scholarly journals Digital Cloud Environment: Present Challenges and Future Forecast

2020 ◽  
Vol 12 (5) ◽  
pp. 82
Author(s):  
Serg Mescheryakov ◽  
Dmitry Shchemelinin ◽  
Konstantin Izrailov ◽  
Victor Pokussov
Keyword(s):  
Data Model ◽  
Capacity Planning ◽  
System Analysis ◽  
System Capacity ◽  
Cloud Environment ◽  
Public Cloud ◽  
Production Environment ◽  
International Telecommunications ◽  
Operational Costs ◽  
Business Metrics

This article addresses the challenges of a digital cloud environment when it comes to global scalability with a large number of remote servers and an unsecure public cloud, such as Amazon. The goal of the study was to work out an approach for evaluating the reasonable system capacity under heavy workload. For that purpose, Zabbix monitoring solution is used and business metrics are applied in relation to existing system ones. A prediction data model is proposed to compute the future forecast of the user activity based on the collected historical statistics and to verify whether capacity adjustment is possible or not. The results of capacity planning are implemented at Genesys International Telecommunications Company. System analysis of the production environment indicates the possibility to downscale the capacity of certain virtual servers, which allowed savings to the annual operational costs of $3500 (50%) for each affected server.

Testbed Platform

2014 ◽  
pp. 192-211
Author(s):  
Deepak Mane
Keyword(s):  
Cloud Services ◽  
Cloud Environment ◽  
Public Cloud ◽  
Production Environment ◽  
New Paradigm ◽  
Software Applications ◽  
On Demand ◽  
Amazon Web Services ◽  
Operational Excellence ◽  
Testing As A Service

Libraries invest millions of dollars in developing and maintaining library applications that are core to their libraries and help them to improve their competitive advantage through operational excellence of libraries. Continuous changes in the library environment forces the library to innovate and optimize their library process, resulting in continuous changes in the software applications that support the library processes. As a consequence, delivering applications rapidly that are defect free, scalable, and reliable becomes challenging. Testing becomes a critical and vital step in the process – not only in terms of coverage but also in terms of performance, security, and usability. Setting up test environments that closely mirror the production environment can be expensive – in terms of hardware, licenses, people to manage library infrastructure and its application. “Testing as a Service” – a new paradigm of Cloud-based “On Demand” testing service can help libraries to address this challenge. This chapter focuses on how libraries can optimize their IT budget through a strategic initiative in the form of “On Demand” testing. This chapter describes Requirements of Testbed Platform, Cloud Testing, and Benefits of testing using cloud environment for library Amazon Web Services – Public Cloud Services.

Testbed Platform

2015 ◽  
pp. 730-748
Author(s):  
Deepak Mane
Keyword(s):  
Cloud Services ◽  
Cloud Environment ◽  
Public Cloud ◽  
Production Environment ◽  
New Paradigm ◽  
Software Applications ◽  
On Demand ◽  
Amazon Web Services ◽  
Operational Excellence ◽  
Testing As A Service

Libraries invest millions of dollars in developing and maintaining library applications that are core to their libraries and help them to improve their competitive advantage through operational excellence of libraries. Continuous changes in the library environment forces the library to innovate and optimize their library process, resulting in continuous changes in the software applications that support the library processes. As a consequence, delivering applications rapidly that are defect free, scalable, and reliable becomes challenging. Testing becomes a critical and vital step in the process – not only in terms of coverage but also in terms of performance, security, and usability. Setting up test environments that closely mirror the production environment can be expensive – in terms of hardware, licenses, people to manage library infrastructure and its application. “Testing as a Service” – a new paradigm of Cloud-based “On Demand” testing service can help libraries to address this challenge. This chapter focuses on how libraries can optimize their IT budget through a strategic initiative in the form of “On Demand” testing. This chapter describes Requirements of Testbed Platform, Cloud Testing, and Benefits of testing using cloud environment for library Amazon Web Services – Public Cloud Services.

A Review on Load Balancing Model Using Best Partition Technique

2017 ◽  
Vol 7 (8) ◽  
pp. 284
Author(s):  
M. Chaitanya ◽  
K. Durga Charan
Keyword(s):  
Cloud Computing ◽  
Fault Tolerance ◽  
Load Balancing ◽  
Load Balance ◽  
Large Impact ◽  
Cloud Environment ◽  
Public Cloud ◽  
The Public ◽  
Partition Technique ◽  
Textual Content

Load balancing makes cloud computing greater knowledgeable and could increase client pleasure. At reward cloud computing is among the all most systems which offer garage of expertise in very lowers charge and available all the time over the net. However, it has extra vital hassle like security, load administration and fault tolerance. Load balancing inside the cloud computing surroundings has a large impact at the presentation. The set of regulations relates the sport idea to the load balancing manner to amplify the abilties in the public cloud environment. This textual content pronounces an extended load balance mannequin for the majority cloud concentrated on the cloud segregating proposal with a swap mechanism to select specific strategies for great occasions.

scholarly journals Fully Automated Cultivation of Adipose-Derived Stem Cells in the StemCellDiscovery—A Robotic Laboratory for Small-Scale, High-Throughput Cell Production Including Deep Learning-Based Confluence Estimation

Processes ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 575
Author(s):  
Jelena Ochs ◽  
Ferdinand Biermann ◽  
Tobias Piotrowski ◽  
Frederik Erkens ◽  
Bastian Nießing ◽  
...  
Keyword(s):  
Stem Cells ◽  
Deep Learning ◽  
High Throughput ◽  
High Speed ◽  
New Technologies ◽  
Human Mesenchymal Stem Cells ◽  
Simulation Software ◽  
System Capacity ◽  
Small Scale ◽  
Production Environment

Laboratory automation is a key driver in biotechnology and an enabler for powerful new technologies and applications. In particular, in the field of personalized therapies, automation in research and production is a prerequisite for achieving cost efficiency and broad availability of tailored treatments. For this reason, we present the StemCellDiscovery, a fully automated robotic laboratory for the cultivation of human mesenchymal stem cells (hMSCs) in small scale and in parallel. While the system can handle different kinds of adherent cells, here, we focus on the cultivation of adipose-derived hMSCs. The StemCellDiscovery provides an in-line visual quality control for automated confluence estimation, which is realized by combining high-speed microscopy with deep learning-based image processing. We demonstrate the feasibility of the algorithm to detect hMSCs in culture at different densities and calculate confluences based on the resulting image. Furthermore, we show that the StemCellDiscovery is capable of expanding adipose-derived hMSCs in a fully automated manner using the confluence estimation algorithm. In order to estimate the system capacity under high-throughput conditions, we modeled the production environment in a simulation software. The simulations of the production process indicate that the robotic laboratory is capable of handling more than 95 cell culture plates per day.

scholarly journals Using ontology merging for the integration of information systems and the production capacity planning system

2019 ◽  
pp. 401-408
Author(s):  
N Yarushkina ◽  
A Romanov ◽  
A Filippov ◽  
A Dolganovskaya ◽  
M Grigoricheva
Keyword(s):  
Information System ◽  
Information Systems ◽  
Relational Database ◽  
Data Model ◽  
Capacity Planning ◽  
Production Capacity ◽  
Semantic Integration ◽  
Data Sources ◽  
Planning System ◽  
Ontology Merging

This article describes the method of integrating information systems of an aircraft factory with the production capacity planning system based on the ontology merging. The ontological representation is formed for each relational database (RDB) of integrated information systems. The ontological representation is formed in the process of analyzing the structure of the relational database of the information system (IS). Based on the ontological representations merging the integrating data model is formed. The integrating data model is a mechanism for semantic integration of data sources.

scholarly journals A Secure Encrypted Classified Electronic Healthcare Data for Public Cloud Environment

2022 ◽  
Vol 32 (2) ◽  
pp. 765-779
Author(s):  
Kirupa Shankar Komathi Maathavan ◽  
Santhi Venkatraman
Keyword(s):  
Cloud Environment ◽  
Public Cloud ◽  
Healthcare Data

Achieving Cloud Security Using a Third Party Auditor and Preserving Privacy for Shared Data Over a Public Cloud

2021 ◽  
pp. 1371-1391
Author(s):  
Vitthal Sadashiv Gutte ◽  
Sita Devulapalli
Keyword(s):  
Cloud Security ◽  
Third Party ◽  
Security Model ◽  
Cloud Environment ◽  
Public Cloud ◽  
Shared Data ◽  
Metadata File ◽  
Efficient Mechanisms ◽  
Different Levels ◽  
Access Security

Correctness of data and efficient mechanisms for data security, while transferring the file to and from Cloud, are of paramount importance in today's cloud-centric processing. A mechanism for correctness and efficient transfer of data is proposed in this article. While processing users request data, a set of attributes are defined and checked. States with attributes at different levels are defined to prevent unauthorized access. Security is provided while storing the data using a chunk generation algorithm and verification of chunks using lightweight Third-Party Auditor (TPA). TPA uses digital signatures to verify user's data that are generated by RSA with MD5 algorithms. The metadata file of generated chunks is encrypted using a modified AES algorithm. The proposed method prevents unauthorized users from accessing the data in the cloud environment, in addition to maintaining data integrity. Results of the proposed cloud security model implementation are discussed.

Sign in / Sign up

Export Citation Format

Share Document