Implementation and Testing of Failure Recovery Based on Backup Resource Sharing Model for Distributed Cloud Computing System

2018 ◽  
Author(s):  
Takehiro Sato ◽  
Fujun He ◽  
Eiji Oki ◽  
Takashi Kurimoto ◽  
Shigeo Urushidani
Keyword(s):  
Cloud Computing ◽  
Resource Sharing ◽  
Computing System ◽  
Failure Recovery ◽  
Cloud Computing System ◽  
Distributed Cloud

Design of Cloud Computing Environment for Online Open Course

2014 ◽  
Vol 687-691 ◽  
pp. 2867-2870 ◽  
Author(s):  
Xiao Yong Zhao ◽  
Chun Rong Yang
Keyword(s):  
Cloud Computing ◽  
Resource Sharing ◽  
Security Analysis ◽  
Computing System ◽  
System Structure ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Cloud Computing System ◽  
Traditional Mode ◽  
Open Courses

The rise of Massive Open Online Course (MOOC) has enabled open courses to overcome the shortcomings of its traditional mode. Interactions and communications have become important elements in online open courses right now. Cloud computing is a new platform for MOOC development, which is extension of the distribution computing, the parallel computing and the grid computing, settling the problem of various resource sharing. In this paper, the design of cloud computing environments is showed with the cloud computing system structure, network security analysis of cloud computing, and map-reduce program mode, which forms the model of cloud computing environment.

A Resource Discovery Mechanism on Cloud Computing System

2012 ◽  
Vol 220-223 ◽  
pp. 2941-2944
Author(s):  
Hong Wei Zhao
Keyword(s):  
Cloud Computing ◽  
Resource Sharing ◽  
Computing System ◽  
Resource Discovery ◽  
Distribution Method ◽  
Comprehensive Service ◽  
Cloud Computing System ◽  
Service Resource ◽  
Current Loading ◽  
Join Points

Cloud Computing is an efficient way to resolve the resource sharing and cooperative work in distributed environments. Considering the disadvantages of traditional Scheduling method and the characteristics of Cloud Computing System, a resource discovery mechanism has been designed and implemented. Firstly, a calculation method based on each join points’ loading has been proposed, providing the Formula of method. Secondly, a comprehensive service resource distribution method has been designed and implemented in consideration of respective service resource counts, each join points’ performance and current loading distribution. Finally, the result of the experiment indicates that the scheduling system can improve the efficiency of dispatching service resource and the utilization ratio of distributed service resource on Cloud Computing System.

scholarly journals Prediction of Cloud Computing Resources Based on the Open Source Monitoring System

2020 ◽  
Vol 6 (3) ◽  
pp. 100-106
Author(s):  
K. Kucherova
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Source Monitoring ◽  
Computing System ◽  
Operating Conditions ◽  
Software Products ◽  
Database Structure ◽  
Cloud Computing System ◽  
Distributed Cloud ◽  
Globally Distributed

The paper describes the universal approach for monitoring the data storage of a globally distributed cloud computing system, which allows you to automate creation of new metrics in the system and predict their behavior for the end users. Since the existing monitoring software products provide built-in scheme only for system metrics like RAM, CPU, disk drives, network traffic, but don’t offer solutions for business functions, IT companies have to design specialized database structure (DB). The data structure proposed in this paper for storing the monitoring statistics is universal and allows you to save resources when orginizing database monitoring on the scale of the GDCCS. The goal of the research is to develop a universal model for monitoring and forecasting of data storage in a globally distributed cloud computing system and its adequacy to real operating conditions.

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