Novel dynamic load balancing algorithm for cloud-based big data analytics

Big data analytics in cloud environments introduces challenges such as real-time load balancing besides security, privacy, and energy efficiency. This paper proposes a novel load balancing algorithm in cloud environments that performs resource allocation and task scheduling efficiently. The proposed load balancer reduces the execution response time in big data applications performed on clouds. Scheduling, in general, is an NP-hard problem. Our proposed algorithm provides solutions to reduce the search area that leads to reduced complexity of the load balancing. We recommend two mathematical optimization models to perform dynamic resource allocation to virtual machines and task scheduling. The provided solution is based on the hill-climbing algorithm to minimize response time. We evaluate the performance of proposed algorithms in terms of response time, turnaround time, throughput metrics, and request distribution with some of the existing algorithms that show significant improvements.

     

Enhanced Hole-Carrier Selectivity in Wide Bandgap Halide Perovskite Photovoltaic Devices for Indoor Internet of Things Applications

Halide perovskite-based photovoltaic (PV) devices have recently emerged for low energy consumption electronic devices such as Internet of Things (IoT). In this work, an effective strategy to form a hole-selective layer using phenethylammonium iodide (PEAI) salt is presented that demonstrates unprecedently high open-circuit voltage of 0.9 V with 18 µW cm⁻² under 200 lux (cool white light-emitting diodes). An appropriate post-deposited amount of PEAI (2 mg) strongly interacts with the perovskite surface forming a conformal coating of PEAI on the perovskite film surface, which improves the crystallinity and absorption of the film. Here, Kelvin probe force microscopy results indicate the diminished potential difference across the grain boundaries and grain interiors after the PEAI deposition, constructing an electrically and chemically homogeneous surface. Also, the surface becomes more p-type with a downshift of a valence band maximum, confirmed by ultraviolet photoelectron spectroscopy measurement, facilitating the transport of holes to the hole transport layer (HTL). The hole-selective layer-deposited devices exhibit reduced hysteresis in light current density–voltage curves and maintain steadily high fill factor across the different light intensities (200–1000 lux). This work highlights the importance of the HTL/perovskite interface that prepares the indoor halide perovskite PV devices for powering IoT device.     

Radiosensitivity of Saccharomyces yeasts and srm genes: effects of srm1 and srm5 mutations

The presence in the cell genotype of srm1 and srm5 (cdc28-srm) mutations decreasing the spontaneous rho- mutability was shown to have no effect on the rates of spontaneous nuclear gene mutations and gamma-ray-induced mitotic recombination. Mutation cdc28-srm exerts a marked effect on cell sensitivity to the lethal action of ionizing radiation and on the appearance of homoplasmic segregants generated from heteroplasmic diploids. Additive interactions between mutations cdc28-srm and each of the rad6 and rad52 mutations were revealed by an analysis of double mutants with respect to their sensitivity to radiation. Mutation rad9 was epistatic with mutation cdc28-srm. These data agree with the idea that the p34CDC28 gene product is a target for the RAD9-dependent feedback control operating at the cell cycle checkpoints (checkpoint control) and ensuring an additional amount of time for premitotic repair of chromosomal DNA damage.     

Facile fabrication of mesoporous carbon nanofibers with unique hierarchical nanoarchitecture for electrochemical hydrogen storage

A colloidal silica incorporated porous anodic aluminum oxide (AAO) was utilized as a dual-template to prepare mesoporous carbon nanofibers (MCNFs). Such a strategy is simple because it takes advantage of commercially available materials (i.e., colloidal silica and AAO) and the templates can be removed in one step. The as-prepared MCNF shows a hierarchical nanostructure consisting of open macroporous channel connected with large mesopores and micropores. As a result of the large surface area and unique hierarchical nanoarchitecture which facilitates fast mass and electron transport, the MCNF reveals a discharge capacity of 679 mA h g⁻¹ at 25 mA g⁻¹. This value is significantly greater than that (i.e., 394 mA h g⁻¹) observed for an ordered mesoporous carbon (OMC) with a similar specific surface area. Furthermore, at 3000 mA g⁻¹, the MCNF demonstrates a discharge capacity of 585 mA h g⁻¹, which is about twice that (i.e., 256 mA h g⁻¹) of the OMC.     

A new weighted optimal combination of ANNs for catalyst design and reactor operation: Methane steam reforming studies

Catalyst design and evaluation is a multifactorial multiobjective optimization problem and the absence of well‐defined mechanistic relationships between wide ranging input‐output variables has stimulated interest in the application of artificial neural network for the analysis of the large body of empirical data available. However, single ANN models generally have limited predictive capability and insufficient to capture the broad range of features inherent in the voluminous but dispersed data sources. In this study, we have employed a Fibonacci approach to select optimal number of neurons for the ANN architecture followed by a new weighted optimal combination of statistically‐derived candidate ANN models in a multierror sense. Data from 200 cases for catalytic methane steam reforming have been used to demonstrate the veracity and robustness of the integrated ANN modeling technique. © 2011 American Institute of Chemical Engineers AIChE J, 58: 2412–2427, 2012     

The Use of Thermal Lattice Boltzmann Numerical Scheme for Particle-Laden Channel Flow with a Cavity

In this article, particle-laden flow in a channel with heated cavity has been investigated. Calculations were performed using a point force scheme for particle dynamics, while the process of fluid renewal was modeled using the double-population thermal lattice Boltzmann method. Point-particle formulation accounts for the finite-size dispersed phase and the forces acting on the particles were modeled through drag force correlations. Two-way interactions of solid-fluid calculation were considered by adding an external force term for feedback that forced particles in the evolution of fluid distribution function. The method was first validated with steady state flow in a channel with cavity in the presence and absence of a heat source. It was then applied to mixed convection flow laden with particles at various Grashof numbers. The particle dispersion characteristics were examined in detail, where the particle removal rate from cavity upon cavity aspect ratio was emphasized. The effect of the Reynolds number on particle distribution was further investigated numerically by varying the speed of inlet flow into the channel.     

TWO-LAYER-MODEL PREDICTIONS OF HEAT TRANSFER INSIDE ENHANCED TUBES

ABSTRACT

Turbulent flow in axisymmetric enhanced tubes with repeated transverse rectangular disruptions was simulated using the two-layer turbulence model of Chen and Patel 111. The predictions were in good agreement with experimental data for friction factors and both local and average Nusselt numbers. The low-Reynolds-number two-equation model of Lam and Bremhorst 121 was considered, and the predicted results were also compared with local heat transfer measurements. This model overestimated the local Nusselt numbers at some locations by about a factor of 2. Results from the two turbulence models were also compared for a sudden pipe-expansion geometry. The Lam and Bremhorst model yielded acceptable local Nusselt number predictions, while the Chen and Patel model underpredicted the local Nusselt numbers and predicted the location of the heat transfer maximum further upstream.     

Comments on ‘Lattice Boltzmann simulation of alumina-water nanofluid in a square cavity’ by Yurong He,Cong Qi,Yanwei Hu,Bin Qin,Fengchen Li and Yulong Ding

This work presents some comments concerning the paper entitled ‘Lattice Boltzmann simulation of alumina-water nanofluid in a square cavity’ by Yurong He, Cong Qi, Yanwei Hu, Bin Qin, Fengchen Li and Yulong Ding which was published in Nanoscale Research Letters in 2011. The comments are related to the numerical parameters and the computed results of average Nusselt number.     

Decision making on business issues with foresight perspective; an application of new hybrid MCDM model in shopping mall locating

Shopping malls are one of the glories of metropolises with their attractive shops and a wide variety people who are walking in order to purchase goods. Location of a shopping mall is one of the critical criteria, because it can influence the success of the project. In addition, selecting an appropriate location to establish a new shopping mall is a sophisticated, time consuming and risky decision. Commonly multi-factors should be considered in the decision making model. Thus, a comprehensive model should be considered for similar studies. Moreover, the foresight perspective can be necessary for the future competitiveness of the project. Decision makers need powerful tools for the process of the decision making, for this aim two Multiple Criteria Decision Making (MCDM) methods are applied in our model. Stepwise Weight Assessment Ratio Analysis (SWARA) is applied to decision making in order to prioritize and calculating the relative importance of the criteria. Then, Weighted Aggregated Sum Product Assessment (WASPAS) methodology is used to evaluate potential alternatives. Tehran is considered as a real example of this research and potential places for this mean considered in research. This brand-new hybrid MCDM method is presented in this research as a powerful framework is decision making. This framework can be useful as an appropriate framework for solving locating issues in other companies.