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Network Function Virtualization (NFV) is a new paradigm to enable service innovation through virtualizing traditional network functions. To construct a new NFV-enabled network, there are two critical requirements: minimizing server deployment cost and satisfying switch resource constraints . However, prior work mostly focuses on the server deployment cost, while ignoring the switch resource constraints ( e.g. , switch’s flow-table size). It thus results in a large number of rules on switches and leads to massive control overhead. To address this challenge, we propose an incremental server deployment (INSD) problem for construction of scalable NFV-enabled networks. We prove that the INSD problem is NP-Hard, and there is no polynomial-time algorithm with approximation ratio of $(1-\epsilon) \cdot \ln m$ , where $\epsilon $ is an arbitrarily small value and $m$ is the number of requests in the network. We then present an efficient algorithm with an approximation ratio of $2\cdot H(q\cdot p)$ , where $q$ is the number of VNF’s categories and $p$ is the maximum number of requests through a switch. We evaluate the performance of our algorithm with experiments on physical platform (Pica8), Open vSwitches, and large-scale simulations. Both experimental results and simulation results show high scalability of the proposed algorithm. For example, our solution can reduce the control and rule overhead by about 88% with about 5% additional server deployment, compared with the existing solutions.

We study mean field Stackelberg games between a major player (the leader) and a large population of minor players (the followers). By treating the mean field as part of the dynamics of the major player and a representative minor player, we Markovianize the decision problems and employ dynamic programming to determine the equilibrium strategy in a state feedback form. We show that for linear quadratic (LQ) models, the feedback equilibrium strategy is time consistent. We further give the explicit solution in a discrete-time LQ model.

White light-emitting diodes (WLEDs), which have high luminous brightness, longevity, low energy consumption and friendliness of environment, could be employed in diverse fields. Nevertheless, commercial phosphors are short of red light component. New phosphors which can emit red light are required. Mn2+ doped aluminum nitride (marked as AlN) red phosphors were prepared by a simple solid-state reaction. X-ray diffraction (XRD), scanning electron microscope (SEM), high-resolution transmission electron microscopy (HRTEM), and X-ray photoelectron spectroscopy (XPS), as well as photoluminescence (PL) spectra are utilized to characterize the prepared samples. The preparing process of AlN phosphors, phase formation and crystal structure, morphology, and photoluminescence are detailedly investigated. For Mn2+ doped AlN phosphor(marked as AlN:Mn2+), it exhibits an intense red emission caused by the 4T1(4G)-6A1(6S) transition of Mn2+. The unusual red emission of Mn2+ is ascribed to the strong nephelauxetic and crystal field between Mn2+ and the tetrahedrally coordinated N3−. The oxygen-related defects in AlN have a great influence on the photoluminescence properties of the Mn2+ doped AlN. The AlN:Mn2+ phosphors exhibits a high brightness, high color purity, and lower saturation, which make it a great candidate of red phosphors for white light-emitting diodes (WLEDs).

The (Fe1-xDyx)3C@C composites were produced by a simple sol-gel route. The structure, composition, morphology and magnetism of the composites are studied by many characterization methods, for example, X-ray powder diffraction (XRD), X-ray photoelectron spectroscopy (XPS), scanning and transmission electron microscopy (SEM, TEM) as well as vibrating sample magnetometer (VSM). Analysis of the above results indicates that the (Fe1-xDyx)3C is embedded in carbon nanotubes and carbon matrix and displays ferromagnetic properties. Moreover, this indicates that saturation magnetization (MS) values of the composites tend to increase with the increase in Dy doping. More importantly, we investigates the electrochemical hydrogen production capacity of the (Fe1-xDyx)3C@C composites.

Software defined networking is a new paradigm that separates the control plane from the data plane. To provide high scalability and reduce the controller load in a large-scale software defined network (SDN), a natural way is to deploy a cluster of distributed controllers so as to cooperatively manage the network. However, since each controller just manages a set of the connected (or associated) switches and usually holds the information of these switches (and connected links), it may result in controller load imbalance and link load imbalance. Thus, both controller load and link load should be optimized to achieve better QoS in SDNs. To this end, this paper tries to answer the following question: how to perform both controller load balancing and link load balancing in an SDN? We formulate the load-balancing routing for both links and controllers (LBR-LC) problem in an SDN, and prove its NP-hardness. A rounding-based algorithm is proposed to solve this problem, and the approximation performance is also analyzed. Moreover, we discuss the efficient mechanism for network status maintenance among distributed controllers. The extensive simulation results show that our proposed algorithm can reduce the maximum controller response time by 70% compared with the previous solution, while only increasing the maximum link load by 3%.

(Fe1−xNdx)3N was successfully prepared by a simple complex method. The as-synthetized (Fe1−xNdx)3N exhibits regular rod-like morphology and excellent magnetic properties. X-ray diffraction, scanning electron microscopy with Energy dispersive X-ray spectroscopy, high-resolution transmission electron microscopy, X-ray photoelectron spectroscopy, as well as vibrating sample magnetometer are employed to analyze the structure, morphology and magnetic properties of the samples. What’s more, when the Nd doping concentration is 3%, the coercivity reaches a higher value of 664.61 Oe. It is much higher than the coercivity of 408.84 Oe for the pure Fe3N. The material shows a trend of transition to hard magnet. It opens the way for other soft magnet translating into hard magnet by doping rare earth ions.

To better serve a diversity of flows, load balancing is crucial to ensure operational efficiency. However, previous works for load balancing have several disadvantages: 1) limited applicability with sub-flow scheduling (e.g., LetFlow); 2) hash collision (e.g., ECMP); or 3) transient network congestion due to reactive scheduling for traffic dynamics (e.g., Hedera and DevoFlow). An important reason for the above disadvantages is that it is difficult to provide fully fine-grained flow control for load balancing in an SDN as the flow table size of each SDN switch is usually limited. Inspired by the fact that a virtual switch (vswitch) has more powerful processing capacity and more flow entries compared with a physical switch, the previous work (e.g., Presto) deploys one vswitch for each ingress switch, and achieves the load balancing through efficient flow routing. However, this mechanism may lead to high cost and not well deal with topology asymmetry. Thus, this paper proposes to achieve the load balancing by incrementally deploying a certain number of vswitches in an SDN. We formulate the joint optimization of vswitch deployment and routing (JVR) problem as an integer linear program, and prove its NP-hardness. A rounding-based algorithm with bounded approximation factors is proposed to solve the JVR problem. We implement the proposed algorithm on an SDN testbed for experimental studies and use simulations for large-scale investigation. The experimental results and simulation results show high efficiency of our algorithm. For example, our proposed algorithm can reduce the link load ratio by about 41.5% compared with ECMP by deploying a small number of virtual switches.

We investigated the CT process between a 4-mercaptobenzoic acid (4-MBA) monolayer and TiO2 NPs under high pressure using surface-enhanced Raman scattering (SERS). Employing the CT enhancement mechanism of semiconductors, we explore the CT process and explain how the pressure affects the process in the 4-MBA@TiO2 system.

Anycast mechanism has been used as a fundamental technology in many fields, with multiple servers providing the same service. Each request does not care which server it is served by. For security and performance reasons, requests must meet the requirements of service function chain (SFC) in network function virtualization (NFV) enabled networks. Though the routing of SFC has been widely studied, most of these works focus on unicast, which does not involve server selection, and cannot be applied directly for anycast. If we simply combine the traditional anycast algorithms and SFC unicast routing algorithms, it will overload the links and servers. Since overloaded links and servers will reduce the quality of services, it is important to balance the load of links and servers. In this work, we focus on designing an SFC routing mechanism for anycast that takes server selection into account and achieves load balancing among servers as well as links with the help of software defined network (SDN). We first propose the problem of joint server selection and SFC routing for anycast in NFV-enabled SDNs (JSR). Then based on the method of random rounding, we design an algorithm called RBLB with approximate ratio guarantee that can solve the JSR problem. The extensive simulation results show that our algorithm can reduce the load of servers and links. For example, algorithm RBLB can reduce the server load by 41.4%–60.1% compared with the comparison algorithm, when the number of requests exceeds 20k.

Link failure is a major problem that must be addressed, which occurs frequently in large networks. In a software-defined network, the recovery scheme for single link failure can be divided into two categories: proactive and reactive. For reactive scheme, it takes a long time to recover due to the controller participation. Though the proactive scheme can achieve faster recovery, it may consume a large number of forwarding rules, which is typically limited on switches due to expensiveness and power hungry. Therefore, this paper proposes a proactive recovery scheme for single link failure based on segment routing with less forwarding rules. In the proposed scheme, we regard the affected flows through the same link as an aggregated flow and use the link protection methods to achieve link failures recovery. The link protection methods calculate backup paths for each link of the working path, so we propose the backup paths calculation problem and formulate it as an mixed integer non-linear programming model. To solve the problem and avoid link congestion, we design an efficient algorithm to select the most appropriate backup path. In addition, due to the limitation of the maximal number of MPLS labels that the packet header can hold, we design an algorithm to divide the working and backup path into segments to meet the hardware requirements. The simulation results show that the proposed algorithms outperform CAFFE and SPR by 14.7% and 77.1% on recovery time, and outperform CAFFE by 21.5% on forwarding rules consumption. Moreover, the proposed scheme does not cause congestion in post-recovery network.

MgFe2O4 with inverse spinel structure is demonstrated to be an efficient support for constructing practical potential Pt catalyst (Pt/MgFe2O4). The resultant Pt/MgFe2O4 exhibits excellent catalytic behavior in CO oxidation under normal temperature and humidity. TOF calculated based on the content of Pt is 0.131 s–1. The excellent performance of Pt/MgFe2O4 attributes to the presence of surface undercoordinated lattice oxygens on MgFe2O4 support. These oxygens could participate in the initial CO oxidation and then be recovered under O2 conditions. Over this Pt/MgFe2O4 catalyst, CO catalytic oxidation should mainly follow a redox mechanism.

Semiconductor nanomaterial is a kind of important enhancement substrate in surface-enhanced Raman scattering (SERS), and the charge-transfer (CT) process contributes dominantly when they are used as the enhancement substrate for SERS. Doping has significant effect on the CT process of semiconductor nanomaterials. Yet till now, none attempts have been made to explore how doping affects the CT process between the semiconductor and probe molecules. For the first time, this paper investigates the effect of gallium (Ga) doping on the CT process between ZnO nanoparticles and 4-mercaptobenzoic acid (4-MBA) monolayer. In this paper, a series of Ga-doped ZnO nanoparticles (NPs) with various ratio of Ga and Zn are synthesized and their SERS performances are studied. The study shows that the doped Ga can cause the band gap shrinkage of ZnO NPs and then affect the CT resonance process form the valence band (VB) of ZnO NPs to the LUMO of 4-MBA molecules. The band gap of Ga-doped ZnO NPs is gradually narrowed with the increasing doping concentration, and a minimum value (3.16 eV) is reached with the Ga and Zn ratio of 3.8%, resulting in the maximum degree of CT. This work investigates the effects of doping induced band gap shrinkage on CT using SERS and provides a new insight on improving the SERS performance of semiconductor NPs.

Fe3C is a promising material with both high saturation magnetization and chemical stability. In this article, we present a facile sol–gel route for the synthesis of Fe3C/Fe nanocomposites, in which bromide was found to be the inducing agent for the conversion of FeCl3 to Fe3C. X-ray diffraction, transmission electron microscopy, and vibrating sample magnetometer were used to characterize the composites. The experimental results show that the composition and magnetic properties of Fe3C/Fe composites can be controlled by changing reaction temperatures, reaction time and the amount of inducing agent. Moreover, the possible formation mechanism of as-prepared nanostructures is discussed.