scholarly journals Monitoring and Prediction of SLA for IoT based Cloud

2020 ◽  
Vol 21 (3) ◽  
pp. 349-358
Author(s):  
Vivek Kumar Prasad ◽  
Madhuri D Bhavsar
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
End Users ◽  
Cloud Services ◽  
Cloud Provider ◽  
Peak Time ◽  
Processing Power ◽  
It Resources ◽  
Set Up ◽  
Cloud Resources

Internet of Things (IoT) and cloud computing are the expertise captivating the technology. The most astonishing thing is their interdependence. IoT deals with the production of an additional amount of information that requires transmission of data, storage, and huge infrastructural processing power, posing a solemn delinquent. This is where cloud computing fits into the scenario. Cloud computing can be treated as the utility factor nowadays and can be used by pay as you go manner. As a cloud is a multi-tenant approach, and the resources will be used by multiple users. The cloud resources are required to be monitored, maintained, and configured and set-up as per the need of the end-users. This paper describes the mechanisms for monitoring by using the concept of reinforcement learning and prediction of the cloud resources, which forms the critical parts of cloud expertise in support of controlling and evolution of the IT resources and has been implemented using LSTM. The resource management system coordinates the IT resources among the cloud provider and the end users; accordingly, multiple instances can be created and managed as per the demand and availability of the support in terms of resources. The proper utilization of the resources will generate revenues to the provider and also increases the trust factor of the provider of cloud services. For experimental analysis, four parameters have been used i.e. CPU utilization, disk read/write throughput and memory utilization. The scope of this research paper is to manage the Cloud Computing resources during the peak time and avoid the conditions of the over and under-provisioning proactively.

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 A New Secure Model for Data Protection over Cloud Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Amr M. Sauber ◽  
Passent M. El-Kafrawy ◽  
Amr F. Shawish ◽  
Mohamed A. Amin ◽  
Ismail M. Hagag
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Data Protection ◽  
Cloud Services ◽  
Security And Privacy ◽  
Storage Model ◽  
Cloud Data ◽  
Security Issues ◽  
Data Owner ◽  
Proposed Model

The main goal of any data storage model on the cloud is accessing data in an easy way without risking its security. A security consideration is a major aspect in any cloud data storage model to provide safety and efficiency. In this paper, we propose a secure data protection model over the cloud. The proposed model presents a solution to some security issues of cloud such as data protection from any violations and protection from a fake authorized identity user, which adversely affects the security of the cloud. This paper includes multiple issues and challenges with cloud computing that impairs security and privacy of data. It presents the threats and attacks that affect data residing in the cloud. Our proposed model provides the benefits and effectiveness of security in cloud computing such as enhancement of the encryption of data in the cloud. It provides security and scalability of data sharing for users on the cloud computing. Our model achieves the security functions over cloud computing such as identification and authentication, authorization, and encryption. Also, this model protects the system from any fake data owner who enters malicious information that may destroy the main goal of cloud services. We develop the one-time password (OTP) as a logging technique and uploading technique to protect users and data owners from any fake unauthorized access to the cloud. We implement our model using a simulation of the model called Next Generation Secure Cloud Server (NG-Cloud). These results increase the security protection techniques for end user and data owner from fake user and fake data owner in the cloud.

A Study on Capabilities and Challenges of Fog Computing

2019 ◽  
pp. 249-273
Author(s):  
R. Priyadarshini ◽  
N. Malarvizhi ◽  
E. A. Neeba
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Fog Computing ◽  
End Users ◽  
Information Measure ◽  
New Paradigm ◽  
Control Activity ◽  
Management Functions ◽  
Future Topics

Fog computing is a new paradigm believed to be an extension of cloud computing and services to the sting of the network. Similarly, like Cloud, Fog provides computing, data, storage, and various application services to the connected end-users. Fog computing uses one or a lot of combined end users or nearby end users edge devices to perform the configuration, communication, storage, control activity, and management functions over the infrastructure supported. This new paradigm solves the latency and information measure limitation issues encountered from the cloud computing. Primarily, the architecture of the fog computing is discussed and analyzed during this work and then indicates the connected potential security and trust problems. Then, however such problems are tackled within the existing literature is systematically reportable. Finally, the open challenges, analysis, trends, and future topics of security and trust in fog computing are mentioned.

Introduction to Fog Computing

2019 ◽  
pp. 1-35
Author(s):  
Stojan Kitanov ◽  
Toni Janevski
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Fog Computing ◽  
High Mobility ◽  
End Users ◽  
Mobile Edge Computing ◽  
New Paradigm ◽  
Research Directions ◽  
Intelligent Networking ◽  
High Scalability

Pushing computing, control, data storage, and processing into the cloud has been a key trend in the past decade. However, the cloud alone encounters growing limitations, such as reduced latency, high mobility, high scalability, and real-time execution in order to meet the upcoming computing and intelligent networking demands. A new paradigm called fog computing has emerged to overcome these limits. Fog extends cloud computing and services to the edge of the network. It provides data, computing, storage, and application services to end-users that can be hosted at the network edge. It reduces service latency, and improves QoS/QoE, that results in superior user experience. This chapter is about introduction and overview of fog computing, comparison between fog computing and cloud computing, fog computing and mobile edge computing, possible fog computing architecture, applications of fog computing, and possible research directions.

A Mobile Cloud Middleware to Support Mobility and Cloud Interoperability

2016 ◽  
Vol 7 (1) ◽  
pp. 41-58 ◽  
Author(s):  
Khadija Akherfi ◽  
Hamid Harroud ◽  
Michael Gerndt
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Data Storage ◽  
Mobile Cloud Computing ◽  
Relevant Information ◽  
Cloud Services ◽  
Mobile Cloud ◽  
Computing Power ◽  
Cloud Interoperability

With the recent advances in cloud computing and the improvement in the capabilities of mobile devices in terms of speed, storage, and computing power, Mobile Cloud Computing (MCC) is emerging as one of important branches of cloud computing. MCC is an extension of cloud computing with the support of mobility. In this paper, the authors first present the specific concerns and key challenges in mobile cloud computing. They then discuss the different approaches to tackle the main issues in MCC that have been introduced so far, and finally focus on describing the proposed overall architecture of a middleware that will contribute to providing mobile users data storage and processing services based on their mobile devices capabilities, availability, and usage. A prototype of the middleware is developed and three scenarios are described to demonstrate how the middleware performs in adapting the provision of cloud web services by transforming SOAP messages to REST and XML format to JSON, in optimizing the results by extracting relevant information, and in improving the availability by caching. Initial analysis shows that the mobile cloud middleware improves the quality of service for mobiles, and provides lightweight responses for mobile cloud services.

scholarly journals Towards Distributed Data Management in Fog Computing

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Vasileios Moysiadis ◽  
Panagiotis Sarigiannidis ◽  
Ioannis Moscholios
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Large Scale ◽  
Fog Computing ◽  
Cloud Services ◽  
Smart Devices ◽  
Distributed Data ◽  
Storage Allocation ◽  
Huge Amount ◽  
Distributed Data Storage

In the emerging area of the Internet of Things (IoT), the exponential growth of the number of smart devices leads to a growing need for efficient data storage mechanisms. Cloud Computing was an efficient solution so far to store and manipulate such huge amount of data. However, in the next years it is expected that Cloud Computing will be unable to handle the huge amount of the IoT devices efficiently due to bandwidth limitations. An arising technology which promises to overwhelm many drawbacks in large-scale networks in IoT is Fog Computing. Fog Computing provides high-quality Cloud services in the physical proximity of mobile users. Computational power and storage capacity could be offered from the Fog, with low latency and high bandwidth. This survey discusses the main features of Fog Computing, introduces representative simulators and tools, highlights the benefits of Fog Computing in line with the applications of large-scale IoT networks, and identifies various aspects of issues we may encounter when designing and implementing social IoT systems in the context of the Fog Computing paradigm. The rationale behind this work lies in the data storage discussion which is performed by taking into account the importance of storage capabilities in modern Fog Computing systems. In addition, we provide a comprehensive comparison among previously developed distributed data storage systems which consist of a promising solution for data storage allocation in Fog Computing.

A Structured Method for Security Requirements Elicitation concerning the Cloud Computing Domain

2014 ◽  
Vol 5 (2) ◽  
pp. 20-43 ◽  
Author(s):  
Kristian Beckers ◽  
Isabelle Côté ◽  
Ludger Goeke ◽  
Selim Güler ◽  
Maritta Heisel
Keyword(s):  
Cloud Computing ◽  
System Analysis ◽  
Economic Benefits ◽  
Cloud Services ◽  
Security Requirements ◽  
Cloud System ◽  
Security Requirement ◽  
Analysis Pattern ◽  
It Resources ◽  
Requirements Patterns

Cloud computing systems offer an attractive alternative to traditional IT-systems, because of economic benefits that arise from the cloud's scalable and flexible IT-resources. The benefits are of particular interest for SME's. The reason is that using Cloud Resources allows an SME to focus on its core business rather than on IT-resources. However, numerous concerns about the security of cloud computing services exist. Potential cloud customers have to be confident that the cloud services they acquire are secure for them to use. Therefore, they have to have a clear set of security requirements covering their security needs. Eliciting these requirements is a difficult task, because of the amount of stakeholders and technical components to consider in a cloud environment. Therefore, the authors propose a structured, pattern-based method supporting eliciting security requirements and selecting security measures. The method guides potential cloud customers to model the application of their business case in a cloud computing context using a pattern-based approach. Thus, a potential cloud customer can instantiate our so-called Cloud System Analysis Pattern. Then, the information of the instantiated pattern can be used to fill-out our textual security requirements patterns and individual defined security requirement patterns, as well. The presented method is tool-supported. Our tool supports the instantiation of the cloud system analysis pattern and automatically transfers the information from the instance to the security requirements patterns. In addition, they have validation conditions that check e.g., if a security requirement refers to at least one element in the cloud. The authors illustrate their method using an online-banking system as running example.

Research of Public Service Platform Based on Cloud Computing for Middle Size Enterprises

2014 ◽  
Vol 989-994 ◽  
pp. 5498-5503
Author(s):  
Chun Xiao Wang ◽  
Ying Guo ◽  
Xiu Gang Guo
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Public Service ◽  
Service Management ◽  
Cloud Service ◽  
Cloud Services ◽  
Information Support ◽  
Enterprise Management ◽  
Service Platform ◽  
Development Lifecycle

Based on the research in cross-regional resource scheduling and massive data storage, the article built public service platform including IaaS, PaaS and SaaS. It provided all kinds of management software and business software for middle size enterprise users, and provided the development, testing, deployment platform for software vendors, and provided unified resource management, monitoring and maintenance for platform operators which finally become cloud service platform to support enterprise management and software development lifecycle. This helps to form a self-loop and self-development cloud computing ecosystem, to form the linkage of cloud services production, cloud services consumption and cloud service management, and to provide comprehensive information support for the growth and development of middle size enterprise.

scholarly journals Mobile e-Governance in Cloud

2018 ◽  
Vol 6 (2) ◽  
pp. 46
Author(s):  
Kujtim Mustafa ◽  
Isak Shabani
Keyword(s):  
Cloud Computing ◽  
Developing Countries ◽  
Data Storage ◽  
Cloud Services ◽  
The Internet ◽  
Mobile Data ◽  
Mobile Software ◽  
The People ◽  
Relationship Of ◽  
The Relationship

<p>We are living in the era of internet and smartphones. Almost everybody in developing countries has at least one smartphone or connection to the internet through any other mobile device. So developing mobile software for the people or government is a big chance to make people life easier. The time has become a very important factor for which you can’t even pay for extra time, so making life easier for those people who don’t have time is big chance not losing it. All the data that are generated from the software or services is the best match to store those data on cloud, with which we don’t care about privacy and protection, availability to access them, manipulation of them and so on. In this paper, we describe how this newly emerged paradigm of cloud computing can be helpful for mobile e-Governance. Using cloud of course has a cost, but if you can’t give the same conditions that cloud gives, it is best choice to store the data on cloud. If we use cloud you don’t have to pay for all the IT staff who cares about the data, servers, databases, networks, with those money you can pay for cloud services. We start by an introduction about the cloud and e-Government, continuing with what the benefits and challenges of the e-Government and cloud are computing, the relationship of e-Government and cloud computing, mobile e-Governance in cloud and some examples of some countries that are using mobile e-Government in cloud. <br />Keywords: e-Government, e-Governance, Cloud Computing, Mobile, Data Storage</p>

scholarly journals Minimizing the Cost for Resource Allocation from Multiple Cloud Providers

2021 ◽  
Vol 9 (11) ◽  
pp. 1611-1618
Author(s):  
Manasa Jonnagadla
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Service Providers ◽  
Low Cost ◽  
Hybrid Approach ◽  
Cloud Service ◽  
Cloud Services ◽  
Business Efficiency ◽  
Demand Variability ◽  
Cloud Resources

Abstract: Cloud computing provides streamlined tools for exceptional business efficiency. Cloud service providers typically offer two types of plans: reserved and on-demand. Restricted policies provide low-cost long-term contracting, while order contracts are expensive and ready for short periods. Cloud resources must be delivered wisely to meet current customer demands. Many current works rely on low-cost resource-reserved strategies, which may be under- or over-provisioning. Resource allocation has become a difficult issue due to unfairness causing high availability costs and cloud demand variability. That article suggests a hybrid approach to allocating cloud services to complex customer orders. The strategy was built in two stages: accommodation stages and a flexible structure. By treating each step as an optimization problem, we can reduce the overall implementation cost while maintaining service quality. Due to the uncertain nature of cloud requests, we set up a stochastic Optimization-based approach. Our technique is used to assign individual cloud resources and the results show its effectiveness. Keywords: Cloud computing, Resource allocation, Demand

Sign in / Sign up

Export Citation Format

Share Document