Multiple Workflow Scheduling Strategies with User Run Time Estimates on a Grid

In this paper, we present an experimental study of deterministic non-preemptive multiple workflow scheduling strategies on a Grid. We distinguish twenty five strategies depending on the type and amount of information they require. We analyze scheduling strategies that consist of two and four stages: labeling, adaptive allocation, prioritization, and parallel machine scheduling. We apply these strategies in the context of executing the Cybershake, Epigenomics, Genome, Inspiral, LIGO, Montage, and SIPHT workflows applications. In order to provide performance comparison, we performed a joint analysis considering three metrics. A case study is given and corresponding results indicate that well known DAG scheduling algorithms designed for single DAG and single machine settings are not well suited for Grid scheduling scenarios, where user run time estimates are available. We show that the proposed new strategies outperform other strategies in terms of approximation factor, mean critical path waiting time, and critical path slowdown. The robustness of these strategies is also discussed.     

A new multi-level trust management framework (MLTM) for solving the invalidity and sparse problems of user feedback ratings in cloud environments

Choosing a trusted cloud service provider (CSP) is a major challenge for cloud users (CUs) in the cloud environment, as many CSPs offer cloud services (CSs) with the same functionality. Trust evaluation of CSPs is often based on information from quality of service (QoS) monitoring and CUs’ feedback ratings. Despite the volume of feedback ratings received in trust management systems, the quality of feedback storage is very low, as many CUs do not send their feedback ratings when using CSs. Additionally, a percentage of existing feedback ratings may not be valid, since some malicious CUs send unfair feedback ratings to change the trust evaluation results. As these lead to poor data quality, the accuracy of trust evaluation results might be affected. To overcome these limitations, this paper proposes a new multi-level trust management framework, which completes previous frameworks by defining new components to improve the data quality of feedback storage. In our framework, new components were defined to solve the invalidity and sparse problems of feedback storage. Certainly, the trust assessment of CSP would be more accurate based on high-quality feedback ratings. The performance of the MLTM was evaluated using two different datasets based on a real Quality of Web Services dataset (QWS) and an artificial data set (Cloud-Armor), whose quality was reduced for the purpose of this study. Analytical values revealed that our proposed approach significantly outperformed other approaches even with the poor data quality of feedback storage.

     

An efficient facet shell element for corotational nonlinear analysis of thin and moderately thick laminated composite structures

In the present work, an efficient facet shell element for the geometrically nonlinear analysis of laminated composite structures using the corotational approach is developed. The facet element is developed by combining the discrete Kirchhoff-Mindlin triangular bending element (DKMT), and the optimal membrane triangular element (OPT). The membrane-bending coupling effect of composite laminates is incorporated in the formulation, and inconsistent stress stiffness matrix is formulated. Using corotational formulation and the proposed facet element, some example laminated composite structures with geometric nonlinearity are analyzed, and the results are compared with those found using other facet elements.     

A Launch-time Scheduling Heuristics for Parallel Applications on Wide Area Grids

Large and dynamic computational Grids, generally known as wide-area Grids, are characterized by a large availability, heterogene- ity on computational resources, and high vari- ability on their status during the time. Such Grid infrastructures require appropriate schedule mechanisms in order to satisfy the application performance requirements (QoS). In this paper we propose a launch-time heuristics to schedule component-based parallel applications on such kind of Grid. The goal of the proposed heuristics is threefold: to meet the minimal task computation- al requirement, to maximize the throughput between communicating tasks, and to evaluate on-the-fly the resource availability to minimize the aging effect on the resources state. We evaluate the proposed heuristics by simulations applying it to a suite of task graphs and Grid platforms randomly generated. Moreover, a further test was conducted to schedule a real application on a real Grid. Experimental results shown that the proposed solution can be a viable one.     

Solid State Viscoelastic Properties,Morphological and Melt Rheological Studies on PLA/TPU/POSS Nanocomposites

Effects of trifluoropropyl-substituted polyhedral oligomeric Silsesquioxane (POSS), on the morphological, rheological and dynamic mechanical properties of a series of poly(lactic acid)

(PLA)/thermoplastic polyurethane (TPU) blends were explored, thoroughly. Microscopic techniques including scanning electron microscope (SEM) and transmission electron microscope (TEM) utilized in conjunction with viscosity measurements to explain morphological dissimilarities between different samples. A remarkable morphological refinement was observed upon addition of POSS into the 50/50 PLA/TPU blend. This morphological change was detected by means of frequency sweep rheological experiments, where the shoulder-like plateau appears as a result of increase in the contribution from the interfacial component of elasticity in the enhancement of storage modulus. Based on the results of the dynamic time sweep small amplitude oscillatory shear (SAOS) experiments, a scaling relation was proposed to quantify the kinetics of phase separation and the associate time evolution of elasticity. It turned out that POSS particles can slow down the rate of morphological coarsening up to the 50%. Using dynamic mechanical thermal analysis (DMTA) and rheological experiments, the differences in the rate of undergoing dynamics in all the length scales, starting from segmental up to the chain level, were compared for various compositions and the discrepancies were fully described based on the dissimilarities in the entanglement densities, combinatorial effects of soft and hard segments of TPU, lubricating role of POSS particles, crystallinity, and morphological characteristics of samples.     

Environmental control of the dominant phytoplankton in Aras Reservoir (Iran): A multivariate approach

This study was undertaken to determine the phytoplankton structure and the environmental variables comprising the driving factors leading to cyanobacterial blooms in Aras Reservoir. Sampling was carried out seasonally at five sampling sites along the main body of the reservoir. Samples were collected for phytoplankton identification and enumeration, chemical analyses and chlorophyll‐a (Chl‐a) concentrations at each sampling site. Principal component analysis (PCA) and two‐way unweighted pair group method with arithmetic mean (UPGMA) were performed to determine the environmental variables affecting phytoplankton community dynamics. Seventy‐two species belonging to five divisions were determined during this study. Cyanobacteria contained the highest density (74%) during the study period, with Pseudanabaena limnetica being the most abundant species. The Shannon diversity index was low (0.44–1.87), indicating a high level of cyanobacteria dominance and eutrophic water status. Principal component analysis indicated that total phosphorus and temperature were significantly associated with cyanobacteria growth. Two‐way clustering by UPGMA indicated a close relationship among sampling sites during the same season from the perspective of the phytoplankton density. The findings of this study suggested Aras Reservoir could be highly affected by agricultural runoff and untreated sewage loadings. Thus, the proper use of fertilizers and sewage treatment should be taken into account in considering effective conservation and management plans.     

Optimization of Hydraulic-Hydrologic Complex System of Reservoirs and Connecting Tunnel

Nowadays, population growth, environmental constraints and climate change can adversely affect our water supply systems’ ability to keep up with demand. Due to lack of unsuitable distribution and dispersion of water resources, precipitation, soil resources, etc., inter-basin transfers of water could be a solution in order to balancing between supply and demand water in different areas. In this study, the optimal designing of water conveyance from basin No-1 to basin No-2 is investigated. Water is transferred between these two dams by tunnel structure. Since the water flow through the tunnel is under pressure, increasing dam height will cause the decrease of tunnel diameter for constant water conveyance efficiency. The purpose of this study is transferring 95 % of water flow between two basins after supplying the agriculture consumption and environmental needs. Therefore, the mathematical program was developed first to solve the governing equations of water balance of reservoir and hydraulic of tunnel. Then, various strategies including different diameters of tunnel and dam height were considered and finally the best strategy from economic and technical viewpoint was proposed. The results showed that dam height of 151.2 m and tunnel diameter of 3.2 m are the economic options to convey of 95 % of the water.     

Elevated‐Temperature 3D Printing of Hybrid Solid‐State Electrolyte for Li‐Ion Batteries

While 3D printing of rechargeable batteries has received immense interest in advancing the next generation of 3D energy storage devices, challenges with the 3D printing of electrolytes still remain. Additional processing steps such as solvent evaporation were required for earlier studies of electrolyte fabrication, which hindered the simultaneous production of electrode and electrolyte in an all‐3D‐printed battery. Here, a novel method is demonstrated to fabricate hybrid solid‐state electrolytes using an elevated‐temperature direct ink writing technique without any additional processing steps. The hybrid solid‐state electrolyte consists of solid poly(vinylidene fluoride‐hexafluoropropylene) matrices and a Li⁺‐conducting ionic‐liquid electrolyte. The ink is modified by adding nanosized ceramic fillers to achieve the desired rheological properties. The ionic conductivity of the inks is 0.78 × 10 ^?3 S cm^?1. Interestingly, a continuous, thin, and dense layer is discovered to form between the porous electrolyte layer and the electrode, which effectively reduces the interfacial resistance of the solid‐state battery. Compared to the traditional methods of solid‐state battery assembly, the directly printed electrolyte helps to achieve higher capacities and a better rate performance. The direct fabrication of electrolyte from printable inks at an elevated temperature will shed new light on the design of all‐3D‐printed batteries for next‐generation electronic devices.     

Catalytic cracking of light naphtha over hierarchical ZSM-5 using rice husk ash as silica source in presence of ultrasound energy: Effect of carbon nanotube content

Hierarchical structured ZSM-5 was prepared by sonochemical assisted carbon nanotube templated method and their catalytic activity was examined in catalytic cracking of light naphtha. Different amounts of carbon nanotubes (5, 15, 30?wt%) was introduced into the synthesis gel, as a hard template, for mesopore creation. The rice husk ash was used as a silica source. In order to analyse physicochemical properties of synthesized catalysts, multi-techniques such as XRF, XRD, BET, FE-SEM, NH₃-TPD and TGA were used. The obtained results revealed that by adjusting the amount of carbon nanotube, catalyst properties can be favorably tuned. The XRD analysis confirmed successful synthesis of high crystalline ZSM-5 zeolite. According to the FE-SEM analysis, small rough spheres of ZSM-5 were synthesized in all samples. The use of carbon nanotube led to creating new mesopores in the ZSM-5 structure. However, increase in carbon nanotube content led to destruction of micropores of ZSM-5. The acidity of ZSM-5 slightly changed. Results from catalytic activity test showed that high catalyst stability can be achieved in presence of mesopores along with the micropores. The highest olefin yield (54?wt%) and the best catalytic stability were obtained over the synthesized ZSM-5 with 15?wt% carbon nanotube.     

Leveraging the nugget parameter for efficient Gaussian process modeling

Gaussian process (GP) metamodels have been widely used as surrogates for computer simulations or physical experiments. The heart of GP modeling lies in optimizing the log‐likelihood function with respect to the hyperparameters to fit the model to a set of observations. The complexity of the log‐likelihood function, computational expense, and numerical instabilities challenge this process. These issues limit the applicability of GP models more when the size of the training data set and/or problem dimensionality increase. To address these issues, we develop a novel approach for fitting GP models that significantly improves computational expense and prediction accuracy. Our approach leverages the smoothing effect of the nugget parameter on the log‐likelihood profile to track the evolution of the optimal hyperparameter estimates as the nugget parameter is adaptively varied. The new approach is implemented in the R package GPM and compared to a popular GP modeling R package ( GPfit) for a set of benchmark problems. The effectiveness of the approach is also demonstrated using an engineering problem to learn the constitutive law of a hyperelastic composite where the required level of accuracy in estimating the response gradient necessitates a large training data set.