scholarly journals Reducing cloud infrastructure costs through task management

2021 ◽  
Vol 4 (4) ◽  
pp. 366-376
Author(s):  
Oleg N. Galchonkov ◽  
Mykola I. Babych ◽  
Andrey V. Plachinda ◽  
Anastasia R. Majorova
Keyword(s):  
Cloud Services ◽  
Time Interval ◽  
Cloud Provider ◽  
Task Management ◽  
Cloud Infrastructure ◽  
Price Forecast ◽  
Discrete Moment ◽  
Preliminary Preparation ◽  
The Cost ◽  
Placement Option

The transition of more and more companies from their own computing infrastructure to the clouds is due to a decrease in the cost of maintaining it, the broadest scalability, and the presence of a large number of tools for automating activities. Accordingly, cloud providers provide an increasing number of different computing resources and tools for working in the clouds. In turn, this gives rise to the problem of the rational choice of the types of cloud services in accordance with the peculiarities of the tasks to be solved. One of the most popular areas of effort for cloud consumers is to reduce rental costs. The main base of this direction is the use of spot resources. The article proposes a method for reducing the cost of renting computing resources in the cloud by dynamically managing the placement of computational tasks, which takes into account the possible underutilization of planned resources, the forecast of the appearance of spot resources and their cost. For each task, a state vector is generated that takes into account the duration of the task and the required deadline. Accordingly, for a suitable set of computing resources, an availability forecast vectors are formed at a given time interval, counting from the current moment in time. The technique proposes to calculate at each discrete moment of time the most rational option for placing the task on one of the resources and the delay in starting the task on it. The placement option and launch delays are determined by minimizing the rental cost function over the time interval using a genetic algorithm. One of the features of using spot resources is the auction mechanism for their provision by a cloud provider. This means that if there are more preferable rental prices from any consumer, then the provider can warn you about the disconnection of the resource and make this disconnection after the announced time. To minimize the consequences of such a shutdown, the technique involves preliminary preparation of tasks by dividing them into substages with the ability to quickly save the current results in memory and then restart from the point of stop. In addition, to increase the likelihood that the task will not be interrupted, a price forecast for the types of resources used is used and a slightly higher price is offered for the auction of the cloud provider, compared to the forecast. Using the example of using the Elastic Cloud Computing (EC2) environment of the cloud provider AWS, the effectiveness of the proposed method is shown.

scholarly journals Micro Service Based System for Cost Based Selection of Cloud Provider Services

2020 ◽  
Vol 8 (5) ◽  
pp. 985-991
Keyword(s):  
Service Providers ◽  
Cloud Service ◽  
Daily Basis ◽  
Cloud Services ◽  
Cloud Provider ◽  
Cloud Infrastructure ◽  
Cloud Service Providers ◽  
Architectural Framework ◽  
The Cost ◽  
Cloud Applications

The increase in the amount of data generated on a daily basis coupled with the need to store and manage this data has encouraged the organizations to adopt cloud computing. In order to ensure better availability and reliability of their data as well as resources, most of the organizations make use of one or more cloud service providers .But the use of cloud resources puts forth some challenges as well. One of the challenges is its detailed monitoring. As the number of services utilized by the cloud consumers goes on increasing, the number of logs and metrics generated by them also scales rapidly.The dynamic nature of cloud infrastructure and the variety of services offered by several cloud vendors demands a sophisticated mechanism to calculate and analyze the cost of using different services. The billing reports by the cloud service providers deliver statistics about the usage of resources and the costs associated with them. It contains large amount of data which needs to be processed in order to gain useful information. In this paper, we propose a micro service based architectural framework which gathers the data from two different cloud service providers. This data is not only stored but processed to generate reports to enable optimal use of cloud infrastructure. The use of microservices framework provides benefits and is a preferred framework for the development of cloud applications. The main aim of this work is to provide an integrated mechanism to enable the comparison of cost for using similar cloud services.

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 Evaluating Cloud Service Elasticity Behavior

2015 ◽  
Vol 24 (03) ◽  
pp. 1541002 ◽  
Author(s):  
Georgiana Copil ◽  
Hong-Linh Truong ◽  
Daniel Moldovan ◽  
Schahram Dustdar ◽  
Demetris Trihinas ◽  
...  
Keyword(s):  
Control Process ◽  
Cloud Service ◽  
Cloud Services ◽  
Decision Quality ◽  
Decision Making Process ◽  
Cloud Infrastructure ◽  
Control Processes ◽  
And Performance ◽  
The Cost ◽  
Different Parts

To optimize the cost and performance of complex cloud services under dynamic requirements, workflows and diverse cloud offerings, we rely on different elasticity control processes. An elasticity control process, when being enforced, produces effects in different parts of the cloud service. These effects normally evolve in time and depend on workload characteristics, and on the actions within the elasticity control process enforced. Therefore, understanding the effects on the behavior of the cloud service is of utter importance for runtime decision-making process, when controlling cloud service elasticity. In this paper, we present a novel methodology and a framework for estimating and evaluating cloud service elasticity behaviors. To estimate the elasticity behavior, we collect information concerning service structure, deployment, service runtime, control processes, and cloud infrastructure. Based on this information, we utilize clustering techniques to identify cloud service elasticity behavior, in time, and for different parts of the service. Knowledge about such behavior is utilized within a cloud service elasticity controller to substantially improve the selection and execution of elasticity control processes. These elasticity behavior estimations are successfully being used by our elasticity controller, in order to improve runtime decision quality. We evaluate our framework with three real-world cloud services in different application domains. Experiments show that we are able to estimate the behavior in 89.5% of the cases. Moreover, we have observed improvements in our elasticity controller, which takes better control decisions, and does not exhibit control oscillations.

scholarly journals Networking for Cloud Robotics: The DewROS Platform and Its Application

2021 ◽  
Vol 10 (2) ◽  
pp. 34
Author(s):  
Alessio Botta ◽  
Jonathan Cacace ◽  
Riccardo De Vivo ◽  
Bruno Siciliano ◽  
Giorgio Ventre
Keyword(s):  
Response Time ◽  
Large Data ◽  
Cloud Services ◽  
Cloud Provider ◽  
Human Beings ◽  
Minimal Impact ◽  
Network Connection ◽  
Cloud Robotics ◽  
Networking Technologies ◽  
The Impact

With the advances in networking technologies, robots can use the almost unlimited resources of large data centers, overcoming the severe limitations imposed by onboard resources: this is the vision of Cloud Robotics. In this context, we present DewROS, a framework based on the Robot Operating System (ROS) which embodies the three-layer, Dew-Robotics architecture, where computation and storage can be distributed among the robot, the network devices close to it, and the Cloud. After presenting the design and implementation of DewROS, we show its application in a real use-case called SHERPA, which foresees a mixed ground and aerial robotic platform for search and rescue in an alpine environment. We used DewROS to analyze the video acquired by the drones in the Cloud and quickly spot signs of human beings in danger. We perform a wide experimental evaluation using different network technologies and Cloud services from Google and Amazon. We evaluated the impact of several variables on the performance of the system. Our results show that, for example, the video length has a minimal impact on the response time with respect to the video size. In addition, we show that the response time depends on the Round Trip Time (RTT) of the network connection when the video is already loaded into the Cloud provider side. Finally, we present a model of the annotation time that considers the RTT of the connection used to reach the Cloud, discussing results and insights into how to improve current Cloud Robotics applications.

scholarly journals Selective caching: a persistent memory approach for multi-dimensional index structures

2021 ◽  
Author(s):  
Muhammad Attahir Jibril ◽  
Philipp Götze ◽  
David Broneske ◽  
Kai-Uwe Sattler
Keyword(s):  
Main Memory ◽  
Index Structure ◽  
Index Structures ◽  
Cloud Infrastructure ◽  
General Technique ◽  
Persistent Memory ◽  
The Cost ◽  
Cloud Applications ◽  
Memory Layout ◽  
Analytical Index

AbstractAfter the introduction of Persistent Memory in the form of Intel’s Optane DC Persistent Memory on the market in 2019, it has found its way into manifold applications and systems. As Google and other cloud infrastructure providers are starting to incorporate Persistent Memory into their portfolio, it is only logical that cloud applications have to exploit its inherent properties. Persistent Memory can serve as a DRAM substitute, but guarantees persistence at the cost of compromised read/write performance compared to standard DRAM. These properties particularly affect the performance of index structures, since they are subject to frequent updates and queries. However, adapting each and every index structure to exploit the properties of Persistent Memory is tedious. Hence, we require a general technique that hides this access gap, e.g., by using DRAM caching strategies. To exploit Persistent Memory properties for analytical index structures, we propose selective caching. It is based on a mixture of dynamic and static caching of tree nodes in DRAM to reach near-DRAM access speeds for index structures. In this paper, we evaluate selective caching on the OLAP-optimized main-memory index structure Elf, because its memory layout allows for an easy caching. Our experiments show that if configured well, selective caching with a suitable replacement strategy can keep pace with pure DRAM storage of Elf while guaranteeing persistence. These results are also reflected when selective caching is used for parallel workloads.

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.

Benefits and Challenges for Business Process Management in the Cloud

2015 ◽  
Vol 5 (2) ◽  
pp. 80-104 ◽  
Author(s):  
Ute Riemann
Keyword(s):  
Cloud Computing ◽  
Business Process ◽  
Information Exchange ◽  
Business Process Management ◽  
Process Management ◽  
Business Models ◽  
Business Processes ◽  
Cloud Services ◽  
Cloud Infrastructure ◽  
Business Application

Business processes are not only variable they are as well dynamic. A key benefit of Business Process Management (BPM) is the ability to adjust business processes accordingly in response to changing market requirements. In parallel to BPM, enterprise cloud computing technology has emerged to provide a more cost effective solution to businesses and services while making use of inexpensive computing solutions, which combines pervasive, internet, and virtualization technologies (). Despite the slow start, the business benefits of cloud computing are as such that the transition of BPM to the cloud is now underway. Cloud services refer to the operation of a virtualized, automated, and service-oriented IT landscape allowing the flexible provision and usage-based invoicing of resources, services, and applications via a network or the internet. The generic term “X-as-a-Service” summarize the business models delivering almost everything as a service. BPM in the cloud is often regarded as a SaaS application. More recently, BPM is being regarded as a PaaS as it facilitates the creation and deployment of applications, in this case business process solutions. The PaaS landscape is the least developed of the four cloud based software delivery models previously discussed. PaaS vendors, such as IBM, Oracle, and Microsoft delivered an application platform with managed cloud infrastructure services however, more recently the PaaS market has begun to evolve to include other middleware capabilities including process management. BPM PaaS is the delivery of BPM technology as a service via a cloud service provider. For the classification as a PaaS a BPM suite requires the following capabilities: the architecture should be multi-tenant, hosting should be off premise and it should offer elasticity and metering by use capabilities. When we refer to BPM in the cloud, what we are really referring to is a combination of BPM PaaS and BPaaS (Business Process as a Service). Business Process as a Service (BPaaS) is a set of pre-defined business processes that allows the execution of customized business processes in the cloud. BPaaS is a complete pre-integrated BPM platform hosted in the cloud and delivered as a service, for the development and execution of general-purpose business process application. Although such a service harbors an economic potential there are remaining questions: Can an individual and company-specific business process supported by a standardized cloud solution, or should we protect process creativity and competitive differentiation by allowing the company to design the processes individually and solely support basic data flows and structures? Does it make sense to take a software solution “out of the box” that handles both data and process in a cloud environment, or would this hinder the creativity of business (process) development leading to a lower quality of processes and consequently to a decrease in the competitive positioning of a company? How to manage the inherent compliance and security topic. Within a completely integrated business application system, all required security aspects can be implemented as a safeguarding with just enough money. Within the cloud, however, advanced standards and identity prove is required to monitor and measure information exchange across the federation. Thereby there seems to be no need for developing new protocols, but a standardized way to collect and evaluate the collected information.

An Architecture Paradigm for Providing Cloud Services in School Labs Based on Open Source Software to Enhance ICT in Education

2012 ◽  
Vol 2 (1) ◽  
pp. 44-57 ◽  
Author(s):  
Yannis Siahos ◽  
Iasonas Papanagiotou ◽  
Alkis Georgopoulos ◽  
Fotis Tsamis ◽  
Ioannis Papaioannou
Keyword(s):  
Classroom Management ◽  
Open Source ◽  
Open Source Software ◽  
Educational Software ◽  
Cloud Model ◽  
Cloud Services ◽  
Hybrid Cloud ◽  
Information Communication ◽  
Cloud Infrastructure ◽  
On Line

The authors present their experience and practices of introducing cloud services, as a means to simplify the adoption of ICT (Information Communication and Technology) in education, using Free/Open Source Software. The solution creates a hybrid cloud infrastructure, in order to provide a pre-installed (Ubuntu and Linux Terminal Server Project) virtual machine, acting as a server inside the school, providing desktop environment based on the Software as a Service cloud model, where legacy PCs act as stateless devices. Classroom management is accomplished using the application “Epoptes.” To minimize administration tasks, educational software is provided accordingly, either on-line or through repositories to automate software installation (including patches and updates). The advantages of the hybrid cloud implementation, include services that are not completely dependent on broadband connections’ state, minimal cost, reusability of obsolete equipment, ease of administration, centralized management, patches and educational software provisioning and, above all, facilitation of the educational procedure.

scholarly journals Cloud Brokering with Bundles: Multi-objective Optimization of Services Selection

2019 ◽  
Vol 44 (4) ◽  
pp. 407-426
Author(s):  
Jedrzej Musial ◽  
Emmanuel Kieffer ◽  
Mateusz Guzek ◽  
Gregoire Danoy ◽  
Shyam S. Wagle ◽  
...  
Keyword(s):  
Optimization Problem ◽  
Real Data ◽  
Cloud Service ◽  
Optimal Choice ◽  
Cloud Services ◽  
Multi Objective Optimization ◽  
Problem Instances ◽  
The Cost ◽  
Special Case ◽  
Single Objective

Abstract Cloud computing has become one of the major computing paradigms. Not only the number of offered cloud services has grown exponentially but also many different providers compete and propose very similar services. This situation should eventually be beneficial for the customers, but considering that these services slightly differ functionally and non-functionally -wise (e.g., performance, reliability, security), consumers may be confused and unable to make an optimal choice. The emergence of cloud service brokers addresses these issues. A broker gathers information about services from providers and about the needs and requirements of the customers, with the final goal of finding the best match. In this paper, we formalize and study a novel problem that arises in the area of cloud brokering. In its simplest form, brokering is a trivial assignment problem, but in more complex and realistic cases this does not longer hold. The novelty of the presented problem lies in considering services which can be sold in bundles. Bundling is a common business practice, in which a set of services is sold together for the lower price than the sum of services’ prices that are included in it. This work introduces a multi-criteria optimization problem which could help customers to determine the best IT solutions according to several criteria. The Cloud Brokering with Bundles (CBB) models the different IT packages (or bundles) found on the market while minimizing (maximizing) different criteria. A proof of complexity is given for the single-objective case and experiments have been conducted with a special case of two criteria: the first one being the cost and the second is artificially generated. We also designed and developed a benchmark generator, which is based on real data gathered from 19 cloud providers. The problem is solved using an exact optimizer relying on a dichotomic search method. The results show that the dichotomic search can be successfully applied for small instances corresponding to typical cloud-brokering use cases and returns results in terms of seconds. For larger problem instances, solving times are not prohibitive, and solutions could be obtained for large, corporate clients in terms of minutes.

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.

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