scholarly journals Dynamic Performance Optimization for Cloud Computing Using M/M/m Queueing System

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Lizheng Guo ◽  
Tao Yan ◽  
Shuguang Zhao ◽  
Changyuan Jiang
Keyword(s):  
Cloud Computing ◽  
Performance Optimization ◽  
Queueing System ◽  
Dynamic Performance ◽  
Wait Time ◽  
Optimization Methods ◽  
Proposed Model ◽  
Set Up ◽  
Qos Performance ◽  
The Cost

Successful development of cloud computing has attracted more and more people and enterprises to use it. On one hand, using cloud computing reduces the cost; on the other hand, using cloud computing improves the efficiency. As the users are largely concerned about the Quality of Services (QoS), performance optimization of the cloud computing has become critical to its successful application. In order to optimize the performance of multiple requesters and services in cloud computing, by means of queueing theory, we analyze and conduct the equation of each parameter of the services in the data center. Then, through analyzing the performance parameters of the queueing system, we propose the synthesis optimization mode, function, and strategy. Lastly, we set up the simulation based on the synthesis optimization mode; we also compare and analyze the simulation results to the classical optimization methods (short service time first and first in, first out method), which show that the proposed model can optimize the average wait time, average queue length, and the number of customer.

Design and Realization Based on Cloud Stack Hybrid Cloud Computing Platform

2014 ◽  
Vol 989-994 ◽  
pp. 2297-2300
Author(s):  
Peng Cheng ◽  
Hui Qu
Keyword(s):  
Cloud Computing ◽  
Hybrid Cloud ◽  
Cloud Platform ◽  
Computing Platform ◽  
Resource Classification ◽  
Virtualization Technology ◽  
Cloud Computing Platform ◽  
Low Efficiency ◽  
Set Up ◽  
The Cost

While setting up the cloud computing platform by using OpenStack, there were some disadvantages such as very tedious operating steps and low efficiency. In this paper, we put forward a design and realization method based on CloudStack hybrid cloud computing platform. Firstly, we used CloudStack as tool to set up two independent cloud platforms, one of them was called public cloud and the other one private cloud. Then virtualization technology and a shared resource classification method discussed in this paper were performed to set up two virtual sub-servers on the main server and operate the cloud platform already established on it. Finally, we gave the two platforms corresponding authority, thus the hybrid cloud platform was established. This method was easy to set up and could reduce the cost effectively, therefore, it was very practical.

Self adaptive fruit fly algorithm for multiple workflow scheduling in cloud computing environment

Kybernetes ◽  
2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ambika Aggarwal ◽  
Priti Dimri ◽  
Amit Agarwal ◽  
Ashutosh Bhatt
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Fruit Fly ◽  
Flow Time ◽  
Workflow Scheduling ◽  
Content Type ◽  
Proposed Model ◽  
Conventional Methods ◽  
The Cost ◽  
Better Than

Purpose In general, cloud computing is a model of on-demand business computing that grants a convenient access to shared configurable resources on the internet. With the increment of workload and difficulty of tasks that are submitted by cloud consumers; “how to complete these tasks effectively and rapidly with limited cloud resources?” is becoming a challenging question. The major point of a task scheduling approach is to identify a trade-off among user needs and resource utilization. However, tasks that are submitted by varied users might have diverse needs of computing time, memory space, data traffic, response time, etc. This paper aims to proposes a new way of task scheduling. Design/methodology/approach To make the workflow completion in an efficient way and to reduce the cost and flow time, this paper proposes a new way of task scheduling. Here, a self-adaptive fruit fly optimization algorithm (SA-FFOA) is used for scheduling the workflow. The proposed multiple workflow scheduling model compares its efficiency over conventional methods in terms of analysis such as performance analysis, convergence analysis and statistical analysis. From the outcome of the analysis, the betterment of the proposed approach is proven with effective workflow scheduling. Findings The proposed algorithm is more superior regarding flow time with the minimum value, and the proposed model is enhanced over FFOA by 0.23%, differential evolution by 2.48%, artificial bee colony (ABC) by 2.85%, particle swarm optimization (PSO) by 2.46%, genetic algorithm (GA) by 2.33% and expected time to compute (ETC) by 2.56%. While analyzing the make span case, the proposed algorithm is 0.28%, 0.15%, 0.38%, 0.20%, 0.21% and 0.29% better than the conventional methods such as FFOA, DE, ABC, PSO, GA and ETC, respectively. Moreover, the proposed model has attained less cost, which is 2.14% better than FFOA, 2.32% better than DE, 3.53% better than ABC, 2.43% better than PSO, 2.07% better than GA and 2.90% better than ETC, respectively. Originality/value This paper presents a new way of task scheduling for making the workflow completion in an efficient way and for reducing the cost and flow time. This is the first paper uses SA-FFOA for scheduling the workflow.

scholarly journals A Novel Cost Based Model for Energy Consumption in Cloud Computing

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
A. Horri ◽  
Gh. Dastghaibyfard
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Electrical Energy ◽  
Cloud Environment ◽  
Cloud Infrastructure ◽  
Cloud Data ◽  
Proposed Model ◽  
Energy Consumption Model ◽  
Cloud Data Centers ◽  
The Cost

Cloud data centers consume enormous amounts of electrical energy. To support green cloud computing, providers also need to minimize cloud infrastructure energy consumption while conducting the QoS. In this study, for cloud environments an energy consumption model is proposed for time-shared policy in virtualization layer. The cost and energy usage of time-shared policy were modeled in the CloudSim simulator based upon the results obtained from the real system and then proposed model was evaluated by different scenarios. In the proposed model, the cache interference costs were considered. These costs were based upon the size of data. The proposed model was implemented in the CloudSim simulator and the related simulation results indicate that the energy consumption may be considerable and that it can vary with different parameters such as the quantum parameter, data size, and the number of VMs on a host. Measured results validate the model and demonstrate that there is a tradeoff between energy consumption and QoS in the cloud environment. Also, measured results validate the model and demonstrate that there is a tradeoff between energy consumption and QoS in the cloud environment.

scholarly journals Heuristic and Meta-Heuristic Optimization Models for Task Scheduling in Cloud-Fog Systems: A Review

2020 ◽  
Vol 16 (2) ◽  
pp. 103-112
Author(s):  
Mohammed Abdulredha ◽  
Bara'a Attea ◽  
Adnan Jabir
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Optimization Methods ◽  
Time Frame ◽  
Resource Provisioning ◽  
Clear Vision ◽  
Np Hard Problem ◽  
The Cost ◽  
Cloud Users ◽  
Workflow Tasks

Nowadays, cloud computing has attracted the attention of large companies due to its high potential, flexibility, and profitability in providing multi-sources of hardware and software to serve the connected users. Given the scale of modern data centers and the dynamic nature of their resource provisioning, we need effective scheduling techniques to manage these resources while satisfying both the cloud providers and cloud users goals. Task scheduling in cloud computing is considered as NP-hard problem which cannot be easily solved by classical optimization methods. Thus, both heuristic and meta-heuristic techniques have been utilized to provide optimal or near-optimal solutions within an acceptable time frame for such problems. In this article, a summary of heuristic and meta-heuristic methods for solving the task scheduling optimization in cloud-fog systems is presented. The cost and time aware scheduling methods for both bag of tasks and workflow tasks are reviewed, discussed, and analyzed thoroughly to provide a clear vision for the readers in order to select the proper methods which fulfill their needs.

A Circular Business Model for Cloud Computing Services Providers

10.31355/33 ◽  
2018 ◽  
Vol 2 ◽  
pp. 105-120
Author(s):  
Hamed Motaghi ◽  
Saeed Nosratabadi ◽  
Thabit Qasem Atobishi
Keyword(s):  
Cloud Computing ◽  
Business Model ◽  
Circular Economy ◽  
Service Providers ◽  
Sustainable Consumption ◽  
Future Research ◽  
Extensive Literature ◽  
Computing Services ◽  
Proposed Model ◽  
Cloud Computing Service

NOTE: THIS ARTICLE WAS PUBLISHED WITH THE INFORMING SCIENCE INSTITUTE. Aim/Purpose................................................................................................................................................................................................. The main objective of the current study is to develop a business model for service providers of cloud computing which is designed based on circular economy principles and can ensure the sustainable consumption. Background Even though the demand for cloud computing technology is increasing day by day in all over the world, the current the linear economy principles are incapable to ensure society development needs. To consider the benefit of the society and the vendors at the same time, the principles of circular economy can address this issue. Methodology................................................................................................................................................................................................. An extensive literature review on consumption, sustainable consumption, circular economic, business model, and cloud computing were conducted. the proposed model of Osterwalder, Pigneur and Tucci (2005) is admitted designing the circular business model. Contribution................................................................................................................................................................................................. The proposed model of the study is the contribution of this study where provides the guidelines for the cloud computing service providers to achieve both their economic profits and the society’ needs. Findings Finding reveals that if the cloud computing service providers design their business model based on the “access” principle of circular economy, they can meet their economic profits and the society’ needs at a same time. Recommendations for Practitioners.............................................................................................................................................................. It is recommended to the startup and the existing businesses to utilize the proposed model of this study to reach a sustainable development. Recommendation for Researchers................................................................................................................................................................ It proposes a new circular business model and its linkages with community building. Impact on Society............................................................................................................................................................................................ The proposed model of the study provides guidelines to the cloud computing service providers to design a business model which is able not only to meet their economic profit, but also to meet the society’s and customers’ benefits. Future Research............................................................................................................................................................................................... Future researches can build on this research model which proposed in this study to examine the limitations of this model by using empirical researches.

ON COMPARATIVE ANALYSIS OF PERFORMANCE OPTIMIZATION METHODS OF MULTI-PUMP UNITS

2020 ◽  
pp. 23-28
Author(s):  
A.I. Glushchenko ◽  
M.Yu. Serov
Keyword(s):  
Energy Efficiency ◽  
Control System ◽  
Comparative Analysis ◽  
Performance Optimization ◽  
Optimization Methods ◽  
Online Optimization ◽  
New Approach ◽  
Advantages And Disadvantages ◽  
Analysis Of Performance

В статье рассматривается вопрос совершенствования системы управления параллельно-работающими насосными агрегатами с целью повышения энергоэффективности их работы. Проведено сравнение и выявление недостатков существующих методов решения рассматриваемой проблемы. Предложена идея нового подхода на базе онлайн оптимизации. The problem under consideration is improvement of the energy efficiency of a control system of parallel-running pump units. Known methods used to solve this problem are considered. Their advantages and disadvantages are shown. Finally, the idea of a new approach, which is based on online optimization, is proposed.

Structure Sensitivity Analysis and Dynamic Performance Optimization of Marine Gearbox

2017 ◽  
Author(s):  
Tengjiao Lin ◽  
Daokun Xie ◽  
Ziran Tan ◽  
Bo Liu
Keyword(s):  
Sensitivity Analysis ◽  
Performance Optimization ◽  
Optimization Design ◽  
Dynamic Performance ◽  
Structure Sensitivity ◽  
Superposition Method ◽  
Structure Parameters ◽  
Analysis Model ◽  
Vibration Acceleration ◽  
Response Optimization

The aim of this paper is to investigate the influence of structure parameters on the vibration characteristics and improve the dynamic performance of marine gearbox. A finite element model was established to solve the dynamic response by using modal superposition method. Based on the theory of multi-objective optimization design, the structure sensitivity analysis model of marine gearbox was established, which takes the structure parameters of the housing as design variables. The modal and response sensitivity was obtained by using the optimal gradient method. According to the results of sensitivity analysis, a modal and response optimization model of marine gearbox was established. The objective was to avoid natural frequencies from the excitation frequencies and minimize the root mean square of vibration acceleration of the evaluating points on the surface of housing. Then the modal optimization and response optimization of gearbox were carried out by using zero-order and first-order optimization method. The results indicate that the dynamic optimization of the gearbox can be achieved. After optimization, the amplitude of vibration acceleration of the evaluating points on the housing surface has been reduced and the resonance of marine gearbox can be avoided.

scholarly journals Prediction of Pest Insect Appearance Using Sensors and Machine Learning

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4846
Author(s):  
Dušan Marković ◽  
Dejan Vujičić ◽  
Snežana Tanasković ◽  
Borislav Đorđević ◽  
Siniša Ranđić ◽  
...  
Keyword(s):  
Machine Learning ◽  
Relative Humidity ◽  
Weather Conditions ◽  
Daily Basis ◽  
Machine Learning Algorithms ◽  
Lower Percentage ◽  
Timely Manner ◽  
Proposed Model ◽  
Set Up ◽  
Accuracy Of Prediction

The appearance of pest insects can lead to a loss in yield if farmers do not respond in a timely manner to suppress their spread. Occurrences and numbers of insects can be monitored through insect traps, which include their permanent touring and checking of their condition. Another more efficient way is to set up sensor devices with a camera at the traps that will photograph the traps and forward the images to the Internet, where the pest insect’s appearance will be predicted by image analysis. Weather conditions, temperature and relative humidity are the parameters that affect the appearance of some pests, such as Helicoverpa armigera. This paper presents a model of machine learning that can predict the appearance of insects during a season on a daily basis, taking into account the air temperature and relative humidity. Several machine learning algorithms for classification were applied and their accuracy for the prediction of insect occurrence was presented (up to 76.5%). Since the data used for testing were given in chronological order according to the days when the measurement was performed, the existing model was expanded to take into account the periods of three and five days. The extended method showed better accuracy of prediction and a lower percentage of false detections. In the case of a period of five days, the accuracy of the affected detections was 86.3%, while the percentage of false detections was 11%. The proposed model of machine learning can help farmers to detect the occurrence of pests and save the time and resources needed to check the fields.

Establishment and comparison of a spatial dynamics model for virtual track train with different steering modes

2021 ◽  
pp. 146441932110240
Author(s):  
Zhonghui Yin ◽  
Jiye Zhang ◽  
Haiying Lu
Keyword(s):  
Pid Controller ◽  
Dynamic Performance ◽  
Spatial Dynamics ◽  
Steering System ◽  
Front Wheel ◽  
Proportional Integral Derivative ◽  
Dynamics Model ◽  
Proposed Model ◽  
Suspension Control ◽  
Curved Section

To solve the urbanization and the economic challenges, a virtual track train (VTT) transportation system has been proposed in China. To evaluate the dynamic behavior of the VTT, a spatial dynamics model has been developed that considers the suspension system and the steering system. Additionally, the model takes into account road irregularity to make simulations more realistic. Based on the newly proposed dynamic model and a designed proportional–integral–derivative (PID) controller, simulation frames of the vehicle and of the VTT are established with the path-tracking performance. The results show that the vehicle and the VTT can run along a desired lane with allowable errors, verifying the proposed model. The vehicle and VTT with the four-wheel steering system show a better dynamic performance than the models with the front-wheel steering system in the curved section. Moreover, the simulation frame can be further applied to dynamics-related assessments, parameter optimization and active suspension control strategy.

Wave propagation improvement in two-dimensional bond-based peridynamics model

2021 ◽  
pp. 095440622098555
Author(s):  
Reza Alebrahim ◽  
Pawel Packo ◽  
Mirco Zaccariotto ◽  
Ugo Galvanetto
Keyword(s):  
Wave Propagation ◽  
Dynamic Performance ◽  
Numerical Dispersion ◽  
Motion Modeling ◽  
Minimization Method ◽  
Irregular Wave ◽  
Point Collocation ◽  
Potential Applications ◽  
Non Local ◽  
Set Up

In this study, methods to mitigate anomalous wave propagation in 2-D Bond-Based Peridynamics (PD) are presented. Similarly to what happens in classical non-local models, an irregular wave transmission phenomenon occurs at high frequencies. This feature of the dynamic performance of PD, limits its potential applications. A minimization method based on the weighted residual point collocation is introduced to substantially extend the frequency range of wave motion modeling. The optimization problem, developed through inverse analysis, is set up by comparing exact and numerical dispersion curves and minimizing the error in the frequency-wavenumber domain. A significant improvement in the wave propagation simulation using Bond-Based PD is observed.

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