Solar power system mainly consists of solar cells,however,at present defects of solar cells are detected mainly by manual operation,which is time-consuming and needs high labor costs,besides,it is easy to be misled by subjective factors.This paper proposes a method of detection of solar cells surface defects based on Robust PCA.Our method tries to transform the image matrix,so that it can be decomposed as the sum of a low-rank matrix of defect-free image and a sparse matrix of defective image.We minimize the nuclear norm and 1-norm of the two component matrices through convex optimization,so that the decomposition of the matrix can implement efficiently and fast.Meantime,we discuss two algorithms of Accelerated Proximal Gradient(APG)and Inexact Augmented Lagrange Multiplier(IALM)for solving this optimization problem,and compare their computing time and convergence in the detection of solar cells surface defects.We verify the feasibility and validity of the proposed method on detection of solar cells surface defects with extensive experiments.

Now there is no good solution to the problem of geometric K-center gateway deployment in wireless mesh networks,and the problem is deploying some gateways in given geometric plane to meet coverage conditions and improve the quality of service.To solve the problem,the concept and algorithm of great alternative region are first proposed in the paper.The plane area is divided into different alternative regions in accordance with the nature of network topology and the unit disk and the difference connectivity.Then great alternative regions with the most complete function are filtered out and each great alternative region is inserted into the original network as a virtual node,a new network topology is generated and the geometric K-center problem is transformed into a node K-center problem.Regarding maximum minimum hops as object optimization,an improved genetic algorithm is proposed.Comparing with Kmeans algorithm,the genetic algorithm can achieve better gateway clustering effect,and the simulations show that the proposed method can solve the geometric K-center wireless gateway deployment problem.

Reconfiguration routers have an architecture made up of components,which make the energy meticulous-grained scaling to be real.In this paper,we propose an energy meticulousgrained scaling algorithm to deal with the routers'energy problem,which is based on the idea that components energy can change with application load variety.It first predicts the future workloads of the applications with Brown's quadratic exponential smoothing method to make reconfiguration catch up with loads.Next,it adopts a genetic algorithm to parallel find the optimal reconfiguration policy.The real network traffic is used to check the algorithm.Experimental results demonstrate the approach can adapt the router's energy according to the change of network traffic,reduce the algorithm computing time by 60%and the energy consumption by 25%.

Comparing to the booming prosperity of the Internet application and the underlying communication technology,the basic network architecture of the Internet has not been developed simultaneously,and is based on the beginning design of TCP/IP protocol.With the evolvement of application environment,user requirements and underlying facilities,the existing network architecture has exposed more and more defects.For these problems,researchers have proposed many new network architecture,concepts,services,protocols,and algorithms to build the new Future Internet,which is different from the existing Internet.However,any of such new ideas must be tested and evaluated rigorously before being realized or deployed in the actual Internet.So it is not only the base of Future Internet research,but also the way to explore the Future Internet itself to build the large-scale,realistic,controlled experiment platform.This paper concludes and categorizes the experiment platform from the basic characteristics of scale,function,openness,science experimentation elements,and network element type.The architecture principle and hierarchical framework are analyzed.Apart from that,the key technologies to build Future Internet,including the experiment description language,control framework and network resource slicing,are analyzed mainly.After that,the status of domestic experiment platform is analyzed.Finally,the development trend of Future Internet experiment platform is discussed.

With the advances in heterogeneous wireless networks and smart mobile terminals,mobile multimedia conferencing gradually becomes the new trend and research focus.However,in the unreliable and time-varying wireless networks,video stalls and glitches caused by the endto-end delay often occur during the meeting sessions.These problems significantly degrade the Quality of Service(QoS)of the multimedia conferencing.In this paper,we propose an application-layer end-to-end QoS guarantee strategy,which jointly exploits the packet fragmentationreassembly and path diversity over heterogeneous wireless networks.First,video packets are fragmented into several units with regard to bandwidth,latency,weight,packet size and other metrics.Second,after the arrival of all the fragmented units,they will be checked and reassembled.This process is realized by the proposed PFDA-PRRA algorithm,which constructs an endto-end virtual path for guaranteeing the fast transmission of video streaming.Simulation results show that the proposed QoS guarantee strategy effectively aggregates bandwidth of heterogeneous wireless networks and reduces one-way delay.