Towards a Model-Driven Solution to the Vendor Lock-In Problem in Cloud Computing

2013 ◽  
Author(s):  
Gabriel Costa Silva ◽  
Louis M. Rose ◽  
Radu Calinescu
Keyword(s):  
Cloud Computing ◽  
Model Driven ◽  
Lock In

Modernizing Legacy Systems

2018 ◽  
Vol 10 (2) ◽  
pp. 50-60
Author(s):  
Aparna Vijaya ◽  
Neelanarayanan Venkataraman
Keyword(s):  
Cloud Computing ◽  
Legacy Systems ◽  
Pilot Projects ◽  
Model Driven ◽  
Low Costs ◽  
Lock In ◽  
Model Driven Approach ◽  
Cloud Applications ◽  
The Way

Cloud computing is a paradigm which has changed the way organizations develop, manage, and deploy their applications. Most of the resources are available at low costs in this technology and it creates new opportunities for organizations to move their existing applications to the cloud for modernization. But this modernization also comes at a price. The authors present a model-driven approach to address the challenges in application modernization and focus on the application migration to cloud. Most of the cloud applications are very specific to a particular vendor's features or services. The proposed methodology addresses the challenge of vendor lock-in also. The authors present their theoretical details and experience with two pilot projects where they have applied the proposed approach.

Formal Metamodeling for Secure Model-Driven Engineering

2021 ◽  
Vol 12 (2) ◽  
pp. 46-67
Author(s):  
Liliana Maria Favre
Keyword(s):  
Cloud Computing ◽  
Formal Specifications ◽  
Model Driven Engineering ◽  
Model Driven ◽  
Transformation Rules ◽  
Systematic Development ◽  
Definition Of ◽  
Context Specific ◽  
Theoretical Foundations

Systems and applications aligned with new paradigms such as cloud computing and internet of the things are becoming more complex and interconnected, expanding the areas in which they are susceptible to attacks. Their security can be addressed by using model-driven engineering (MDE). In this context, specific IoT or cloud computing metamodels emerged to support the systematic development of software. In general, they are specified through semiformal metamodels in MOF style. This article shows the theoretical foundations of a method for automatically constructing secure metamodels in the context of realizations of MDE such as MDA. The formal metamodeling language Nereus and systems of transformation rules to bridge the gap between formal specifications and MOF are described. The main contribution of this article is the definition of a system of transformation rules called NEREUStoMOF for transforming automatically formal metamodeling specifications in Nereus to semiformal-MOF metamodels annotated in OCL.

Standardization

2014 ◽  
pp. 75-96
Keyword(s):  
Cloud Computing ◽  
World Wide ◽  
Cloud Provider ◽  
Main Question ◽  
Hybrid Cloud ◽  
Cloud Infrastructure ◽  
The World ◽  
Cloud Interoperability ◽  
Lock In ◽  
Computing Landscape

The importance of cloud computing standards is the same as the World Wide Web standardization. There are plenty of prevalent standards around cloud computing that make different aspects of cloud computing possible. Standardization is a key answer and solution to the main question in this book (i.e., whether cloud computing will survive and remain on IT trends track or not). Standardization will bring interoperability, integration, and portability to the cloud computing landscape. With these three features, the main elements of IT (i.e., computation and data) can move from one cloud provider to another. Therefore, it eliminates vendor lock-in that is one of the barriers in cloud adoption. In addition, cloud interoperability will minimize cloud fragmentation. We need interoperability and portability to achieve cloud federation and to build hybrid cloud. In addition, there is still no de facto standard for moving workloads or data among different clouds. Cloud standardization needs to be addressed at various layers of a cloud infrastructure such as: virtual machine format, data, interface, context, and identity layers. This chapter reviews the emerging standards from the perspective of various organizations and standard bodies.

scholarly journals Survey on security threats in mobile cloud computing

2018 ◽  
Vol 7 (1.9) ◽  
pp. 238
Author(s):  
S. Iniyan ◽  
M. Senthilraja ◽  
R. Srinivasan ◽  
A. Palaniraj
Keyword(s):  
Cloud Computing ◽  
Mobile Cloud Computing ◽  
Security And Privacy ◽  
Computation Offloading ◽  
Mobile Cloud ◽  
Mobile Environment ◽  
Seamless Connectivity ◽  
Fast Development ◽  
Lock In ◽  
Privacy Issues

Cell phones are turning into a basic piece of our day by day life because of most proficient and powerful specialized devices without time and space boundation. Everybody has a portable, tablet, tablet with calling office i.e. Fablet. Distributed computing (DC) has been broadly perceived as the cutting edge's registering foundation with the fast development of portable applications and the support of Cloud Computing for an assortment of administrations, the Mobile Cloud Computing (MCC) is presented as an incorporation of Cloud Computing into the Mobile Environment. Portable Cloud Computing is picking up stream. MCC is alluded to as the framework where both the information stockpiling and the information handling occur outside the cell phone. In MCC condition, Cloud Computing, Mobile Computing and Application confront a few difficulties like Mobile Computation Offloading, Seamless Connectivity, Vendor/Data Lock-in, Long WAN Latency, Live VM (Virtual Machine) relocation issues, Low Bandwidth, Energy-Efficient Transmissions and Trust-Security and Privacy Issues. In this paper, I have talked about around a few difficulties and issues identified with the Mobile Cloud Computing. This paper gives data about Mobile Cloud Computing Application, Security and Issues.

scholarly journals A model-driven framework for data-driven applications in serverless cloud computing

PLoS ONE ◽  
2020 ◽  
Vol 15 (8) ◽  
pp. e0237317
Author(s):  
Fatima Samea ◽  
Farooque Azam ◽  
Muhammad Rashid ◽  
Muhammad Waseem Anwar ◽  
Wasi Haider Butt ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Data Driven ◽  
Model Driven

Model-Driven Open Ecological Cloud Enterprise Resource Planning

2021 ◽  
Vol 18 (3) ◽  
pp. 82-99
Author(s):  
Yi Zhang ◽  
Bo Hu ◽  
YIwen Zhang
Keyword(s):  
Cloud Computing ◽  
Enterprise Resource Planning ◽  
Resource Planning ◽  
Reference Architecture ◽  
Enterprise Information System ◽  
Enterprise Information ◽  
Erp System ◽  
Model Driven ◽  
Development Approach ◽  
Faster Development

Cloud enterprise resource planning (Cloud ERP) is an internet- and cloud computing-based enterprise information system developed on the cloud platform. Cloud ERP has lower costs and shorter development time compared with traditional ERP system, but it remains in a state of information isolated island. To maximize the advantages of cloud computing and make up the deficiency of traditional ERP systems, it is necessary to break down the "wall" between enterprises, making cloud ERP enter a more open and interconnected ecological environment. The model-driven development approach contributes to a better resilient scheduling capability of ERP system, leading to faster development and deployment of it. In this article, the authors propose a “knowledge + data” model-driven open ecological cloud ERP and explain the definition and functions of each model layer. Finally, the effectiveness of model layers is demonstrated in the open ecological cloud ERP reference architecture.

Model-Driven Automated Error Recovery in Cloud Computing

2011 ◽  
pp. 136-155 ◽  
Author(s):  
Yu Sun ◽  
Jules White ◽  
Jeff Gray ◽  
Aniruddha Gokhale
Keyword(s):  
Cloud Computing ◽  
Error Detection ◽  
Error Recovery ◽  
Inference Engine ◽  
Innovative Approach ◽  
Time Model ◽  
Model Driven ◽  
Recovery Pattern ◽  
On Demand ◽  
Run Time

Cloud computing provides a platform that enables users to utilize computation, storage, and other computing resources on-demand. As the number of running nodes in the cloud increases, the potential points of failure and the complexity of recovering from error states grows correspondingly. Using the traditional cloud administrative interface to manually detect and recover from errors is tedious, time-consuming, and error prone. This chapter presents an innovative approach to automate cloud error detection and recovery based on a run-time model that monitors and manages the running nodes in a cloud. When administrators identify and correct errors in the model, an inference engine is used to identify the specific state pattern in the model to which they were reacting, and to record their recovery actions. An error detection and recovery pattern can be generated from the inference and applied automatically whenever the same error occurs again.

Cloud Computing for Earth Observation

2015 ◽  
pp. 1204-1230
Author(s):  
Roberto Cossu ◽  
Claudio Di Giulio ◽  
Fabrice Brito ◽  
Dana Petcu
Keyword(s):  
Cloud Computing ◽  
Earth Observation ◽  
Cloud Services ◽  
Grid Services ◽  
Efficient Storage ◽  
Technical Details ◽  
Earth Observation Satellites ◽  
Lock In ◽  
The Impact

This chapter elaborates on the impact and benefits Cloud Computing may have on Earth Observation. Earth Observation satellites generate in fact Tera- to Peta-bytes of data, and Cloud Computing provides many capabilities that allow an efficient storage and exploitation of such data. Several scenarios related to Earth Observation activities are analyzed in order to identify the possible benefits from the adoption of Cloud Computing. As concrete proofs-of-concept, several activities related to Cloud Computing in the context of Earth Observation are exposed and discussed. Technical details are provided for a particular framework used by Earth Observation applications that has made the transition from using Grid services towards using Cloud services. A special attention is given to the avoidance of the vendor-lock-in problem.

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