scholarly journals Multiobjective Level-Wise Scientific Workflow Optimization in IaaS Public Cloud Environment

2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
Phyo Thandar Thant ◽  
Courtney Powell ◽  
Martin Schlueter ◽  
Masaharu Munetomo
Keyword(s):  
Big Data ◽  
Virtual Machine ◽  
Resource Selection ◽  
Service Providers ◽  
Scientific Workflow ◽  
Cloud Infrastructure ◽  
Nsga Ii ◽  
Workflow Optimization ◽  
Machine Failure ◽  
Deployment Cost

Cloud computing in the field of scientific applications such as scientific big data processing and big data analytics has become popular because of its service oriented model that provides a pool of abstracted, virtualized, dynamically scalable computing resources and services on demand over the Internet. However, resource selection to make the right choice of instances for a certain application of interest is a challenging problem for researchers. In addition, providing services with optimal performance at the lowest financial resource deployment cost based on users’ resource selection is quite challenging for cloud service providers. Consequently, it is necessary to develop an optimization system that can provide benefits to both users and service providers. In this paper, we conduct scientific workflow optimization on three perspectives: makespan minimization, virtual machine deployment cost minimization, and virtual machine failure minimization in the cloud infrastructure in a level-wise manner. Further, balanced task assignment to the virtual machine instances at each level of the workflow is also considered. Finally, system efficiency verification is conducted through evaluation of the results with different multiobjective optimization algorithms such as SPEA2 and NSGA-II.

scholarly journals A virtual machine migration policy for multi-tier application in cloud computing based on game theory

2021 ◽  
Author(s):  
Hung Cong Tran ◽  
Khiet Thanh Bui ◽  
Hung Dac Ho ◽  
Vu Tran Vu
Keyword(s):  
Game Theory ◽  
Cloud Computing ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Service Providers ◽  
Learning Algorithm ◽  
Energy Performance ◽  
Cloud Infrastructure ◽  
Virtual Machine Migration ◽  
Extraction Phase

Abstract Cloud computing technology provides shared computing which can be accessed over the Internet. When cloud data centers are flooded by end-users, how to efficiently manage virtual machines to balance both economical cost and ensure QoS becomes a mandatory work to service providers. Virtual machine migration feature brings a plenty of benefits to stakeholders such as cost, energy, performance, stability, availability. However, stakeholder's objectives are usually conflicted with each other. Also, the optimal resource allocation problem in cloud infrastructure is usually NP-Hard or NP-Complete class. In this paper, the virtual migration problem is formulated by applying game theory to ensure both load balance and resource utilization. The virtual machine migration algorithm, named V2PQL, is proposed based on Markov Decision Process and Q-learning algorithm. The results of the simulation demonstrate the efficiency of our proposal which are divided into training phase and extraction phase. The proposed V2PQL policy has been benchmarked to the Round-Robin policy in order to highlight their strength and feasibility in policy extraction phase.

A Hybrid Approach for Virtual Machine Migration in Cloud Computing Environment

2017 ◽  
Vol 7 (9) ◽  
pp. 30 ◽  
Author(s):  
Ramandeep Kaur
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Heuristic Algorithms ◽  
Hybrid Approach ◽  
Cloud Infrastructure ◽  
Virtual Machine Migration ◽  
Bee Colony ◽  
Effective Manner ◽  
Effective Performance

A lot of research has been done in the field of cloud computing in computing domain.  For its effective performance, variety of algorithms has been proposed. The role of virtualization is significant and its performance is dependent on VM Migration and allocation. More of the energy is absorbed in cloud; therefore, the utilization of numerous algorithms is required for saving energy and efficiency enhancement in the proposed work. In the proposed work, green algorithm has been considered with meta heuristic algorithms, ABC (Artificial Bee colony .Every server has to perform different or same functions. A cloud computing infrastructure can be modelled as Primary Machineas a set of physical Servers/host PM1, PM2, PM3… PMn. The resources of cloud infrastructure can be used by the virtualization technology, which allows one to create several VMs on a physical server or host and therefore, lessens the hardware amount and enhances the resource utilization. The computing resource/node in cloud is used through the virtual machine. To address this problem, data centre resources have to be managed in resource -effective manner for driving Green Cloud computing that has been proposed in this work using Virtual machine concept with ABC and Neural Network optimization algorithm. The simulations have been carried out in CLOUDSIM environment and the parameters like SLA violations, Energy consumption and VM migrations along with their comparison with existing techniques will be performed.

GOVERNMENT REGULATIONS OF THE USING CLOUD SERVICES

2022 ◽  
Author(s):  
Olexander Melnikov ◽  
◽  
Konstantin Petrov ◽  
Igor Kobzev ◽  
Viktor Kosenko ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Service Providers ◽  
Cloud Service ◽  
Cloud Services ◽  
Government Agencies ◽  
Remote Work ◽  
Cloud Infrastructure ◽  
Wide Range ◽  
Technological Base

The article considers the development and implementation of cloud services in the work of government agencies. The classification of the choice of cloud service providers is offered, which can serve as a basis for decision making. The basics of cloud computing technology are analyzed. The COVID-19 pandemic has identified the benefits of cloud services in remote work Government agencies at all levels need to move to cloud infrastructure. Analyze the prospects of cloud computing in Ukraine as the basis of e-governance in development. This is necessary for the rapid provision of quality services, flexible, large-scale and economical technological base. The transfer of electronic information interaction in the cloud makes it possible to attract a wide range of users with relatively low material costs. Automation of processes and their transfer to the cloud environment make it possible to speed up the process of providing services, as well as provide citizens with minimal time to obtain certain information. The article also lists the risks that exist in the transition to cloud services and the shortcomings that may arise in the process of using them.

scholarly journals Sunlight alone is not a disinfectant: Consent and the futility of opening Big Data black boxes (without assistance)

2020 ◽  
Vol 7 (1) ◽  
pp. 205395172093561 ◽  
Author(s):  
Jonathan A. Obar
Keyword(s):  
Big Data ◽  
Service Providers ◽  
Information Access ◽  
Data Practices ◽  
Black Boxes

In our attempts to achieve privacy and reputation deliverables, advocating for service providers and other data managers to open Big Data black boxes and be more transparent about consent processes, algorithmic details, and data practice is easy. Moving from this call to meaningful forms of transparency, where the Big Data details are available, useful, and manageable is more difficult. Most challenging is moving from that difficult task of meaningful transparency to the seemingly impossible scenario of achieving, consistently and ubiquitously, meaningful forms of consent, where individuals are aware of data practices and implications, understand these realities, and agree to them as well. This commentary unpacks these concerns in the online consent context. It emphasizes that self-governance fallacy pervades current approaches to achieving digital forms of privacy, exemplified by the assertion that transparency and information access alone are enough to help individuals achieve privacy and reputation protections.

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.

scholarly journals Pangeo Forge: Crowdsourcing Analysis-Ready, Cloud Optimized Data Production

2021 ◽  
Author(s):  
Charles Stern ◽  
Ryan Abernathey ◽  
Joseph Hamman ◽  
Rachel Wegener ◽  
Chiara Lepore ◽  
...  
Keyword(s):  
Big Data ◽  
Open Source ◽  
Climate Science ◽  
Cloud Infrastructure ◽  
Scientific Domain ◽  
Weather And Climate ◽  
Data Production ◽  
New Community ◽  
High Level ◽  
Machine Readable

Pangeo Forge is a new community-driven platform that accelerates science by providing high-level recipe frameworks alongside cloud compute infrastructure for extracting data from provider archives, transforming it into analysis-ready, cloud-optimized (ARCO) data stores, and providing a human- and machine-readable catalog for browsing and loading. In abstracting the scientific domain logic of data recipes from cloud infrastructure concerns, Pangeo Forge aims to open a door for a broader community of scientists to participate in ARCO data production. A wholly open-source platform composed of multiple modular components, Pangeo Forge presents a foundation for the practice of reproducible, cloud-native, big-data ocean, weather, and climate science without relying on proprietary or cloud-vendor-specific tooling.

scholarly journals Selection of optimal data placement using cloud infrastructure

2021 ◽  
pp. 34-42
Author(s):  
Vladimir Meikshan ◽  
◽  
Natalia Teslya ◽  
Keyword(s):  
Mathematical Model ◽  
Data Storage ◽  
Service Providers ◽  
Cloud Service ◽  
Cloud Services ◽  
Information Storage ◽  
Cloud Infrastructure ◽  
Digital Ecosystem ◽  
Cloud Service Providers ◽  
The Cost

Benefits of using cloud technology are obvious, their application is expanding, as a result, it determines the steady growth of demand. Cloud computing has acquired particular relevance for large companies connected with Internet services, retailing, logistics that generate large volume of business and other information. The use of cloud technologies allows organizing the joint consumption of resources, solving the problems of storing and transferring significant amounts of data. Russian consumer cooperation refers to large territory distributed organizations actively forming their own digital ecosystem. The issue of data storing and processing for consumer coo-peration organizations is very relevant. At the same time, the prices of cloud service providers are significantly different and require solving the problem of minimizing the cost of storing and transferring significant amounts of data. The application of the linear programming method is considered to select the optimal data storage scheme for several cloud service providers having different technical and economic parameters of the package (maximum amount of storage, cost of allocated resources). Mathematical model includes the equation of costs for data storing and transferring and restrictions on the amount of storage, the amount of data and its safety. Software tool that allows to perform numerical calculations is selected Microsoft Excel in combination with the "search for solutions" add-on. In accordance with the mathematical model, the conditions for minimizing the amount of cloud storage costs and the necessary restrictions are established. Initial data are set for three data forming centers, storages of certain size for five cloud service providers and nominal price for information storage and transmission. Calculations of expenses are performed in several variants: without optimization, with the solution of the optimization problem, with price increase by cloud service providers. Results of the calculations confirm the necessity to solve the problem of minimizing the cost of cloud services for corporate clients. The presented model can be expanded for any cost conditions as well as for different areas of cloud applications.

scholarly journals The Smart Triad : Big Data Analytics , Cloud Computing and Internet of Things to shape the Smart Home, Smart City, Smart Business & Smart Country

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3594-3600 ◽  
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Data Analytics ◽  
Smart Home ◽  
Service Providers ◽  
Irrigation System ◽  
Electronic Devices ◽  
Big Data Analytics ◽  
User Privacy

Big data analytics, cloud computing & internet of things are a smart triad which have started shaping our future towards smart home, city, business, country. Internet of things is a convergence of intelligent networks, electronic devices, and cloud computing. The source of big data at different connected electronic devices is stored on cloud server for analytics. Cloud provides the readymade infrastructure, remote processing power to consumers of internet of things. Cloud computing also gives device manufacturers and service providers access to ―advanced analytics and monitoring‖, ―communication between services and devices‖, ―user privacy and security‖. This paper, presents an overview of internet of things, role of cloud computing & big data analytics towards IoT. In this paper IoT enabled automatic irrigation system is proposed that saves data over ―ThingSpeak‖ database an IoT analytics platform through ESP8266 wifi module. This paper also summarizes the application areas and discusses the challenges of IoT.

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