scholarly journals Implementation of the Digital COVID-19 Vaccination Passport based on Blockchain Protecting Privacy

2021 ◽  
Vol 25 (2) ◽  
pp. 61-76
Author(s):  
Przemysław Pukocz
Keyword(s):  
Cloud Computing ◽  
Entire Solution ◽  
Qr Code ◽  
Reference Architecture ◽  
Cloud Environment ◽  
Computing Environment ◽  
System Operation ◽  
Cloud Computing Environment ◽  
Verification Process ◽  
Privacy And Anonymity

The paper discusses proposals for implementing the COVID-19 digital Vaccination Passport based on Blockchain that protects privacy. Since the end of the last year, after the commencement of vaccination against COVID-19, there has been an intense discussion on the form of introducing such a tool and the consequences of its implementation. This discussion is taking place in many European countries. One element of this discussion was the safety and anonymity of the massively verified data of persons on vaccinations in various areas of society functioning. These issues are being resolved by the proposed digital Vaccination Passport system. This system uses two major methods: Blockchain and hash functions, which allow you to maintain security, privacy, and anonymity at the same time. To improve the intuitiveness and simplicity of the system operation, the QR code technology was proposed in the passport verification process. The system has been implemented and tested in the Amazon AWS cloud computing environment. A reference architecture based on Blockchain for the AWS environment was proposed, dedicated to large and demanding application solutions. In addition, the cloud environment offers access to many tools that were used in the system’s implementation, significantly increasing the security of the entire solution.

Workflow Scheduling for Scientific Application in Homogeneous Cloud Environment

2017 ◽  
Vol 7 (7) ◽  
pp. 137
Author(s):  
. Monika ◽  
Pardeep Kumar ◽  
Sanjay Tyagi
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Large Data ◽  
Workflow Scheduling ◽  
Cloud Environment ◽  
Computing Environment ◽  
Scientific Application ◽  
Cloud Computing Environment ◽  
Flow Of Information

In Cloud computing environment QoS i.e. Quality-of-Service and cost is the key element that to be take care of. As, today in the era of big data, the data must be handled properly while satisfying the request. In such case, while handling request of large data or for scientific applications request, flow of information must be sustained. In this paper, a brief introduction of workflow scheduling is given and also a detailed survey of various scheduling algorithms is performed using various parameter.

Impact of Cloud of Clouds in Enterprises Applications

2019 ◽  
pp. 21-33
Author(s):  
Lavanya S. ◽  
Susila N. ◽  
Venkatachalam K.
Keyword(s):  
Cloud Computing ◽  
Scheduling Algorithm ◽  
Business Environment ◽  
Cloud Environment ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Network Bandwidth ◽  
Enterprise Application ◽  
Major Disruption ◽  
Utmost Care

In recent times, the cloud has become a leading technology demanding its functionality in every business. According to research firm IDC and Gartner study, nearly one-third of the worldwide enterprise application market will be SaaS-based by 2018, driving annual SaaS revenue to $50.8 billion, from $22.6 billion in 2013. Downtime is treated as the primary drawback which may affect great deals in businesses. The service unavailability leads to a major disruption affecting the business environment. Hence, utmost care should be taken to scale the availability of services. As cloud computing has plenty of uncertainty with respect to network bandwidth and resources accessibility, delegating the computing resources as services should be scheduled accordingly. This chapter proposes a study on cloud of clouds and its impact on a business enterprise. It is also decided to propose a suitable scheduling algorithm to the cloud of cloud environment so as to trim the downtime problem faced by the cloud computing environment.

Provisioning of Virtual Machines in the Context of an Auto-Scaling Cloud Computing Environment

2020 ◽  
Vol 17 (6) ◽  
pp. 2430-2434
Author(s):  
R. S. Rajput ◽  
Dinesh Goyal ◽  
Rashid Hussain ◽  
Pratham Singh
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Resource Utilization ◽  
Virtual Machines ◽  
Cloud Environment ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Auto Scaling ◽  
Adequate Resource ◽  
Cloud Resources

The cloud computing environment is accomplishing cloud workload by distributing between several nodes or shift to the higher resource so that no computing resource will be overloaded. However, several techniques are used for the management of computing workload in the cloud environment, but still, it is an exciting domain of investigation and research. Control of the workload and scaling of cloud resources are some essential aspects of the cloud computing environment. A well-organized load balancing plan ensures adequate resource utilization. The auto-scaling is a technique to include or terminate additional computing resources based on the scaling policies without involving humans efforts. In the present paper, we developed a method for optimal use of cloud resources by the implementation of a modified auto-scaling feature. We also incorporated an auto-scaling controller for the optimal use of cloud resources.

scholarly journals Performance Evaluation of SUMEGHA Cloud Computing Environment: Methodologies & Tool

2019 ◽  
Vol 8 (12) ◽  
pp. 875-880
Keyword(s):  
Cloud Computing ◽  
Performance Evaluation ◽  
Software As A Service ◽  
Automated Testing ◽  
Cloud Environment ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Platform As A Service ◽  
Testing Tools ◽  
Manual Testing

Cloud ecosystem basically offers Platform as a Service (PaaS), Infrastructure as a Service (IaaS) and Software as a Service (SaaS). This paper describes the testing process employed for testing the C-DAC cloud SuMegha. Though new tools for the testing cloud are emerging into the market, there are aspects which are suited for manual testing and some which can be speeded up using automated testing tools. This paper brings out the techniques best suited to test different features of Cloud computing environment. It offers a comparison of several tools which enhance the testing process at each level. The authors also try to bring out (recommend) broad guidelines to follow while setting up a cloud environment to reduce the number of bugs in the system

scholarly journals A Study on Factors Contributing to Efficiency of Scheduling Algorithms in a Cloud Computing Environment; Overview of Several Algorithms

2015 ◽  
Vol 37 ◽  
pp. 427
Author(s):  
Minoo Soltanshahi ◽  
Aliakbar Niknafs
Keyword(s):  
Cloud Computing ◽  
Fault Tolerance ◽  
Efficient Algorithm ◽  
System Performance ◽  
Scheduling Algorithms ◽  
Cloud Environment ◽  
Computing Environment ◽  
Shared Resources ◽  
Cloud Computing Environment ◽  
Tremendous Impact

Cloud computing is the latest distributed technology providing a rich environment of dynamically shared resources through virtualization, which can fulfill the requirements of users by allocating resources to programs. Any program in a cloud environment is delivered by workflows which are a series of interlinked tasks to accomplish a goal. One of the most important tasks in cloud computing is correct mapping of tasks onto resources. It is essential to schedule processes in distributed systems such as cloud, since it leaves a tremendous impact on the system performance. This is done by scheduling algorithms. Therefore, it is crucial to present and adopt an efficient algorithm in the cloud environment. This article attempted to examine the parameters effective in the efficiency of scheduling algorithms including deadline, cost constraint, balanced loading, power consumption and fault tolerance. Additionally, the performances of several algorithms were briefly discussed.

scholarly journals Testing Methodologies for Cloud Performance

2019 ◽  
Vol 8 (12) ◽  
pp. 2586-2592
Keyword(s):  
Cloud Computing ◽  
Performance Testing ◽  
Automatic Testing ◽  
Software As A Service ◽  
Cloud Environment ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Platform As A Service ◽  
Testing Tools ◽  
Manual Testing

Cloud environment basically offers Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS). Here we describe the testing process employed for performance testing. Though new tools for testing cloud are emerging into the market, there are aspects which are suited for manual testing and some which can be speeded up using automatic testing tools. This paper brings out the techniques best suited to test different features of Cloud computing environment. The authors also try to bring out (recommend) broad guidelines to follow while setting up a cloud environment to reduce the number of bugs in the system.

scholarly journals Task scheduling algorithm based on multi criteria decision making method for cloud computing environment: TSABMCDMCCE

2019 ◽  
Vol 9 (1) ◽  
pp. 279-291 ◽  
Author(s):  
Proshikshya Mukherjee ◽  
Prasant Kumar Pattnaik ◽  
Tanmaya Swain ◽  
Amlan Datta
Keyword(s):  
Decision Making ◽  
Cloud Computing ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Multi Criteria Decision Making ◽  
Cloud Environment ◽  
Computing Environment ◽  
Queuing Model ◽  
Cloud Computing Environment ◽  
Task Scheduling Algorithm

AbstractThis Paper focuses on multi-criteria decision making techniques (MCDMs), especially analytical networking process (ANP) algorithm to design a model in order to minimize the task scheduling cost during implementation using a queuing model in a cloud environment and also deals with minimization of the waiting time of the task. The simulated results of the algorithm give better outcomes as compared to other existing algorithms by 15 percent.

Migration issues of SCADA systems to the cloud computing environment (review)

2020 ◽  
pp. 155-164
Author(s):  
R.G. Alakbarov ◽  
◽  
M.A. Hashimov ◽  
Keyword(s):  
Cloud Computing ◽  
Supervisory Control ◽  
Lower Cost ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Cloud Environment ◽  
Computing Environment ◽  
Gas Industry ◽  
Cloud Computing Environment ◽  
Scada Systems

The paper deals with the migration of SCADA (Supervisory Control and Data Acquisition) systems widely used in the monitoring and management of the oil and gas industry to the cloud computing environment. There arise various problems in data collection, transmission, and processing because of traditional SCADA systems being very expensive, inflexible, and complicated scalability. The transferring of the SCADA system's applications to the cloud environment reduces costs and improves scalability. The purchase of hardware and software is carried out at a lower cost than its installation and maintenance. In the article, the usage of cloud-based SCADA systems has been proposed for easy, safe, reliable and quick collection and processing of data from facilities installed in the oil and gas industry.

scholarly journals Data Service Trust Measurement in Cloud Environment

2019 ◽  
Author(s):  
Lin Shi ◽  
Zilong Wang ◽  
Ning Chen ◽  
Jie Chen
Keyword(s):  
Cloud Computing ◽  
Web Application ◽  
Virtual Machines ◽  
Management Service ◽  
Cloud Environment ◽  
Computing Environment ◽  
Optimization Scheme ◽  
Processing Scheme ◽  
Cloud Computing Environment ◽  
Cloud Data

Abstract Highly trusted issues will be one of the main obstacles to a new era of highly trusted cloud computing. In the cloud computing environment, because sensitive applications and user data are put into the cloud, they run in virtual machines in the data center. Among them, due to the existence of access vulnerability, virtualization vulnerability, web application vulnerability, etc., high trust issues arise from data control, identity authentication, lack of information and other related issues. The introduction of trust mechanisms can be very facilitate the solution of related issues, achieve highly trusted quantification, analysis, and modeling of cloud data centers, meet high trust requirements, and provide users with a highly trusted cloud computing environment. This article mainly studies the trust measure of data services in cloud environment. In this paper, the optimization scheme is verified through experiments, and the traditional big data processing scheme, the original Sahara and the optimization scheme are compared in six cases. Overall, the optimization scheme has a significant performance improvement. Compared with the default configuration of Sahara, the configuration of the new interface has increased the throughput in DFSIO by 120%. Using the design of the unified cache management service, Tachyon can reach 13 in specific situations. In the execution time of Sort workloads, the optimization scheme generally decreased by about 50% compared to the original Sahara, and the memory utilization increased from 80% to 96% in our experiments, but in the cache isolation and other areas need to be improved. The results are basically in line with expectations, which also confirms the rational thinking and value of this article on BDAaS performance research.

scholarly journals THE FEASIBILITY STUDY OF RUNNING HPC WORKLOADS ON COMPUTATIONAL CLOUDS

2017 ◽  
Vol 10 (13) ◽  
pp. 445
Author(s):  
Purvi Pathak ◽  
Kumar R
Keyword(s):  
Cloud Computing ◽  
Parallel Computing ◽  
High Performance ◽  
Cloud Environment ◽  
Computing Environment ◽  
Private Cloud ◽  
Computing Systems ◽  
Cloud Computing Environment ◽  
Pros And Cons ◽  
Performance Computing

High-performance computing (HPC) applications require high-end computing systems, but not all scientists have access to such powerful systems. Cloud computing provides an opportunity to run these applications on the cloud without the requirement of investing in high-end parallel computing systems. We can analyze the performance of the HPC applications on private as well as public clouds. The performance of the workload on the cloud can be calculated using different benchmarking tools such as NAS parallel benchmarking and Rally. The workloads of HPC applications require use of many parallel computing systems to be run on a physical setup, but this facility is available on cloud computing environment without the need of investing in physical machines. We aim to analyze the ability of the cloud to perform well when running HPC workloads. We shall get the detailed performance of the cloud when running these applications on a private cloud and find the pros and cons of running HPC workloads on cloud environment.

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