Research on fault repair method of all-optical network based on SDN

Zhao, Zhenmin; Wang, Huiqiang; Wang, Jian; Guo, Hong-Wei

doi:10.23919/jcc.2020.06.015

Cited by 3 publications

(5 citation statements)

References 14 publications

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“…Assuming that all nodes are deployed in a cloud data center and connect all nodes to be able to carry service functions, the physical node resources and the remaining resource capacity of the link bandwidth obey the random distribution of [1000, 1500]; the unit mapping cost of link and node is both 1. Each SFC request consists of different types of service functions, its quantity obeys the random distribution of [2,5], the resource demand of each SFC node and link obeys the uniform distribution of [0.5, 1], the number of service types supported by the underlying network is set to 10, and each node randomly provides 1 to 5 of them [15].…”

Section: Experimental Evaluation and Analysismentioning

confidence: 99%

“…The emergence of edge computing and end-to-end (Device-to-Device, D2D) communication technologies, for the rapid deployment of perception tasks, perceives the transmission and processing of data and provides a new opportunity. With the help of edge computing, not only can the rapid processing of sensory data be realized at the edge of the network; it can also reduce the occupation of backbone network resources [2]. Therefore, in order to achieve large-scale, high-efficiency, and low-cost mobile group intelligence perception, how to organically integrate edge devices and end devices has become one of the important tasks in the research of mobile group intelligence perception.…”

Section: Introductionmentioning

confidence: 99%

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Optimization Distribution Method of Computer Sensor Network Communication Based on the Linear Planning Model

et al. 2022

Journal of Sensors

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In order to explore the optimal allocation method of computer network communication, a linear programming model is proposed. Based on the overall structure of service chain deployment, the integer linear programming model is introduced to make mathematical modeling, so that network resources and load balancing can be effectively utilized under resource and delay constraints. Simulation results showed that in the experiment, 10 to 100 SFC request intensities were generated, respectively, calculating the request acceptance rates of the three deployment algorithms. Under the same conditions, the average request acceptance rate based on the G-kSP algorithm is about 95.4% and about 92.3%, and the greedy deployment algorithm is about 81.7%. We show that the optimized distribution method of computer sensor network communication based on a linear programming model reduces the load balance and time complexity while reducing the request acceptance rate.

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Section: Experimental Evaluation and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimization Distribution Method of Computer Sensor Network Communication Based on the Linear Planning Model

et al. 2022

Journal of Sensors

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“…The data collected by sensor nodes can be described as a matrix structure, as shown in formula (1). where the row vector represents a single parameter to sample the dataset over the time series.…”

Section: Dynamicmentioning

confidence: 99%

“…However, performing linear regression on the entire time series will produce relatively large errors, mainly due to: (1) The correlation degree of parameters in different time periods is different. For example, the rate of change of ambient temperature is small in the noon time of the day, while the rate of change is large in the evening.…”

Section:  mentioning

confidence: 99%

“…With the increasing maturity of wireless communication, integrated circuit, sensor and micro electro mechanical system (MEMS), it is possible to produce micro wireless sensors with low cost, low power consumption and multi-function. These sensor nodes integrate functional components such as information sensing, data processing and wireless communication [1]. WSN is a wireless self-adjusting network composed of multiple miniature smart sensor nodes sent to the monitoring area.Its purpose is to monitor, perceive and collect the data of various environments or monitoring objects in the geographical area covered by the network in real time, process these data, obtain detailed and accurate information and transmit them to users who need these information.…”

Section: Introductionmentioning

confidence: 99%

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Label big data compression in Internet of things based on piecewise linear regression

Zhang

Zhao

et al. 2022

Applied Mathematics and Nonlinear Sciences

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In order to solve the key problem that most of the energy of wireless sensor network nodes is consumed in wireless data modulation, which is an extremely important and limited resource. The energy efficiency evaluation scheme of data compression algorithm based on the separation of hardware factor and algorithm factor is proposed; In order to improve the running efficiency of the compression algorithm and reduce the energy consumption of the algorithm itself, a program level energy-saving optimization method for the data compression algorithm is proposed; In order to keep the energy-saving benefits of the data compression algorithm when the wireless transmission power is adjusted, an adjustment mechanism of the compression algorithm which can adapt to the change of transmission power is proposed. The experiment shows that when the wireless transmission power is - 7dBm and below (k < 178.4), the data should be compressed by S-LZW algorithm, and when the wireless transmission power is - 5dBm and above (k > 178.4), the b ~ RLE algorithm should be used for compression. The validity of the method is verified.

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Research on analogue of electromagnetically induced transparency effect based on asymmetric structure all-dielectric metamaterial

Zhang¹,

Cheng²,

Zhang³

et al. 2021

Acta Phys. Sin.

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The electromagnetically induced transparency (EIT), which is a result of destructive interference between different excitation paths in a three-energy-level atomic medium, makes opaque probe light transparent over a range of frequencies. As this EIT effect is usually accompanied with strong dispersion, it has potential applications such as slow light propagation, optical buffering, nonlinear optics, optical sensing, etc. However, for conventional quantum EIT effect which requires stable gas lasers and low temperature environment, the implementation of EIT in chip-scale applications is severely hampered by the scathing experimental requirements. Recently, the EIT-like effect in metamaterials, which are constructed by designing the artificial subwavelength functional elements and arranging the spatial sequences, attracts tremendous attention because of its advantages, such as room temperature manipulability, large bandwidth, and small sizes. In addition, the high-quality factor(Q) value obtained by EIT-like effect has great significance in designing the metamaterial-based devices. In this paper, we design an EIT-like metamaterial with such a structure. The unit cell of the proposed metamaterial is constructed by two asymmetric silicon blocks embedded on a silicon dioxide substrate. Meanwhile, we analyze its optical properties and EIT-like effects by using three-dimension (3D) FDTD method. Based on the coupled Lorentz model, the EIT-like effect of the designed metamaterial is investigated. Then, by employing the electric field distribution on the surface of the metamaterial, and combining with the three-level atomic system, the mechanism of the EIT-like effect is analyzed in detail. We find that the EIT-like effect in the proposed metamaterial has high Q value (Q ≈ 8616) and the high transmission (T = 96%). By changing the length of the silicon block to destroy the asymmetry of the metamaterial structure, an active tuning EIT-like effect is realized. Furthermore, the metamaterial structure has the advantages of low loss, easy preparation, and active-controllability. This study represents an innovative approach to designing the EIT-like metamaterial, which is expected to be useful for designing active tunable slow-light devices and highly sensitive optical sensors.

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Research on fault repair method of all-optical network based on SDN

Cited by 3 publications

References 14 publications

Optimization Distribution Method of Computer Sensor Network Communication Based on the Linear Planning Model

Optimization Distribution Method of Computer Sensor Network Communication Based on the Linear Planning Model

Label big data compression in Internet of things based on piecewise linear regression

Research on analogue of electromagnetically induced transparency effect based on asymmetric structure all-dielectric metamaterial

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