适应新常态人才需求的《网络编程》课程的教学改革研究

面对中国经济进入换挡降速、结构优化、提质增效的新常态,高校如何才能适应并为创新驱动发展战略的实施提供人才储备,成为当前需要研究和解决的问题。针对新常态的需求和我校的培养应用型人才的培养目标,提出了对《网络编程》课程进行了相对应的改革,本次改革从课程的教学过程到考核方式均提出了行之有效的方案。

Synthesis of indirect work exchange networks considering both isothermal and adiabatic process together with exergy analysis

In this paper, an efficient methodology for synthesizing the indirect work exchange networks(WEN) considering isothermal process and adiabatic process respectively based on transshipment model is first proposed. In contrast with superstructure method, the transshipment model is easier to obtain the minimum utility consumption taken as the objective function and more convenient for us to attain the optimal network configuration for further minimizing the number of units. Different from division of temperature intervals in heat exchange networks,different pressure intervals are gained according to the maximum compression/expansion ratio in consideration of operating principles of indirect work exchangers and the characteristics of no pressure constraints for stream matches. The presented approach for WEN synthesis is a linear programming model applied to the isothermal process, but for indirect work exchange networks with adiabatic process, a nonlinear programming model needs establishing. Additionally, temperatures should be regarded as decision variables limited to the range between inlet and outlet temperatures in each sub-network. The constructed transshipment model can be solved first to get the minimum utility consumption and further to determine the minimum number of units by merging the adjacent pressure intervals on the basis of the proposed merging methods, which is proved to be effective through exergy analysis at the level of units structures. Finally, two cases are calculated to confirm it is dramatically feasible and effective that the optimal WEN configuration can be gained by the proposed method.

Towards Wide-Open, Adaptable DCF Implementation for Dynamic Networks

Abstract： This work proposes a Field Programmable Gate Array （FPGA）-oriented architecture for the IEEE 802.11 Distributed Coordination Function （DCF） transceiver. We describe the functional blocks carrying out the Carrier Sense Multiple Accesses with Collision Avoidance （CSMA/CA）, develop the interfaces to the application layer and the physical layer, and implement it on FPGA devices by utilizing Very-high-speed-integrated-circuit Hardware Description Language （VHDL）.

SWN: An SDN Based Framework for Carrier Grade WiFi Networks

With the rapid growth of mobile data traffic and vast traffic offloaded from cellular network, Wi-Fi has been considered as an essential component to cope with the tremendous growth of mobile data traffic. Although operators have deployed a lot of carrier grade Wi-Fi networks, but there are still a multitude of arrears for nowadays Wi-Fi networks, such as supporting seamless handover between APs, automatic network access and unified authentication, etc. In this paper, we propose an SDN based carrier grade Wi-Fi network framework, namely SWN. The key conceptual contribution of SWN is a principled refactoring of Wi-Fi networks into control and data planes. The control plane has a centralized global view of the whole network, can perceive the underlying network state by network situation awareness(NAS) technique, and bundles the perceived information and network management operations into northbound Application Programming Interface(API) for upper applications. In the data plane, we construct software access point(SAP) to abstract the connection between user equipment(UE) and access point(AP). Network operators can design network applications by utilizing these APIs and the SAP abstraction to configure and manage the whole network, which makes carrier grade Wi-Fi networks more flexible, user-friendly, and scalable.

Novel multipath routing protocol integrated with forward error correction in MANET

In order to improve the data transmission reliability of mobile ad hoc network, a routing scheme called integrated forward error correction multipath routing protocol was proposed, which integrates the techniques of packet fragmenting and forward error correction encoding into multipath routing. The scheme works as follows: adding a certain redundancy into the original packets; fragmenting the resulting packets into exclusive blocks of the same size; encoding with the forward error correction technique, and then sending them to the destination node. When the receiving end receives a certain amount of information blocks, the original information will be recovered even with partial loss. The performance of the scheme was evaluated using OPNET modeler. The experimental results show that with the method the average transmission delay is decreased by 20% and the transmission reliability is increased by 30%.

PLC-Oriented Access Point Location Planning Algorithm in Smart-Grid Communication Networks

In this study, we investigate the optimal location of access points （APs） to connect end nodes with a service provider through power-line communication in smartgrid communication networks. APs are the gateways of power-distribution communication networks, connecting users to control centers. Hence, they are vital for the reliable, safe, and economical operation of a power system. This paper proposes a planning method for AP allocation that takes into consideration economics, reliability, network delay, and （n-l） resilience. First, an optimization model for the AP location is established, which minimizes the cost of installing APs, while satisfying the reliability, network delay, and （n-1） resilience constraints. Then, an improved genetic algorithm is proposed to solve the optimization problem. The simulation results indicate that the proposed planning method can deal with diverse network conditions satisfactorily. Furthermore, it can be applied effectively with high flexibility and scalability.

Energy and Water Optimization in Biofuel Plants

In this paper we address the topic of energy and water optimization in the production of bioethanol from corn and switchgrass. We show that in order for these manufacturing processes to be attractive,there is a need to go beyond traditional heat integration and water recycling techniques. Thus,we propose a strategy based on mathe-matical programming techniques to model and optimize the structure of the processes,and perform heat integration including the use of multi-effect distillation columns and integrated water networks to show that the energy effi-ciency and water consumption in bioethanol plants can be significantly improved. Specifically,under some circum-stances energy can even be produced and the water consumption can be reduced below the values required for the production of gasoline.

Design Hybrid Methods for Encoding Prior Knowledge in Feedforward Network with Application in Chemical Engineering

Three-layer feedforward networks have been widely used in modeling chemical engineering processes and prior-knowledge-based methods have been introduced to improve their performances.In this paper,we propose the methodology of designing better prior-knowledge-based hybrid methods by combining the existing ones. Then according to this methodology,two hybrid methods,interpolation-optimization (IO) method and interpolation penalty-function (IPF) method,are designed as examples.Finally,both methods are applied to modeling two cases in chemical engineering to investigate their effectiveness.Simulation results show that the performances of the hybrid methods are better than those of their parents.

Modeling of shear wave velocity in limestone by soft computing methods

The main purpose of current study is development of an intelligent model for estimation of shear wave velocity in limestone. Shear wave velocity is one of the most important rock dynamic parameters. Because rocks have complicated structure, direct determination of this parameter takes time, spends expenditure and requires accuracy. On the other hand, there are no precise equations for indirect determination of it; most of them are empirical. By using data sets of several dams of Iran and neuro-genetic, adaptive neuro-fuzzy inference system （ANFIS）, and gene expression programming （GEP） methods, models are rendered for prediction of shear wave velocity in limestone. Totally, 516 sets of data has been used for modeling. From these data sets, 413 ones have been utilized for building the intelligent model, and 103 have been used for their performance evaluation. Compressional wave velocity （Vp）, density （7） and porosity （.n）, were considered as input parameters. Respectively, the amount of R for neuro-genetic and ANFIS networks was 0.959 and 0.963. In addition, by using GEP, three equations are obtained; the best of them has 0.958R. ANFIS shows the best prediction results, whereas GEP indicates proper equations. Because these equations have accuracy, they could be used for prediction of shear wave velocity for limestone in the future.

Service optimization in programmable cloud network

With the rapid development in cloud data centers and cloud service customers,the demand for high quality cloud service has been grown rapidly.To face this reality,this paper focuses on service optimization issues in cloud computing environment.First,a service-oriented architecture is proposed and programmable network facilities are utilized in it to optimize specific cloud services.Then various cloud services are categorized into two subcategories;static services and dynamic services.Furthermore,the concepts of cloud service quality and cloud resource idle rate are defined,and the aforementioned concepts have also been taken into consideration as parameters in the service optimization algorithm to improve the cloud service quality and optimize system workload simultaneously.Numerical simulations are conducted to verify the effectiveness of the proposed algorithm in balancing the workload of all servers.

Prediction of blast-induced ground vibrations via genetic programming

Excessive ground vibrations, due to blasting, can cause severe damages to the nearby area. Hence, the blast-induced ground vibration prediction is an essential tool for both evaluating and controlling the adverse consequences of blasting. Since there are several effective variables on ground vibrations that have highly nonlinear interactions, no comprehensive model of the blast-induced vibrations are available. In this study, the genetic expression programming technique was employed for prediction of the frequency of the adjacent ground vibrations. Nine input variables were used for prediction of the vibration frequencies at different distances from the blasting face. A high coefficient of determination with low mean absolute percentage error(MAPE) was achieved that demonstrated the suitability of the algorithm in this case. The proposed model outperformed an artificial neural network model that was proposed by other authors for the same dataset.

Real-Time Upstream Services Demonstration in Orthogonal Frequency Division Multiplexing- Passive Optical Network System

Abstract： Real-time digital service and mul- timedia service upstream transmission in Dig- ital Signal Processing （DSP）-based Orthogo- nal Frequency Division Multiplexing-Passive Optical Network （OFDM-PON） is experimen- tally demonstrated with Centralised Light Sou- rce （CLS） configuration in this paper. After transmitted over 25 km Standard Single Mode Fibre （SSMF） with -16.5 dBm optical power at receiver, the Bit Error Rate （BER） is 9.5 ×10^-11. The implementations of digital domain up-conversion and down-conversion based on Field Programmable Gate Array （FPGA） are int- roduced, which can reduce the cost of In-ph- ase and Quadrature （IQ） radio frequency mix- ers utilised at transmitter and receiver. A car- rier synchronization algorithm is implemented for compensating carrier offset. A channel eq- ualization algorithm is adopted for compen- sating the damage of channel. A new structure of Frequency Synchronization Unit （FSU） des- igned in FPGA is also proposed to cope with the frequency shifting at receiver.

The Rise and Fall of Social Networking Sites： A Comparative Study of Cyworld and Facebook

This study examines why some social networking sites （SNSs） stagnate while other SNSs grow by comparing Cyworld with Facebook. Cyworld was one of the most successful SNSs in the world, but its international expansion efforts failed. Facebook＇s open technology has had considerable influence on various sectors of the economy and society and allowed it to become a dominant SNS at the global level, whereas Cyworld has remained a local SNS. Facebook＇s open platform and application programming interface （API） pose a serious challenge to Cyworld＇s walled-garden approach. Cyworld is based on strong ties fostering close relationships, whereas Facebook expands social networks through its open and weak ties and has more network power than Cyworld. Therefore, openness is the main reason behind the rise of Facebook and the fall of Cyworld.

Embedded FPGA Simulator for Wireless Sensor Network Design

The design, manufacture and deployment of embedded systems become increasingly complex and multidisciplinary process. Before the steps of manufacturing and deployment, a simulation and validation phase is necessary. In this paper, a WSN （wireless sensors network） emulator, implemented on a FPGA, is described by： describing some models as examples, how multiple simulations can be done when the device was configured and programmed once, and how results from the behavioral emulator can be extracted. The diversity of applications and the typically scarce node resources set very tight constraints to WSN. It is not possible to fulfill all requirements with a general purpose WSN, for which reason the rapid development of application specific WSNs is preferred. A new emulator for the design, simulation, and evaluation of WSNs, implemented on a very dense FPGA （field programmable gate arrays）, is presented, exploring the parallelism and his resources to do a very rapid simulation ofa WSN for long periods, and without overloading memory by the intermediate data.

A reliable opportunistic routing for smart grid with in-home power line communication networks

The topology of in-home power line communication(PLC) networks varies frequently, which makes traditional routing algorithms failure. To solve this problem, an end-to-end transmission time for remaining path(TTRP) metric-based opportunistic routing(TTRPOR) is proposed. Since a local broadcasting scheme is adopted, the algorithm can find the optimal path for forwarding packets in a dynamic PLC network. The closed-form of the outage probability for a PLC channel is derived to estimate the TTRP. It is proved that the average throughput can achieve maximum as the metric TTRP is utilized to sort candidate forwarding nodes.Numerical results show that the end-to-end throughput of networks with TTRPOR, outperforms that of the network adopting DSR and EXOR, especially for the case of varying-topology in-home PLC networks.

Towards high-performance packet processing on commodity multi-cores: current issues and future directions

The demands of programmability have become more and more exigent as novel network services appear, such as E-commerce, social softwares, and online videos. Commodity multi-core CPUs have been widely applied in network packet processing to get high programmability and reduce the time-to-market. However,there is a great gap between the packet processing performance of commodity multi-core and that of the traditional packet processing hardware, e.g., NP(Network Process). Recently, optimization of the packet processing performance of commodity multi-cores has become a hot topic in industry and academia. In this paper, based on a detailed analysis of the packet processing procedure, firstly we identify two dominating overheads, namely the virtual-to-physical address translation and the packet buffer management. Secondly, we make a comprehensive survey on the current optimization methods. Thirdly, based on the survey, the heterogeneous architecture of the commodity multi-core + FPGA is proposed as a promising way to improve the packet processing performance.Fourthly, a novel Self-Described Buffer(SDB) management technology is introduced to eliminate the overheads of the allocation and deallocation of the packet buffers offloaded to FPGA. Then, an evaluation testbed, named PIOT(Packet I/O Testbed), is designed and implemented to evaluate the packet forwarding performance. I/O capacity of different commodity multi-core CPUs and the performance of optimization methods are assessed and compared based on PIOT. At last, the future work of packet processing optimization on multi-core CPUs is discussed.

FORECASTING TIME SERIES WITH GENETIC PROGRAMMING BASED ON LEAST SQUARE METHOD

Although time series are frequently nonlinear in reality, people tend to use linear models to fit them under some assumptJLons unnecessarily in accordance with the truth, which unsurprisingly leads to unsatisfactory performance. This paper proposes a forecast method： Genetic programming based on least square method （GP-LSM）. Inheriting the advantages of genetic algorithm （GA）, without relying on the particular distribution of the data, this method can improve the prediction accuracy because of its ability of fitting nonlinear models, and raise the convergence speed benefitting from the least square method （LSM）. In order to verify the vMidity of this method, the authors compare this method with seasonal auto regression integrated moving average （SARIMA） and back propagation artificial neural networks （BP-ANN）. The results of empirical analysis show that forecast accuracy and direction prediction accuracy of GP-LSM are obviously better than those of the others.