scholarly journals Distribution of the Emergency Supplies in the COVID-19 Pandemic: A Cloud Computing Based Approach

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Jixiao Wu ◽  
Yinghui Wang
Keyword(s):  
Genetic Algorithm ◽  
Sensitivity Analysis ◽  
Cloud Computing ◽  
Nonprofit Organizations ◽  
Optimal Distribution ◽  
Cloud Platform ◽  
Transport Efficiency ◽  
Transportation Time ◽  
Emergency Logistics ◽  
Integrated Cost

The containment of the COVID-19 pandemic was significantly affected by the unbalanced distribution of emergency supplies, low coordinated transport efficiency, high costs, and the inability of nonprofit organizations to handle the emergency supplies efficiently. Based on the COVID-19 experience, in this paper, we build a cloud platform for emergency supplies distribution to reduce the asymmetry of emergency logistics information, reduce the costs, and improve the efficiency of emergency supplies distribution. Our proposed method uses a genetic algorithm with the monarch scheme to optimize the urban emergency supplies distribution. The numerical results and sensitivity analysis for a sample network indicate that using the proposed platform the integrated cost in different cities are reduced by 29.01%, 28.67%, and 22.73%, the required time in different cities are reduced by 22.98%, 26.59%, and 36.65%. The results suggest that the proposed method reduces the integrated cost and transportation time and finds the optimal distribution path.

ATTITUDE OF LIBRARY PROFESSIONALS TOWARDS ADOPTION OF CLOUD COMPUTING TECHNOLOGY IN VTU AFFILIATED ENGINEERING COLLEGES LIBRARIES

2019 ◽  
pp. 1-4
Author(s):  
C. T. Kantharaja
Keyword(s):  
Cloud Computing ◽  
Academic Libraries ◽  
Technical Skills ◽  
Library Services ◽  
Cloud Platform ◽  
Computing Technology ◽  
Management Software ◽  
Library Management ◽  
The Right ◽  
Library Professionals

Cloud computing technology has signicant role in academic libraries. Most of the library services are available on cloud platform and library software vendors developed their Library Management Software on cloud platform. It is the right time for library professionals to upgrade their technical skills to provide good services to the library stakeholders. This study shows the library services and facilities available on cloud. It is the right time to migrate to cloud

The Research of Measuring Approach and Energy Efficiency for Hadoop Periodic Jobs

2015 ◽  
Vol 8 (1) ◽  
pp. 206-210 ◽  
Author(s):  
Yu Junyang ◽  
Hu Zhigang ◽  
Han Yuanyuan
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Energy Saving ◽  
Energy Estimate ◽  
Cloud Platform ◽  
Periodic Tasks ◽  
Current Consumption ◽  
Reduce Energy Consumption

Current consumption of cloud computing has attracted more and more attention of scholars. The research on Hadoop as a cloud platform and its energy consumption has also received considerable attention from scholars. This paper presents a method to measure the energy consumption of jobs that run on Hadoop, and this method is used to measure the effectiveness of the implementation of periodic tasks on the platform of Hadoop. Combining with the current mainstream of energy estimate formula to conduct further analysis, this paper has reached a conclusion as how to reduce energy consumption of Hadoop by adjusting the split size or using appropriate size of workers (servers). Finally, experiments show the effectiveness of these methods as being energy-saving strategies and verify the feasibility of the methods for the measurement of periodic tasks at the same time.

Task scheduling algorithm based on improved genetic algorithm in cloud computing environment

2020 ◽  
Vol 13 ◽  
Author(s):  
Ge Weiqing ◽  
Cui Yanru
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Task Completion ◽  
Improved Genetic Algorithm ◽  
Fitness Functions ◽  
Task Scheduling Algorithm ◽  
Simulation Results

Background: In order to make up for the shortcomings of the traditional algorithm, Min-Min and Max-Min algorithm are combined on the basis of the traditional genetic algorithm. Methods: In this paper, a new cloud computing task scheduling algorithm is proposed, which introduces Min-Min and Max-Min algorithm to generate initialization population, and selects task completion time and load balancing as double fitness functions, which improves the quality of initialization population, algorithm search ability and convergence speed. Results: The simulation results show that the algorithm is superior to the traditional genetic algorithm and is an effective cloud computing task scheduling algorithm. Conclusion: Finally, this paper proposes the possibility of the fusion of the two quadratively improved algorithms and completes the preliminary fusion of the algorithm, but the simulation results of the new algorithm are not ideal and need to be further studied.

Optimal machine placement based on improved genetic algorithm in cloud computing

2021 ◽  
Author(s):  
Jiawei Lu ◽  
Wei Zhao ◽  
Haotian Zhu ◽  
Jie Li ◽  
Zhenbo Cheng ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Improved Genetic Algorithm ◽  
Optimal Machine

scholarly journals Redundant VoD Streaming Service in a Private Cloud: Availability Modeling and Sensitivity Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Rosangela Maria De Melo ◽  
Maria Clara Bezerra ◽  
Jamilson Dantas ◽  
Rubens Matos ◽  
Ivanildo José De Melo Filho ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Cloud Computing ◽  
Hierarchical Modeling ◽  
Video On Demand ◽  
Differential Sensitivity ◽  
Private Cloud ◽  
Streaming Service ◽  
Critical Components ◽  
Modeling Strategy ◽  
Vod Streaming

For several years cloud computing has been generating considerable debate and interest within IT corporations. Since cloud computing environments provide storage and processing systems that are adaptable, efficient, and straightforward, thereby enabling rapid infrastructure modifications to be made according to constantly varying workloads, organizations of every size and type are migrating to web-based cloud supported solutions. Due to the advantages of the pay-per-use model and scalability factors, current video on demand (VoD) streaming services rely heavily on cloud infrastructures to offer a large variety of multimedia content. Recent well documented failure events in commercial VoD services have demonstrated the fundamental importance of maintaining high availability in cloud computing infrastructures, and hierarchical modeling has proved to be a useful tool for evaluating the availability of complex systems and services. This paper presents an availability model for a video streaming service deployed in a private cloud environment which includes redundancy mechanisms in the infrastructure. Differential sensitivity analysis was applied to identify and rank the critical components of the system with respect to service availability. The results demonstrate that such a modeling strategy combined with differential sensitivity analysis can be an attractive methodology for identifying which components should be supported with redundancy in order to consciously increase system dependability.

Pyramid: A Case Study of Cyber Security in India

2015 ◽  
Vol 4 (1) ◽  
pp. 135-142 ◽  
Author(s):  
Nimisha Singh ◽  
Abha Rishi
Keyword(s):  
Cloud Computing ◽  
Law Enforcement ◽  
Cyber Security ◽  
Cloud Platform ◽  
The Public ◽  
Security Breaches ◽  
Digital Network ◽  
Digital Crime ◽  
A Company

As the world becomes increasingly interlinked through the Internet, cyberspace frauds are also on the rise. This is a case study on a company, Pyramid Cyber Security (P) Ltd., which specializes in digital crime, fraud and forensic solutions and services in India. Over the years, the company has established several digital forensics laboratories and security projects for agencies in law enforcement, the public sector and corporate organizations. With the scalability, flexibility and economic advantage offered by cloud computing, more and more organizations are moving towards cloud for their applications. With all the benefits of cloud computing, it also opens up a company to the danger of digital crime and security breaches on the cloud platform. This has thrown open new vistas for Pyramid, putting it in a dilemma of whether to focus on the existing business or explore new opportunities in cloud forensics investigation thrown by the wide acceptance of cloud computing. It also poses the question whether a company should go in for pre-incident or post-incident digital network security architecture. It is a teaching case.

Numerical Simulation of Gas Lift Optimization Using Artificial Intelligence for a Middle Eastern Oil Field

2021 ◽  
Author(s):  
Mohammed Ahmed Al-Janabi ◽  
Omar F. Al-Fatlawi ◽  
Dhifaf J. Sadiq ◽  
Haider Abdulmuhsin Mahmood ◽  
Mustafa Alaulddin Al-Juboori
Keyword(s):  
Genetic Algorithm ◽  
Sensitivity Analysis ◽  
Middle Eastern ◽  
Optimization Technique ◽  
Injection Rate ◽  
Oil Field ◽  
Oil Fields ◽  
Reservoir Pressure ◽  
Artificial Lift ◽  
Gas Lift

Abstract Artificial lift techniques are a highly effective solution to aid the deterioration of the production especially for mature oil fields, gas lift is one of the oldest and most applied artificial lift methods especially for large oil fields, the gas that is required for injection is quite scarce and expensive resource, optimally allocating the injection rate in each well is a high importance task and not easily applicable. Conventional methods faced some major problems in solving this problem in a network with large number of wells, multi-constrains, multi-objectives, and limited amount of gas. This paper focuses on utilizing the Genetic Algorithm (GA) as a gas lift optimization algorithm to tackle the challenging task of optimally allocating the gas lift injection rate through numerical modeling and simulation studies to maximize the oil production of a Middle Eastern oil field with 20 production wells with limited amount of gas to be injected. The key objective of this study is to assess the performance of the wells of the field after applying gas lift as an artificial lift method and applying the genetic algorithm as an optimization algorithm while comparing the results of the network to the case of artificially lifted wells by utilizing ESP pumps to the network and to have a more accurate view on the practicability of applying the gas lift optimization technique. The comparison is based on different measures and sensitivity studies, reservoir pressure, and water cut sensitivity analysis are applied to allow the assessment of the performance of the wells in the network throughout the life of the field. To have a full and insight view an economic study and comparison was applied in this study to estimate the benefits of applying the gas lift method and the GA optimization technique while comparing the results to the case of the ESP pumps and the case of naturally flowing wells. The gas lift technique proved to have the ability to enhance the production of the oil field and the optimization process showed quite an enhancement in the task of maximizing the oil production rate while using the same amount of gas to be injected in the each well, the sensitivity analysis showed that the gas lift method is comparable to the other artificial lift method and it have an upper hand in handling the reservoir pressure reduction, and economically CAPEX of the gas lift were calculated to be able to assess the time to reach a profitable income by comparing the results of OPEX of gas lift the technique showed a profitable income higher than the cases of naturally flowing wells and the ESP pumps lifted wells. Additionally, the paper illustrated the genetic algorithm (GA) optimization model in a way that allowed it to be followed as a guide for the task of optimizing the gas injection rate for a network with a large number of wells and limited amount of gas to be injected.

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