels in each homogeneous region of HSI according to the low-rank property of abundances and the sparse property of sparse noise, and the proposed RGBM based unmixing method can be solved by the alternative direction method of multipliers (ADMM). Experiments on both synthetic datasets and real HSIs demonstrate that the proposed RGBM and corresponding method are efficient compared with some other popular GBM based unmixing methods. (c) 2017 Elsevier B.V. All rights reserved.
关键词：
Software-defined networking (SDN);Load balance;Network planning;Internet of things
摘要：
Nowadays, with the rapid advance of network technology, the miniaturization of terminal equipment, and the trend of constant reduction of costs, the topic of IoT turns increasingly popular. As IoT becomes common in daily life, one can collect information at any time and in any environment, such as temperature, humidity, and PM2.5. Based on the analysis of such data, we can learn the degree of environmental comfort of a city, which is beneficial for the development of a smart city and other applications. However, the use of a large number of terminal equipment is likely to trigger huge demands of bandwidth, followed by the increase in the time of data transmission. In order to address this issue, this study proposed a service-oriented SDN-SFC load balance mechanism. It considered and classify the type and priority of service required by each terminal device. Then, it adopted the heuristic algorithm to plan the transmission paths among SFCs to reduce the load of each SF and improve the overall network performance. The simulation results indicate that the method proposed by this study can shorten the time of data transmission and achieve load balance.
期刊：
Modern Physics Letters B,2018年32(19):1850213 ISSN：0217-9849
通讯作者：
Zhang, Yong
作者机构：
[Zhao, Jie-Mei; Zhang, Yong] Wuhan Polytech Univ, Dept Math & Comp, Wuhan 430024, Hubei, Peoples R China.
通讯机构：
[Zhang, Yong] W;Wuhan Polytech Univ, Dept Math & Comp, Wuhan 430024, Hubei, Peoples R China.
关键词：
Traffic flow;car-following model;fractional order
摘要：
In order to depict the effect of driver’s memory on car-following behavior, a new kind of car-following model is proposed by using fractional order differential equation in this paper. Its dynamic equation is defined by Caputo fractional order derivative. And the order of derivative is the measurement of driver’s memory. In addition, discrete formulas of the position and velocity of the new model are given. The Optimal Velocity (OV) model is taken as an example to introduce how to get the fractional order car-following model from an ordinary model. The simulation results show that the Fractional Order Optimal Velocity (FOOV) model is more stable, and it can avoid unrealistic acceleration values of the OV model in the cases of starting and braking processes. Moreover, magnitudes of the speed and headway fluctuation of the FOOV model with a suitable order are smaller than those of the OV model. This indicates that the memory characteristic of drivers increases the stability of traffic flow.
期刊：
INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL,2018年13(4):574-589 ISSN：1841-9836
通讯作者：
Zhou, K.
作者机构：
[Zhou, K.; Wang, H. F.] Wuhan Polytech Univ, Dept Math & Comp, Wuhan 430023, Hubei, Peoples R China.;[Zhang, G. X.] Southwest Jiaotong Univ, Sch Elect Engn, Chengdu, Sichuan, Peoples R China.;[Zhang, G. X.] Xihua Univ, Robot Res Ctr, Chengdu, Sichuan, Peoples R China.
通讯机构：
[Zhou, K.] W;Wuhan Polytech Univ, Dept Math & Comp, Wuhan 430023, Hubei, Peoples R China.
关键词：
SN P systems;rules and weights on synapses;addition;multiplication;the greatest common divisor
摘要：
The application of spiking neural P systems with rules and weights on synapses to arithmetic operations is discussed in this paper. We design specific spiking neural P systems with rules and weights on synapses for successfully performing addition, multiplication and the greatest common divisor. This is the first attempt to discuss the application of the new variant of spiking neural P systems, spiking neural P systems with rules and weights on synapses, and especially the use of spiking neural P systems to perform the greatest common divisor. Comparing with the results reported in the literature, smaller number of neurons are required to fulfill the arithmetic operations.
期刊：
TRANSACTIONS OF THE AMERICAN MATHEMATICAL SOCIETY,2018年370(2):1321-1350 ISSN：0002-9947
通讯作者：
Deng, Guotai
作者机构：
[Deng, Guotai] Cent China Normal Univ, Sch Math & Stat, Wuhan 430079, Hubei, Peoples R China.;[Deng, Guotai] Cent China Normal Univ, Hubei Key Lab Math Sci, Wuhan 430079, Hubei, Peoples R China.;[Liu, Chuntai] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430023, Hubei, Peoples R China.;[Ngai, Sze-Man] Hunan Normal Univ, Coll Math & Comp Sci, Changsha 410081, Hunan, Peoples R China.;[Ngai, Sze-Man] Georgia Southern Univ, Dept Math Sci, Statesboro, GA 30460 USA.
通讯机构：
[Deng, Guotai] C;Cent China Normal Univ, Sch Math & Stat, Wuhan 430079, Hubei, Peoples R China.;Cent China Normal Univ, Hubei Key Lab Math Sci, Wuhan 430079, Hubei, Peoples R China.
期刊：
Journal of Mathematical Physics,2017年58(1):011503 ISSN：0022-2488
通讯作者：
Jin, Hai-Yang
作者机构：
[Fan, Lili] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430023, Peoples R China.;[Jin, Hai-Yang] South China Univ Technol, Sch Math, Guangzhou 510640, Guangdong, Peoples R China.
通讯机构：
[Jin, Hai-Yang] S;South China Univ Technol, Sch Math, Guangzhou 510640, Guangdong, Peoples R China.
关键词：
cell motility;diffusion;functions;initial value problems
摘要：
We study the quasilinear chemotaxis system (1.1) in a bounded domain Omega subset of R-n (n >= 3) with smooth boundary, where the diffusion function D(u) satisfies D(u) >= c(D)u(m-1) for all u > 0 with some c(D) > 0. Under the condition m > 3/2 - 1/n, we show that for all reasonably regular initial data, the corresponding initial-boundary value problem for (1.1) possesses global boundedness of solution, which converges to the spatially homogeneous equilibrium ((u) over bar (0),0) in an appropriate sense as t -> infinity, where (u) over bar (0) = 1/vertical bar Omega vertical bar integral(Omega) u(0). Published by AIP Publishing.
