Session details: The 3rd Annual Workshop on Distributed Cloud Computing (DCC 2015)

2015 ◽  
Vol 43 (3) ◽  
Keyword(s):  
Cloud Computing ◽  
Distributed Cloud

Using Distributed Cloud Computing to Solve Resource-Intensive Tasks

2021 ◽  
Vol 12 (5) ◽  
pp. 233-254
Author(s):  
D. Yu. Bulgakov ◽  
Keyword(s):  
Cloud Computing ◽  
Point Of View ◽  
Free Software ◽  
Production Environment ◽  
Learning Models ◽  
Python Programming Language ◽  
Task Processing ◽  
Python Programming ◽  
Distributed Cloud ◽  
Machine Learning Models

A method for solving resource-intensive tasks that actively use the CPU, when the computing resources of one server become insufficient, is proposed. The need to solve this class of problems arises when using various machine learning models in a production environment, as well as in scientific research. Cloud computing allows you to organize distributed task processing on virtual servers that are easy to create, maintain, and replicate. An approach based on the use of free software implemented in the Python programming language is justified and proposed. The resulting solution is considered from the point of view of the theory of queuing. The effect of the proposed approach in solving problems of face recognition and analysis of biomedical signals is described.

scholarly journals Multi-Objective Service Placement Scheme Based on Fuzzy-AHP System for Distributed Cloud Computing

2019 ◽  
Vol 9 (17) ◽  
pp. 3550 ◽  
Author(s):  
A-Young Son ◽  
Eui-Nam Huh
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Response Time ◽  
Data Centers ◽  
Cloud Data ◽  
Multi Objective ◽  
Service Placement ◽  
Service Response Time ◽  
Cloud Data Centers ◽  
Distributed Cloud

With the rapid increase in the development of the cloud data centers, it is expected that massive data will be generated, which will decrease service response time for the cloud data centers. To improve the service response time, distributed cloud computing has been designed and researched for placement and migration from mobile devices close to edge servers that have secure resource computing. However, most of the related studies did not provide sufficient service efficiency for multi-objective factors such as energy efficiency, resource efficiency, and performance improvement. In addition, most of the existing approaches did not consider various metrics. Thus, to maximize energy efficiency, maximize performance, and reduce costs, we consider multi-metric factors by combining decision methods, according to user requirements. In order to satisfy the user’s requirements based on service, we propose an efficient service placement system named fuzzy- analytical hierarchical process and then analyze the metric that enables the decision and selection of a machine in the distributed cloud environment. Lastly, using different placement schemes, we demonstrate the performance of the proposed scheme.

Secure and Effective Key Management Using Secret Sharing Schemes in Cloud Computing

2020 ◽  
Vol 16 (1) ◽  
pp. 1-15
Author(s):  
Shahin Fatima ◽  
Shish Ahmad
Keyword(s):  
Cloud Computing ◽  
Secret Sharing ◽  
Key Management ◽  
Divided Difference ◽  
Threshold Value ◽  
Secret Sharing Schemes ◽  
Sharing Scheme ◽  
Random Threshold ◽  
Crucial Problem ◽  
Distributed Cloud

Security is a crucial problem in Cloud computing. Storing and accessing the data in the Cloud is very popular nowadays but the security of data is still lagging behind. Secret sharing schemes are widely used to improve the security of data. In this article, a threshold secret sharing scheme using Newton divided difference interpolating polynomial (TSSNIP) is proposed in a distributed Cloud environment to enhance security of keys used for encryption. The proposed method uses a Newton divided difference interpolating polynomial for key splitting and key reconstruction. A threshold value is used to reconstruct the shares in secret sharing schemes. The proposed work made use of dynamic and random threshold generation method to ensure security of key. The experimental output shows reduced execution time, better security, efficiency, and robustness in the proposed scheme. Furthermore, the proposed scheme also outperformed other secret sharing schemes.

Clustering based virtual machines placement in distributed cloud computing

2017 ◽  
Vol 66 ◽  
pp. 1-10 ◽  
Author(s):  
Jiangtao Zhang ◽  
Xuan Wang ◽  
Hejiao Huang ◽  
Shi Chen
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Distributed Cloud
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