Design and Implementation of Cloud Computing Platform Monitoring System Based on Nagios

2021 ◽  
pp. 1473-1478
Author(s):  
Jia Liu ◽  
Chengzhang Qu ◽  
Tianhong Zhou
Keyword(s):  
Cloud Computing ◽  
Monitoring System ◽  
Computing Platform ◽  
Design And Implementation ◽  
Cloud Computing Platform

The design of an m-Health monitoring system based on a cloud computing platform

2015 ◽  
Vol 11 (1) ◽  
pp. 17-36 ◽  
Author(s):  
Boyi Xu ◽  
Lida Xu ◽  
Hongming Cai ◽  
Lihong Jiang ◽  
Yang Luo ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Monitoring System ◽  
Health Monitoring ◽  
Health Monitoring System ◽  
Computing Platform ◽  
Cloud Computing Platform

Design and Implementation of Facial Sketch System Based on Cloud Computing Platform and Big Data

2014 ◽  
Vol 651-653 ◽  
pp. 2028-2031
Author(s):  
Yan Jun An ◽  
Yue Hou
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Success Rate ◽  
Computer Technology ◽  
Criminal Investigation ◽  
Computing Platform ◽  
Design And Implementation ◽  
Drawing System ◽  
Cloud Computing Platform ◽  
Search And Recognition

At present, the facial recognition is largely using in the criminal investigation for the identification of suspects, the information from the informants, however, is very hard to obtain the main feature and to draw it accurately because of the affection of mood, light, visual differences and so on. However, with some computer technology, combining the resource from big data and cloud computing platform, the success rate of the search and recognition could be greatly improved. Therefore this article will bring out a facial drawing system based on big data and cloud computing platform.

Optimization Design of Data Collecting and Processing for the Cloud Computing Platform Monitoring System

2015 ◽  
Vol 743 ◽  
pp. 491-495
Author(s):  
G.Z. Xu
Keyword(s):  
Cloud Computing ◽  
Monitoring System ◽  
Optimization Design ◽  
Layered Architecture ◽  
Computing Platform ◽  
Business Association ◽  
Data Collecting ◽  
Cloud Computing Platform

Cloud computing platform monitoring system need to design flexible, scalable data collecting layer and can process the business association. The optimized data Collecting Layer is composed of Agent, including two types of Agent, and divided into three layers. Agent uses plugin mode to monitor each model entities of the cloud computing platform . Disposing Layer which uses MVC layered architecture is divided into three layers, with advantages of low coupling, scalability.

Design and Implementation of Massive Data Retrieving Based on Cloud Computing Platform

2013 ◽  
Vol 303-306 ◽  
pp. 2235-2240 ◽  
Author(s):  
Wei Xiao ◽  
Chun Lei Ji ◽  
Jian Dun Li
Keyword(s):  
Cloud Computing ◽  
Massive Data ◽  
Computing Platform ◽  
Design And Implementation ◽  
Computing Paradigm ◽  
Hybrid Solution ◽  
Great Availability ◽  
Cloud Computing Platform ◽  
Computing Framework ◽  
Low Efficiency

Considering the low efficiency of massive data retrieving in traditional parallel processing, by taking advantage of the great availability of cloud computing paradigm, we propose a hybrid solution based on Map-Reduce model and distributed computing framework--Spark. Moreover, we design and implement this solution in our lab. The results show that the solution can effectively improve the performance of massive data retrieving.

The Design and Implementation of Cloud Computing Model and Platform

2014 ◽  
Vol 631-632 ◽  
pp. 210-217 ◽  
Author(s):  
Jian Jun Jiang ◽  
Zhi Feng Ding
Keyword(s):  
Cloud Computing ◽  
Operating Systems ◽  
Data Center ◽  
Computing Platform ◽  
Design And Implementation ◽  
Computing Model ◽  
Share Data ◽  
User Data ◽  
Cloud Computing Platform ◽  
Cloud Technologies

Cloud computing model, based on cloud technologies, is an evolution to traditional computing model. It fully separates device, operating system, application and user data from each other while freely combines these components to form different computing paths. In cloud computing platform, storage cloud, desktop cloud and application cloud are built in the backend, while user data, operating systems, and applications are deployed in the data center. Therefore, user only needs to focus on data, and is able to access, process and share data with any device, from anywhere and at anytime.

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