CSCLab

2019 ◽  
pp. 532-552
Author(s):  
Paula Prata ◽  
Samuel Alves
Keyword(s):  
Virtual Machines ◽  
Cloud Infrastructure ◽  
Virtual Computing ◽  
The Creation ◽  
Cloud Resources

This paper presents a platform to create and manage virtual computing laboratories using Cloud resources. Using this platform a professor can create a customized laboratory according to the class needs. The laboratory is composed of a set of virtual machines that students may use to get access to the necessary computing resources to attend the class. The platform aims at the creation of a solution to avoid proprietary lock in's, and it was designed to be agnostic to the cloud infrastructure. The machines of the lab can be accessed using some remote desktop protocol and managed by non-expert users.

CSCLab

2015 ◽  
Vol 5 (4) ◽  
pp. 36-55
Author(s):  
Paula Prata ◽  
Samuel Alves
Keyword(s):  
Virtual Machines ◽  
Cloud Infrastructure ◽  
Virtual Computing ◽  
The Creation ◽  
Cloud Resources

This paper presents a platform to create and manage virtual computing laboratories using Cloud resources. Using this platform a professor can create a customized laboratory according to the class needs. The laboratory is composed of a set of virtual machines that students may use to get access to the necessary computing resources to attend the class. The platform aims at the creation of a solution to avoid proprietary lock in's, and it was designed to be agnostic to the cloud infrastructure. The machines of the lab can be accessed using some remote desktop protocol and managed by non-experts users.

scholarly journals Processing streams in a monitoring cloud cluster

2020 ◽  
Vol 7 (6) ◽  
pp. 56-67 ◽  
Author(s):  
Alexey N. Nazarov
Keyword(s):  
Cloud Computing ◽  
Parallel Processing ◽  
High Speed ◽  
Virtual Machines ◽  
Streaming Data ◽  
Bit Rate ◽  
Cloud Infrastructure ◽  
International Telecommunication Union ◽  
Cloud Cluster ◽  
The Creation

The creation of monitoring clusters based on cloud computing technologies is a promising direction for the development of systems for continuous monitoring of objects for various purposes in the web space. Hadoop web-programming environment is the technological basis for the development of algorithmic and software solutions for the synthesis of monitoring clusters, including information security and information counteraction systems. The International Telecommunication Union’ (ITU) recommendations Y. 3510 present the requirements for cloud infrastructure that require monitoring the performance of deployed applications based on the collection of real-world statistics. Often, computing resources of monitoring clusters of cloud data centers are allocated for continuous parallel processing of high-speed streaming data, which imposes new requirements to monitoring technologies, necessitating the creation and research of new models of parallel computing. The need to use service monitoring plays an important role in the cloud computing industry, especially for SLA/QoS assessment, as the application or service may experience problems even if the virtual machines on which the work is taking place appear to be operational. This requires to study the methodological possibilities of organization to study of parallel processing high-speed streaming services with the processing of huge amounts of bit data, and, simultaneously, to estimate the necessary computational resource. In the conditions of high dynamics of changes in the bit rate of information generation from the source, a model of the bit rate of Discretized Stream (DStream) formation is proposed, which has a common application. Based on the poly-burst nature of the bit rate model, a model of group content traffic of any sources of different services processed in the cloud cluster was created. The obtained results made it possible to develop mathematical models of parallel DStreams from sources processed in a cloud cluster via Hadoop technology using the micro-batch architecture of the Spark Streaming module. These models take into account the flow of requests for maintenance from sources of different services, on the one hand, and, on the other hand, the needs of services in bit rate, taking into account the multichannel traffic of sources of various services. At the same time, analytical relations are obtained to calculate the required performance of the Hadoop cluster at a given value of the probability of batch loss.

scholarly journals АНАЛИЗ ПОДХОДОВ К ОБЕСПЕЧЕНИЮ БЕЗОПАСНОСТИ ОБЛАЧНЫХ СЕРВИСОВ

2020 ◽  
pp. 70-82
Author(s):  
Вячеслав Вікторович Фролов
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Geographical Location ◽  
Cloud Service ◽  
Cloud Services ◽  
Cloud Infrastructure ◽  
Critical System ◽  
Cloud Service Providers ◽  
Safety And Reliability ◽  
Cloud Resources

The article is devoted to the analysis of modern approaches that ensure the security of cloud services. Since cloud computing is one of the fastest growing areas among information technology, it is extremely important to ensure the safety and reliability of processes occurring in the clouds and to secure the interaction between the client and the provider of cloud services. Given that fears about data loss and their compromise are one of the main reasons that some companies do not transfer their calculations to the clouds. The object of research and analysis of this work are cloud services, which are provided by various cloud service providers. The aim of the study of this work is to compare existing approaches that provide information security for cloud services, as well as offer a new approach based on the principle of diversity. There are many approaches that ensure their safety, using both traditional and cloud-specific. The multi-cloud approach is one of the most promising strategies for improving reliability by reserving cloud resources on the servers of various cloud service providers. It is shown that it is necessary to use diversity to ensure the reliability and safety of critical system components. The principle of diversity is to use a unique version of each resource thanks to a special combination of a cloud computing provider, the geographical location of data centers, cloud service presentation models, and cloud infrastructure deployment models. The differences between cloud providers and which combination of services are preferable to others in terms of productivity are discussed in detail. In addition, best practices for securing cloud resources are reviewed. As a result, this paper concludes that there is a problem of insufficient security and reliability of cloud computing and how to reduce threats in order to avoid a common cause failure and, as a result, loss of confidential data or system downtime using diversity of cloud services.

Does cloud computing improve team performance and employees' creativity?

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jing Zou ◽  
Cheng Jian
Keyword(s):  
Cloud Computing ◽  
Team Performance ◽  
Supporting Evidence ◽  
Cloud Infrastructure ◽  
Employee Creativity ◽  
Content Type ◽  
Cloud Management ◽  
Cloud Application ◽  
The Impact ◽  
Cloud Resources

Purpose The present investigation goals to empirically test the role of expert cloud on team performance and employee creativity. Here, the expert cloud comprises cloud application, cloud management, cloud infrastructure and cloud resources. The present study aims to identify important and key criteria and examine the relationships among them. In other words, the purpose of this study to find out the impact and relationship between cloud application, cloud management, cloud infrastructure and cloud resources and team performance and employee creativity. Design/methodology/approach Today, human societies’ rapid growth and the environmental changes that surround us every day are clearly visible. They highly affect our activities. In today’s highly complex organizations, people alone cannot handle all the issues that have arisen. As organizational managers are faced with diverse cultures in the governance of organizations, the need to use work teams with different abilities and specializations to achieve the goals of organizations leads managers to use teamwork and focus on employee creativity. On the other hand, the expert cloud makes it possible for human societies like universities, firms, industries, institutes, businesses and colleges to pool and share their human resources’ skills, knowledge and experiences to meet the competitive era’s demands. Therefore, the current investigation examines the impact of expert cloud on team performance and employee creativity. The research information is collected using an online questionnaire. The data collected is analyzed using AMOS and SMART PLS software. Findings All of the formulated hypotheses are supported. The results have shown that cloud application, cloud management, cloud infrastructure and cloud resources positively and significantly affect team performance and employee creativity. Practical implications Managers must be conscious of the vital role that the professional cloud plays in team performance and the innovation of workers. This paper would also make executives more conscious of the powerful tools in the field of cloud computing. Firms can use the outcomes of this paper investigation to improve team performance and employee creativity. Originality/value It is considered one of the initial efforts to demonstrate the impacts of expert cloud on team performance and employee creativity. This study’s value relies on that practitioners and academics may have supporting evidence on the role played by novel technology such as an expert cloud.

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 A STOCHASTIC DEVELOPMENT OF CLOUD COMPUTING BASED TASK SCHEDULING ALGORITHM

2019 ◽  
Vol 2019 (1) ◽  
pp. 41-48 ◽  
Author(s):  
Karunakaran V
Keyword(s):  
Virtual Machines ◽  
Cost Minimization ◽  
Scheduling Algorithm ◽  
Cloud Infrastructure ◽  
Solution Quality ◽  
Task Scheduling Algorithm ◽  
Simulation Results ◽  
Selection For ◽  
Stochastic Development ◽  
Data Centres

Due to diversity of services with respect to technology and resources, it is challenging to choose virtual machines (VM) from various data centres with varied features like cost minimization, reduced energy consumption, optimal response time and so on in cloud Infrastructure as a Service (IaaS) environment. The solutions available in the market are exhaustive computationally and aggregates multiple objectives to procure single trade-off that affects the solution quality inversely. This paper describes a hybrid algorithm that facilitates VM selection for scheduling applications based on Gravitational Search and Non-dominated Sorting Genetic Algorithm (GSA and NSGA). The efficiency of the proposed algorithm is verified by the simulation results.

scholarly journals Centralised Cleanup Service for Kubernetes and Cloud Resources

2021 ◽  
Vol 9 (VII) ◽  
pp. 1545-1549
Author(s):  
Pranava Bhat
Keyword(s):  
Software Development ◽  
Virtual Machines ◽  
Software Development Process ◽  
Architectural Style ◽  
Software Application ◽  
Engineering Teams ◽  
Loosely Coupled ◽  
Agile Software ◽  
Container Orchestration ◽  
Cloud Resources

The architectural style of developing a software application using loosely coupled and highly cohesive services can be termed as microservices architecture. The microservices allow agile software development and enable businesses to build and deliver applications quickly. To achieve the benefits of microservices, an underlying infrastructure that supports them must exist. This includes CI/CD pipelines, execution environments like virtual machines and containers, logging and monitoring, communication mechanisms, and so on. Containers are lightweight, enable multiple execution environments to exist on a single operating system instance, and provide isolation. Container Orchestration Engines such as Docker swarm or Kubernetes automate deployment, scaling, fault tolerance, and container networking. Many organizations use containers to spawn resources in public or private clouds. Different engineering teams perform various kinds of tests by bundling the test code and dependencies into containers. However, cleaning up these containers is necessary for the efficient utilization of hardware resources. This paper discusses the need and benefits of a centralized cleanup service for Kubernetes and cloud resources. It analyzes the value additions this service can bring to the software development process of large organizations.

Using Value-Based Approach for Managing Cloud-Based Services

2017 ◽  
pp. 33-60
Author(s):  
Salah Eddin Murad ◽  
Salah Dowaji
Keyword(s):  
Response Time ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Software As A Service ◽  
Business Service ◽  
Cloud Infrastructure ◽  
Current Strategy ◽  
Target Value ◽  
Different Types ◽  
And Control

Software-as-a-Service (SaaS) providers are influenced by a variety of characteristics and capabilities of the available cloud infrastructure resources (IaaS). As a result, the decision made by business service owners to lease and use certain resources is an important one in order to achieve the planned outcome. This chapter uses value based approach to manage the SaaS service provided to the customers. Based on our approach, customer satisfaction is modeled not only based on the response time, but also based on the allotted budget. Using our model, the application owner is able to direct and control the decision of renting cloud resources as per the current strategy. This strategy is led by a set of defined key performance indicators. In addition, we present a scheduling algorithm that can bid for different types of virtual machines to achieve the target value. Furthermore, we proposed the required Ontology to semantically discover the needed IaaS resources. We conduct extensive simulations using different types of Amazon EC2 instances with dynamic prices.

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