scholarly journals AUTO-SCALING AND ADJUSTMENT PLATFORM FOR CLOUD-BASED SYSTEMS

2017 ◽  
Vol 2 ◽  
pp. 52 ◽  
Author(s):  
Jānis Kampars ◽  
Krišjānis Pinka
Keyword(s):  
Real Time ◽  
Performance Metrics ◽  
Virtual Machines ◽  
Service Providers ◽  
Cloud Service ◽  
Cloud Infrastructure ◽  
Time Data ◽  
Cloud Service Providers ◽  
Auto Scaling

For customers of cloud-computing platforms it is important to minimize the infrastructure footprint and associated costs while providing required levels of Quality of Service (QoS) and Quality of Experience (QoE) dictated by the Service Level Agreement (SLA). To assist with that cloud service providers are offering: (1) horizontal resource scaling through provisioning and destruction of virtual machines and containers, (2) vertical scaling through changing the capacity of individual cloud nodes. Existing scaling solutions mostly concentrate on low-level metrics like CPU load and memory consumption which doesn’t always correlate with the level of SLA conformity. Such technical measures should be preprocessed and viewed from a higher level of abstraction. Application level metrics should also be considered when deciding upon scaling the cloud-based solution. Existing scaling platforms are mostly proprietary technologies owned by cloud service providers themselves or by third parties and offered as Software as a Service. Enterprise applications could span infrastructures of multiple public and private clouds, dictating that the auto-scaling solution should not be isolated inside a single cloud infrastructure. The goal of this paper is to address the challenges above by presenting the architecture of Auto-scaling and Adjustment Platform for Cloud-based Systems (ASAPCS). It is based on open-source technologies and supports integration of various low and high level performance metrics, providing higher levels of abstraction for design of scaling algorithms. ASAPCS can be used with any cloud service provider and guarantees that move from one cloud platform to another will not result in complete redesign of the scaling algorithm. ASAPCS itself is horizontally scalable and can process large amounts of real-time data which is particularly important for applications developed following the microservices architectural style. ASAPCS approaches the scaling problem in a nonstandard way by considering real-time adjustments of the application logic to be part of the scalability strategy if it can result in performance improvements.

scholarly journals Makespan Optimisation in Cloudlet Scheduling with Improved DQN Algorithm in Cloud Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Amine Chraibi ◽  
Said Ben Alla ◽  
Abdellah Ezzati
Keyword(s):  
Execution Time ◽  
Work Performance ◽  
Virtual Machines ◽  
Service Providers ◽  
Scheduling Algorithm ◽  
Cloud Service ◽  
Cloud Infrastructure ◽  
Reward Function ◽  
Cloud Service Providers ◽  
Cloudlet Scheduling

Despite increased cloud service providers following advanced cloud infrastructure management, substantial execution time is lost due to minimal server usage. Given the importance of reducing total execution time (makespan) for cloud service providers (as a vital metric) during sustaining Quality-of-Service (QoS), this study established an enhanced scheduling algorithm for minimal cloudlet scheduling (CS) makespan with the deep Q-network (DQN) algorithm under MCS-DQN. A novel reward function was recommended to enhance the DQN model convergence. Additionally, an open-source simulator (CloudSim) was employed to assess the suggested work performance. Resultantly, the recommended MCS-DQN scheduler revealed optimal outcomes to minimise the makespan metric and other counterparts (task waiting period, resource usage of virtual machines, and the extent of incongruence against the algorithms).

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 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.

Examining Communication Technologies of IoT for Best QoS

2018 ◽  
pp. 264-276
Author(s):  
Jayashree K ◽  
Babu R ◽  
Chithambaramani R
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Cloud Service ◽  
Communication Technologies ◽  
Industry Sector ◽  
Cloud Service Providers ◽  
The Internet Of Things ◽  
Excessive Number ◽  
The Web

The Internet of Things (IoT) architecture has gained an increased amount of attention from academia as well as the industry sector as a significant methodology for the development of innovative applications and systems. Currently, the merging of this architecture with that of Cloud computing has been largely motivated by the need for various applications and infrastructures in IoT. In addition to this, the Cloud ascends as an eminent solution that would help solve various challenges that are faced by the IoT standard when varied physical devices. There are an excessive number of Cloud service providers the web along with many other services. Thus, it becomes critical to choose the provider who can be efficient, consistent, and suitable, and who can deliver the best Quality of Service (QoS). Thus, this chapter discusses QoS for cloud computing and IoT.

A mixed ideal and anti-ideal DEA model: an application to evaluate cloud service providers

2019 ◽  
Author(s):  
Majid Azadi ◽  
Mohammad Izadikhah ◽  
Fahimeh Ramezani ◽  
Farookh Khadeer Hussain
Keyword(s):  
Service Providers ◽  
Rapid Development ◽  
Cloud Service ◽  
Data Envelopment ◽  
Ranking Methods ◽  
Discrimination Power ◽  
Cloud Service Providers ◽  
Complete Ranking ◽  
Selection Of

Abstract The rapid development of cloud computing and the sharp increase in the number of cloud service providers (CSPs) have resulted in many challenges in the suitability and selection of the best CSPs according to quality of service requirements. The main objective of this study is to propose three novel models based on the enhanced Russell model to increase the discrimination power in the evaluation and selection of CSPs. The proposed models are designed based on the distances to two special decision-making units (DMUs), namely the ideal DMU and the anti-ideal DMU. There are two advantages to the proposed ranking methods. First, they consider both pessimistic and optimistic scenarios of data envelopment analysis, so they are more equitable than methods that are based on only one of these scenarios. The second strength of this approach is its discrimination power, enabling it to provide a complete ranking for all CSPs. The proposed method can help customers to choose the most appropriate CSP while at the same time, it helps software developers to identify inefficient CSPs in order to improve their performance in the marketplace.

scholarly journals A Novel Cryptosystem for Files Stored in Cloud using NTRU Encryption Algorithm

2020 ◽  
Vol 9 (1) ◽  
pp. 2127-2130
Keyword(s):  
Service Provider ◽  
Service Providers ◽  
Computational Cost ◽  
Cloud Service ◽  
Encryption Algorithm ◽  
Advanced Encryption Standard ◽  
Cloud Infrastructure ◽  
Computationally Efficient ◽  
Cloud Service Provider ◽  
Cloud Service Providers

The cloud refers to a set of services and infrastructure that are accessed via the internet. the cloud infrastructure is shared by many users each one performing different tasks. in order to prevent data leakage in the cloud the Cloud Service Provider should employ an Encryption Algorithm to protect the data of the users. Since the cloud service providers and large amount of data the Encryption Algorithm should be very efficient in terms of computational cost and time. Current Cloud service providers you son of the following algorithms to encrypt and decrypt the data Advanced encryption standard(AES), Rivest–Shamir–Adleman (RSA) and elliptic curve cryptography(ECC).The encryption for cloud should be chosen such that it is computationally efficient for the Cloud Service Provider and also meets the security requirement of the user

scholarly journals An Efficient Resource Scheduling Framework for Infrastructure Performance Enhancement in Cloud Environment

2019 ◽  
Vol 8 (4) ◽  
pp. 7283-7287
Keyword(s):  
Performance Enhancement ◽  
Service Providers ◽  
Cloud Service ◽  
Cloud Services ◽  
Cloud Infrastructure ◽  
Cloud Service Providers ◽  
Efficient Resource ◽  
Infrastructure Performance ◽  
Cloud Users ◽  
Level Performance

On-demand cloud services must be provided to customers at any time by ways of cloud service providers due to cloud demand. It is obligatory for cloud service providers to lessen large volumes of data, thereby it can reduce costs for maintaining large storage systems.Infrastructure level performance is an important problem which directly affects the overall working of cloud computing environment. The objective of our framework is enhancing the performance of cloud infrastructure. Proposed approach demonstrates high effective in cloud performance enhancement, as it displays enhancement in both the service providers as well as for cloud users.

A Novel Architectural Model for Dynamic Updating and Verification of Data Storage in Cloud Environment

2021 ◽  
Vol 13 (4) ◽  
pp. 75-83
Author(s):  
Dharmendra Singh Rajput ◽  
Praveen Kumar Reddy M. ◽  
Ramasubbareddy Somula ◽  
Bharath Bhushan S. ◽  
Ravi Kumar Poluru
Keyword(s):  
Data Storage ◽  
Service Providers ◽  
Cloud Service ◽  
It Industry ◽  
Multiple Data ◽  
Data Control ◽  
Cloud Service Providers ◽  
Multiple Copies ◽  
Dynamic Updating

Cloud computing is a quickly emerging computing model in the IT industry. Due to the rapid increase in technology, many clients want to store multiple copies of the same data in multiple data centers. Clients are outsourcing the data to cloud service providers and enjoying the high quality of service. Cloud service providers (CSP) are going to charge extra amounts for storing multiple copies; CSP must provide the firm guarantee for storing multiple copies. This paper proposes a new system model for storing and verifying multiple copies; this model deals with identifying tarnished copies which are transparent for the clients. Also, it deals with dynamic data control in the cloud with optimal results.

CLOUDSME

2021 ◽  
pp. 442-459
Author(s):  
Richard Otuka
Keyword(s):  
Service Providers ◽  
Cloud Service ◽  
Cloud Services ◽  
Adoption Process ◽  
Semantic Model ◽  
Service Adoption ◽  
Cloud Service Providers ◽  
Saas Cloud ◽  
Service Attribute

Presently, SMEs are finding it difficult to adopt cloud services for their businesses due to various service providers offering similar services. In addition, little work has been carried out in regards to the cloud services adoption process by SMEs. In this chapter, the authors propose CLOUDSME, a novel framework that aids in the adoption process of SaaS cloud services. Accordingly, they implement a decision support system, which includes an ontology of cloud services knowledge within the proposed framework. Analytical hierarchical process (AHP) is used to determine the weight of each cloud service attribute, and a benchmark is set to determine the acceptability of each cloud service based on its ability to meet the acceptable benchmark for each criteria. It can also help in a healthy competition to improve the quality of service among cloud service providers. The CLOUDSME semantic model will guide SME owners in answering user requirements towards decision making in the cloud service adoption process.

scholarly journals TOSCA-Based and Federation-Aware Cloud Orchestration for Kubernetes Container Platform

2019 ◽  
Vol 9 (1) ◽  
pp. 191 ◽  
Author(s):  
Dongmin Kim ◽  
Hanif Muhammad ◽  
Eunsam Kim ◽  
Sumi Helal ◽  
Choonhwa Lee
Keyword(s):  
Service Providers ◽  
Research Work ◽  
Cloud Service ◽  
Daunting Task ◽  
Cloud Service Providers ◽  
Service Areas ◽  
Sample Application ◽  
Container Orchestration ◽  
Auto Scaling ◽  
Cloud Applications

Kubernetes, a container orchestration tool for automatically installing and managing Docker containers, has recently begun to support a federation function of multiple Docker container clusters. This technology, called Kubernetes Federation, allows developers to increase the responsiveness and reliability of their applications by distributing and federating container clusters to multiple service areas of cloud service providers. However, it is still a daunting task to manually manage federated container clusters across all the service areas or to maintain the entire topology of cloud applications at a glance. This research work proposes a method to automatically form and monitor Kubernetes Federation, given application topology descriptions in TOSCA (Topology and Orchestration Specification for Cloud Applications), by extending the orchestration tool that automatizes the modeling and instantiation of cloud applications. It also demonstrates the successful federation of the clusters according to the TOSCA specifications and verifies the auto-scaling capability of the configured system through a scenario in which the servers of a sample application are deployed and federated.

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