Sharif Digital Repository

Nowadays MapReduce and its open source implementation, Apache Hadoop, are the most widespread solutions for handling massive dataset on clusters of commodity hardware. At the expense of a somewhat reduced performance in comparison to HPC technologies, the MapReduce framework provides fault tolerance and automatic parallelization without any efforts by developers. Since in many cases Hadoop is adopted to support business critical activities, it is often important to predict with fair confidence the execution time of submitted jobs, for instance when SLAs are established with end-users. In this work, we propose and validate a hybrid approach exploiting both queuing networks and support vector... 

Nowadays, analyzing large amount of data is of paramount importance for many companies. Big data and business intelligence applications are facilitated by the MapReduce programming model while, at infrastructural layer, cloud computing provides flexible and cost effective solutions for allocating on demand large clusters. Capacity allocation in such systems is a key challenge to providing performance for MapReduce jobs and minimize cloud resource cost. The contribution of this paper is twofold: (i) we formulate a linear programming model able to minimize cloud resources cost and job rejection penalties for the execution of jobs of multiple classes with (soft) deadline guarantees, (ii) we... 

In this paper, Stochastic Activity Networks (SANs) are used to model and evaluate the performance and power consumption of an Infrastructure-as-a-Service (IaaS) cloud. The proposed SAN model is scalable and flexible, yet encompasses some details of an IaaS cloud, such as Virtual Machine (VM) provisioning, VM multiplexing, and failure/repair behavior of VMs. Using the proposed SAN, a power-aware self-adaptive resource management scheme is presented for IaaS clouds that automatically adjusts the number of powered-on Physical Machines (PMs) regarding variable workloads in different time intervals. The proposed scheme respects user-oriented metrics by avoiding Service Level Agreement (SLA)... 

Infrastructure as a Service (IaaS) is one of the most significant and fastest growing fields in cloud computing. To efficiently use the resources of an IaaS cloud, several important factors such as performance, availability, and power consumption need to be considered and evaluated carefully. Evaluation of these metrics is essential for cost-benefit prediction and quantification of different strategies which can be applied to cloud management. In this paper, analytical models based on Stochastic Reward Nets (SRNs) are proposed to model and evaluate an IaaS cloud system at different levels. To achieve this, an SRN is initially presented to model a group of physical machines which are... 

Infrastructure as a Service (IaaS) is one of the most significant and fastest growing fields in cloud computing. To efficiently use the resources of an IaaS cloud, several important factors such as performance, availability, and power consumption need to be considered and evaluated carefully. Evaluation of these metrics is essential for cost-benefit prediction and quantification of different strategies which can be applied to cloud management. In this paper, analytical models based on Stochastic Reward Nets (SRNs) are proposed to model and evaluate an IaaS cloud system at different levels. To achieve this, an SRN is initially presented to model a group of physical machines which are... 

Companies depend on mining data to grow their business more than ever. To achieve optimal performance of Big Data analytics workloads, a careful configuration of the cluster and the employed software framework is required. The lack of flexible and accurate performance models, however, render this a challenging task. This paper fills this gap by presenting accurate performance prediction models based on Stochastic Activity Networks (SANs). In contrast to existing work, the presented models consider multiple work queues, a critical feature to achieve high accuracy in realistic usage scenarios. We first introduce a monolithic analytical model for a multi-queue YARN cluster running DAG-based Big... 

Nowadays, many enterprises commit to the extraction of actionable knowledge from huge datasets as part of their core business activities. Applications belong to very different domains such as fraud detection or one-to-one marketing, and encompass business analytics and support to decision making in both private and public sectors. In these scenarios, a central place is held by the MapReduce framework and in particular its open source implementation, Apache Hadoop. In such environments, new challenges arise in the area of jobs performance prediction, with the needs to provide Service Level Agreement guarantees to the enduser and to avoid waste of computational resources. In this paper we... 

Simultaneous extraction of zinc and cadmium by a mixture of di-2-ethyl hexyl phosphoric acid (DEHPA) and mono-2-ethyl hexyl phosphoric acid (MEHPA), and the synergistic effect of MEHPA on co-extraction of zinc and cadmium with DEHPA have been investigated. It was shown that the extraction of zinc and cadmium by DEHPA and/or MEHPA can be increased by an increase of pH. The results also illustrate that the pH0.5 of zinc, by increase in MEHPA from 0.1 to 8 vol%, did not vary significantly while that of cadmium varies from 0.63 to 2.4. In other words MEHPA prevents selective extraction of zinc from aqueous media containing both zinc and cadmium. Studies on the selective separation parameter... 

The present work is concerned with the steady incompressible flow through a parallel plate channel with stretching walls under an externally applied magnetic field. The governing continuity and Navier-Stokes equations are reduced to a fourth order nonlinear differential equation by using vorticity definition and similarity solution transformation. The obtained equations are solved by applying the analytical homotopy perturbation method (HPM). The method is called order of magnitude suggested for simplifying series solution to finite expression that is useful in engineering problems. The results are verified by comparing with numerical solutions and demonstrate a good accuracy of the obtained... 

The ride comfort of high-speed trains passing over railway bridges is studied in this paper. A parametric study is carried out using a time domain model. The effects of some design parameters are investigated such as damping and stiffness of the suspension system and also ballast stiffness. The influence of the track irregularity and train speed on two comfort indicators, namely Sperling's comfort index and the maximum acceleration level are also studied. Two types of railway bridges, a simple girder and an elastically supported bridge are considered. Timoshenko beam theory is used for modelling the rail and bridge and two layers of parallel damped springs in conjunction with a layer of mass... 

At SCN 2018, Fiore and Pagnin proposed a generic compiler (called “Matrioska”) allowing to transform sufficiently expressive single-key homomorphic signatures (SKHSs) into multi-key homomorphic signatures (MKHSs) under falsifiable assumptions in the standard model. Matrioska is designed for homomorphic signatures that support programs represented as circuits. The MKHS schemes obtained through Matrioska support the evaluation and verification of arbitrary circuits over data signed from multiple users, but they require the underlying SKHS scheme to work with circuits whose size is exponential in the number of users, and thus can only support a constant number of users. In this work, we propose... 

In the last decade, many potent analytical methods have been utilized to find the approximate solution of nonlinear differential equations. Some of these methods are energy balance method (EBM), homotopy perturbation method (HPM), variational iteration method (VIM), amplitude frequency formulation (AFF), and max-min approach (MMA). Besides the methods mentioned above, the Akbari-Ganji method (AGM) is a highly efficient analytical method to solve a wide range of nonlinear equations, including heat transfer, mass transfer, and vibration problems. In this study, it was constructed the approximate analytic solution for movement of two mechanical oscillators by employing the AGM. In the derived... 

Purpose: The purpose of this paper is to investigate natural convection in a porous wavy-walled enclosure that is including a cylinder cavity in the middle of it and filled with a hybrid nanofluid contains 1-Butanol as the base fluid and MoS2–Fe3O4 hybrid nanoparticles. Design/methodology/approach: The domain of interest is bounded by constant temperature horizontal corrugated surfaces and isothermal vertical flat surfaces. The numerical outputs are explained in the type of isotherms, streamline and average Nusselt number with variations of the Rayleigh number, Hartmann number, nanoparticle shape factor and porosity of the porous medium. For solving the governing equations, the finite... 

Direct Simulation Monte Carlo (DSMC) method is applied to evaluate the performance of a new micro gas sensor (MIKRA) for mass analysis of ammonia in the rarefied gas. In order to simulate a rarefied gas inside the micro gas detector, Boltzmann equation is applied to obtain high precision results. This study performed comprehensive studies to reveal the main mechanism of force generation and applied this for the analysis of the gas mixture. Our findings show that value of generated Knudsen force significantly varies when the percentage of the NH3 varies in the mixture. According to obtained results, the maximum Knudsen force increases when the fraction of the ammonia decreases. Our findings... 

Residual stresses, created in a steel beam by elastic-plastic bending, are predicted using an approximate analysis and the finite element method. The predictions are compared to experimental measurements obtained from the application of incremental centre hole drilling, deep hole drilling and neutron diffraction methods. Finite element simulations of the incremental centre hole drilling and deep hole drilling methods applied to the predicted residual stresses permitted an assessment of their ability to reconstruct the stresses. An analytical reconstruction analysis using an Airy stress function together with boundary and equilibrium conditions is developed and applied to the predictions and... 

In this paper, Direct Simulation Monte Carlo (DSMC) simulations were applied to investigate the mechanism of the force generation inside a low-pressure gas sensor. The flow feature and force generation mechanism inside a rectangular enclosure with heat and cold arms as the non-isothermal walls are comprehensively explained. In addition, extensive parametric studies are done to study the effects of physical parameters on the performance and characteristics of this device in different operating conditions. In this research, the Knudsen number is varied from 0.1 to 4.5 (0.5 to 11torr) to reveal all the characteristics of the thermally driven force inside the MEMS sensor. In order to simulate a... 

A typical process in many industrial applications is rising bubble dynamic in viscous liquids like two-phase reactors. Examining the physical behavior of bubbles may improve the understanding of systems regarding design and operation. This study focused on the splitting of bubbles resulting from their impact on solid obstacles. Fragmentation of the bubbles appears in many applications such as lab on a chip in small scale or slug bubbly flow moving upward in a tube in large scales. Using a new index-function model in Lattice Boltzmann technique proposed by “He”, we simulated the deformation and motion of a bubble in different regimes, through which, we accurately captured a sharp interface... 

This paper deals with the mixed convective heat transfer of nanofluids through a concentric vertical annulus. Because of the non-adherence of the fluid-solid interface in the presence of nanoparticle migrations, known as slip condition, the Navier's slip boundary condition was considered at the pipe walls. The employed model for nanofluid includes the modified two-component four-equation non-homogeneous equilibrium model that fully accounts for the effects of nanoparticles volume fraction distribution. Assuming the fully developed flow and heat transfer, the basic partial differential equations including continuity, momentum, and energy equations have been reduced to two-point ordinary... 

One of the major challenges in the manufacturing parts, especially metals, is turning with good/excellent surface quality, which has a significant effect on the fatigue strength of the industrial components. Selecting incorrect or unsuitable values of machining parameters leads to vibration instability in the cutting tool and as a result, excessive roughness is created on the product’s surface. Therefore, one of the ways to reduce the roughness factor and increase the product fatigue life is to control the relative slip and vibration between the cutting tool and the workpiece. To achieve this goal, the authors attempted to investigate the simultaneous effects of tool overhang and cutting...