Multi-cloud Management: Technologies, Tools, and Techniques

2018 ◽  
pp. 219-240 ◽  
Author(s):  
Pethuru Raj ◽  
Anupama Raman
Keyword(s):  
Cloud Management ◽  
Tools And Techniques ◽  
Multi Cloud

Performance Evaluation of Multi-Cloud Management and Control Systems

2016 ◽  
Vol 5 (1) ◽  
pp. 9-18 ◽  
Author(s):  
Lav Gupta ◽  
Raj Jain ◽  
Mohammed Samaka ◽  
Aiman Erbad ◽  
Deval Bhamare
Keyword(s):  
Performance Evaluation ◽  
Control Systems ◽  
Cloud Management ◽  
And Control ◽  
Multi Cloud

A Framework for Template Driven Automatic Generated Platforms

2013 ◽  
Vol 756-759 ◽  
pp. 3904-3908
Author(s):  
Shu Hu ◽  
Jing Li ◽  
Hu Song
Keyword(s):  
Infrastructure Management ◽  
Computing Technology ◽  
It Industry ◽  
Resources Management ◽  
Management Platform ◽  
Self Help ◽  
Cloud Management ◽  
Technical Architecture ◽  
Architecture Development ◽  
Multi Cloud

In recent years, cloud computing technology has become the most popular field in IT industry, and it has changed the traditional IT technical architecture, development and deployment model in enterprise. Existing cloud management platforms tend to focus only on a single-level resources management, lack of a management platform that combines infrastructure resources, application platform deployment and monitoring services. This paper has designed a deployment-architecture that supports application platform in multi-cloud environment. It helps users deploy the required platform dynamically via self-help tool, frees users from infrastructure management, and provides common and inheritable deployment architecture for infrastructure environment.

scholarly journals Multi-Cloud Management Strategies for Simulating IoT Applications

2019 ◽  
Vol 24 (1) ◽  
pp. 83-103 ◽  
Author(s):  
András Márkus ◽  
József Dániel Dombi
Keyword(s):  
Management Strategies ◽  
Sensor Data ◽  
Smart Devices ◽  
Cloud Systems ◽  
Selection Strategies ◽  
Cloud Management ◽  
Cloud Technologies ◽  
The Internet Of Things ◽  
Multi Cloud ◽  
Application Execution

The Internet of Things (IoT) paradigm is closely coupled with cloud technologies, and the support for managing sensor data is one of the primary concerns of Cloud Computing. IoT-Cloud systems are widely used to manage sensors and different smart devices connected to the cloud, hence a large amount of data is generated by these things that need to be efficiently stored and processed. Simulation platforms have the advantage of enabling the investigation of complex systems without the need of purchasing and installing physical resources. In our previous work, we chose the DISSECT-CF simulator to model IoT-Cloud systems, and we also introduced provider policies to enable cost-aware policies resource management. The aim of this paper is to further extend the simulation capabilities of this tool by enabling multi-cloud management. In this paper we introduce four cloud selection strategies aimed to reduce application execution time and utilization costs. We detail our proposed method towards multi-cloud extension, and evaluate defined strategies through a meteorological application.

scholarly journals Adaptive management of applications across multiple clouds: The SeaClouds Approach

2018 ◽  
Author(s):  
Antonio Brogi ◽  
Jose Carrasco ◽  
Javier Cubo ◽  
Elisabetta Di Nitto ◽  
Francisco Durán ◽  
...  
Keyword(s):  
Adaptive Management ◽  
Research Project ◽  
Cloud Management ◽  
Present Context ◽  
And Migration ◽  
Multiple Clouds ◽  
Heterogeneous Cloud ◽  
Multi Cloud ◽  
The Eu

How to deploy and manage, in an efficient and adaptive way, complex applications across multiple heterogeneous cloud platforms is one of the problems that have emerged with the cloud revolution. In this paper we present context, motivations and objectives of the EU research project SeaClouds, which aims at enabling a seamless adaptive multi-cloud management of complex applications by supporting the distribution, monitoring and migration of application modules over multiple heterogeneous cloud platforms. After positioning SeaClouds with respect to related cloud initiatives, we present the SeaClouds architecture and discuss some of its aspect, such as the use of the OASIS standard TOSCA and the compatibility with the OASIS CAMP initiative.

scholarly journals The cloud application modelling and execution language

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Achilleas P. Achilleos ◽  
Kyriakos Kritikos ◽  
Alessandro Rossini ◽  
Georgia M. Kapitsaki ◽  
Jörg Domaschka ◽  
...  
Keyword(s):  
Technology Acceptance ◽  
Financial Services ◽  
Cloud Resource Management ◽  
Modelling Languages ◽  
Cloud Management ◽  
Cloud Application ◽  
Lock In Effect ◽  
Acceptance Model ◽  
Multiple Clouds ◽  
Multi Cloud

AbstractCloud computing offers a flexible pay-as-you-go model for provisioning application resources, which enables applications to scale on-demand based on the current workload. In many cases, though, users face the single vendor lock-in effect, missing opportunities for optimal and adaptive application deployment across multiple clouds. Several cloud modelling languages have been developed to support multi-cloud resource management, but still they lack holistic cloud management of all aspects and phases. This work defines the Cloud Application Modelling and Execution Language (CAMEL), which (i) allows users to specify the full set of design time aspects for multi-cloud applications, and (ii) supports the models@runtime paradigm that enables capturing an application’s current state facilitating its adaptive provisioning. CAMEL has been already used in many projects, domains and use cases due to its wide coverage of cloud management features. Finally, CAMEL has been positively evaluated in this work in terms of its usability and applicability in several domains (e.g., data farming, flight scheduling, financial services) based on the technology acceptance model (TAM).

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