Migration cost optimization for service provider legacy network migration to software-defined IPv6 network

This paper studies a problem for seamless migration of legacy networks of Internet service providers to a software-defined networking (SDN)-based architecture along with the transition to the full adoption of the Internet protocol version 6 (IPv6) connectivity. Migration of currently running legacy IPv4 networks into such new approaches requires either upgrades or replacement of existing networking devices and technologies that are actively operating. The joint migration to SDN and IPv6 network is considered to be vital in terms of migration cost optimization, skilled human resource management, and other critical factors. In this work, we first present the approaches of SDN and IPv6 migration in service providers' networks. Then, we present the common concerns of IPv6 and SDN migration with joint transition strategies so that the cost associated with joint migration is minimized to lower than that of the individual migration. For the incremental adoption of software-defined IPv6 (SoDIP6) network with optimum migration cost, a greedy algorithm is proposed based on optimal path and the customer priority. Simulation and empirical analysis show that a unified transition planning to SoDIP6 network results in lower migration cost.     

Evolutionary gaming approach for decision making of Tier‐3 Internet service provider networks migration to SoDIP6 networks

With the increasing number of Internet of Things (IoT) devices, current networking world is suffering in terms of management and operations with lack of IPv4 addresses leading to issues like network address translation (NAT) proliferation, security and quality of services. Software‐defined networking (SDN) and Internet Protocol version 6 (IPv6) are the new networking paradigms evolved to address related issues of legacy IPv4 networking. To adapt with global competitive environment and avoid all existing issues in legacy networking system, network service providers have to migrate their networks into IPv6 and SDN‐enabled networks. But immediate transformations of existing network are not viable due to several factors like higher cost of migration, lack of technical human resources, lack of standards and protocols during transitions, and many more. In this paper, we present the migration analysis for proper decision making of network transition in terms of customer demand, traffic engineering, and organizational strength with operation expenditure for network migration using evolutionary gaming approach. Joint migration to SDN‐enabled IPv6 network from game theoretic perspective is modeled and is validated using numerical results obtained from simulations. Our empirical analysis shows the evolutionary process of network migration while different internal and external factors in the organization affect the overall migration. Evolutionary game in migration planning is supportive in decision making for service providers to develop suitable strategy for their network migration. The proposed approach for migration decision making is mostly applicable to fairly sustained service providers who lack economics, regulation/policy, and resources strengths.     

House of Cards Nanostructuring of Graphene Oxide and Montmorillonite Clay for Oil–Water Separation

Noncovalent interactions are ubiquitous in our daily living. Nature employs hydrophobic effects, π–π interactions, hydrogen bonding, van der Waals forces, and electrostatic interactions in many biological processes such as protein folding. In the same manner, scientists exploit this plethora of inherently reversible noncovalent interactions as dials to design robust and smart materials. Electrostatic interaction is particularly interesting due to the simplicity of its concept, i.e., opposite charges attract. However, to our knowledge, the electrostatic interaction between two different 2D nanomaterials has not been investigated in literature. A myriad of natural and synthetic 2D nanomaterials should be explored for what may be an exciting cocktail of synergistic and tunable properties brought about by their charges and physical properties. This contribution highlights an interesting phenomena when organic, negatively charged graphene oxide and inorganic, positively charged montmorillonite (MMT) clay edges are brought into contact.     

Effectiveness of sodium silicate as gangue depressants in iron ore slimes flotation

The recovery of iron from the screw classifier overflow slimes by direct flotation was studied.The relative effectiveness of sodium silicates with different silica-to-soda mole ratios as depressants for silica and silicate bearing minerals was investigated.Silica-to-soda mole ratio and silicate dosage were found to have significant effect on the separation efficiency.The results show that an increase of Fe content in the concentrate is observed with concomitant reduction in SiO2 and Al2O3 levels when a particular type of sodium silicate at a proper dosage is used.The concentrate of 58.89wt％ Fe,4.68wt％ SiO2,and 5.28wt％ Al2O3 with the weight recovery of 38.74％ and the metal recovery of 41.13％ can be obtained from the iron ore slimes with 54.44wt％ Fe,6.72wt％ SiO2,and 6.80wt％ Al2O3,when Na2SiO3 with a silica-to-soda mole ratio of 2.19 is used as a depressant at a feed rate of 0.2 kg/t.     

测控技术在电子技术中的实际应用研究

本文先对测控技术的主要特点进行总结,再分析了当前电子技术的发展过程中测控技术的主要应用方向,旨在提高电子技术中测控技术的应用水平。     

Characterization and Reduction Roasting Studies of an Iron Rich Manganese Ore

The article presents the reduction roasting followed by low intensity magnetic separation studies of a low grade Mn ore assaying 27.7% Mn and 26.1% Fe in order to obtain a Mn rich non-magnetic concentrate. The reflected light microscopic studies followed by the liberation studies of the as-received sample using quantitative mineralogical evaluation by scanning electron microscope suggested a poor liberation pattern of the constituent Mn and Fe minerals owing to a complex association of the different phases present. The reduction roasting studies carried out while varying different process parameters such as ore particle size, temperature, reductant content and residence time ended up with products containing 45–48% Mn with a Mn/Fe ratio of 5–6 at a yield of ~ 60% with the optimum level of conditions such as temperature: 800–850 °C, time: 90–120 min and charcoal: 10–12%. The scanning electron microscopy–energy dispersive X-ray spectroscopy studies of the roasted product reported manganite as the major Mn bearing phase while magnetite was found to be the major iron bearing phase.     

砂土单调剪切特性的非圆颗粒模拟

针对纯圆颗粒模拟的缺陷,利用颗粒流"团颗粒"方法开发了形状近似椭圆的"椭圆团颗粒",研究了颗粒形状变化对数值试样宏观剪切特性的影响及其细观机理;分析了加荷过程中平均接触数的变化规律以及颗粒形状对临界接触数的影响;对比了纯圆颗粒和椭圆团颗粒的不同颗粒旋转特性,并初步探讨其机理;分析了剪切过程中椭圆团颗粒试样的组构各向异性演化规律。结果表明,颗粒形状对试样的强度和变形特性具有重要影响,其在细观机理上与平均接触数有关;剪切荷载作用下椭圆团颗粒试样呈现明显的组构各向异性,颗粒长轴逐渐趋于水平定向,接触法向逐渐偏于加荷的大主应力方向。     

New Modified Controlled Bat Algorithm for Numerical Optimization Problem

Bat algorithm (BA) is an eminent meta-heuristic algorithm that has been widely used to solve diverse kinds of optimization problems. BA leverages the echolocation feature of bats produced by imitating the bats’ searching behavior. BA faces premature convergence due to its local search capability. Instead of using the standard uniform walk, the Torus walk is viewed as a promising alternative to improve the local search capability. In this work, we proposed an improved variation of BA by applying torus walk to improve diversity and convergence. The proposed. Modern Computerized Bat Algorithm (MCBA) approach has been examined for fifteen well-known benchmark test problems. The finding of our technique shows promising performance as compared to the standard PSO and standard BA. The proposed MCBA, BPA, Standard PSO, and Standard BA have been examined for well-known benchmark test problems and training of the a.pngicial neural network (ANN). We have performed experiments using eight benchmark datasets applied from the worldwide famous machine-learning (ML) repository of UCI. Simulation results have shown that the training of an ANN with MCBA-NN algorithm tops the list considering exactness, with more superiority compared to the traditional methodologies. The MCBA-NN algorithm may be used effectively for data classification and statistical problems in the future.