Cross Point Assignment Algorithm Under Consideration of Very Long Nets

A cross point assignment algorithm is proposed under consideration of very long nets (LCPA).It is to consider not only the cost of connection between cross points and pins and the exclusive cost among cross points on the boundary of a global routing cell,but also the cost of displacement among cross points of the same net.The experiment results show that the quality and speed in the following detailed routing are improved obviously,especially for very long nets.

WiFi over Fiber Link and Wavelength Assignment Protocol for Internet of Things

A novel Wireless Fidelity (WiFi) over fiber link and a wavelength assignment protocol are proposed to provide sufficient bandwidth and extensive coverage range for the various applications in the Internet of Things (IoT).The performance of the WiFi over fiber-based wireless IoT network is evaluated in terms of error vector magnitude (EVM) and data throughput for both the up and down links between the WiFi central control system and remote radio units (RRUs).The experimental results illustrate the reliability of the fiber transmission of 64 Quadrature Amplitude Modulation (64QAM) WiFi signals by direct analog modulation.In order to efficiently utilize the wavelength resources,we also demonstrated the wavelength assignment protocol by employing optical switching configurations in Central Station (CS) to realize the wavelength switching,and the simulation results indicate the queuing size and the corresponding queue delay for different numbers of available wavelengths.

QoT-Aware Grooming, Routing, and Wavelength Assignment(GRWA) for Mixed-Line-Rate Translucent Optical Networks

A Mixed Line Rate(MLR)optical network is a good candidate for a core backbone network because of its ability to provide diverse line rates to effectively accommodate traffic demands with heterogeneous bandwidth requirements.Because of the deleterious effects of physical impairments,there is a maximum transmission reach for optical signals before they have to be regenerated.Being expensive devices,regenerators are expected to be sparsely located and used in such a network,called a translucent optical network.In this paper,we consider the Grooming,Routing,and Wavelength Assignment(GRWA)problem so that the Quality of Transmission(QoT)for connections is satisfied,and the network-level performance metric of blocking probability is minimized.Cross-layer heuristics to effectively allocate the sparse regenerators in MLR networks are developed,and extensive simulation results are presented to demonstrate their effectiveness.

Monitoring Soil Moisture under Wheat Growth through a Wireless Sensor Network in Dry Conditions

Drought research requires data on precipitation and actual soil moisture of fields because precipitation is variable among years and the soil textures differ with crop fields. Measurement of soil water content in the field is simple but labor-intensive. A prototype of an automatic field data monitoring system has been recently developed to collect data more efficiently. Using this system, data of soil water contents was successfully transmitted onto the personal computer approximately 700 m away from wheat field plots, for the period from March to May which was critical for soil drying and wheat growth. In addition, sample data of soil water content and grain yield was obtained from field plots of three bread wheat genotypes.

Seismic-inversion method for nonlinear mapping multilevel well–seismic matching based on bidirectional long short-term memory networks

In this paper,the recurrent neural network structure of a bidirectional long shortterm memory network(Bi-LSTM)with special memory cells that store information is used to characterize the deep features of the variation pattern between logging and seismic data.A mapping relationship model between high-frequency logging data and low-frequency seismic data is established via nonlinear mapping.The seismic waveform is infinitely approximated using the logging curve in the low-frequency band to obtain a nonlinear mapping model of this scale,which then stepwise approach the logging curve in the high-frequency band.Finally,a seismic-inversion method of nonlinear mapping multilevel well–seismic matching based on the Bi-LSTM network is developed.The characteristic of this method is that by applying the multilevel well–seismic matching process,the seismic data are stepwise matched to the scale range that is consistent with the logging curve.Further,the matching operator at each level can be stably obtained to effectively overcome the problems that occur in the well–seismic matching process,such as the inconsistency in the scale of two types of data,accuracy in extracting the seismic wavelet of the well-side seismic traces,and multiplicity of solutions.Model test and practical application demonstrate that this method improves the vertical resolution of inversion results,and at the same time,the boundary and the lateral characteristics of the sand body are well maintained to improve the accuracy of thin-layer sand body prediction and achieve an improved practical application effect.