Research and design of autonomic computing system model in cloud computing environment

Cloud computing needs to manage a large number of computing resources, while resources scheduling strategy plays a key role in determining the efficiency of cloud computing. evolutionary algorithms (EA) as appropriate tools to optimize multi-objective problems have been applied to optimize Resources Scheduling of cloud computing ,However, studies on improving the convergence ratio and processing time in the most applied algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) in Resources Scheduling domains remain poorly understood. the resource schedule algorithmbased on Artificial Fish Swarm Optimization(AFSA) for Cloud Computing Environment has been designed and implemented after the study on the resource schedule of Cloud Computing. The main idea of improved AFSA is to extend Fish Swarm Optimization to the interacting swarms model by cooperative Models . The improved AFSA probability analysis indicates that searching solution is much more efficient and speeds up the multi-swarm to converge to the global optimum.Finally, the result of the experiment indicates that the scheduling system can improve the efficiency of dispatching resource and the utilization ratio in the Cloud Computing system.

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Design of Cloud Computing Environment for Online Open Course

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.687-691.2867 ◽

2014 ◽

Vol 687-691 ◽

pp. 2867-2870 ◽

Cited By ~ 1

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.

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An improved data leakage detection system in a cloud computing environment

World Journal of Advanced Research and Reviews ◽

10.30574/wjarr.2021.11.2.0385 ◽

2021 ◽

Vol 11 (2) ◽

pp. 321-328

Author(s):

Prisca I. Okochi ◽

Stanley A. Okolie ◽

Juliet N. Odii

Keyword(s):

Cloud Computing ◽

Detection System ◽

Computing System ◽

Sql Server ◽

Time Stamp ◽

Leakage Detection ◽

Computing Environment ◽

Sensitive Data ◽

Cloud Computing Environment ◽

New System

An Improved Data Leakage Detection System is designed to mitigate the leakage of crucial and sensitive data in a cloud computing environment. Generally, leakage of data in computing system has caused a lot of irreparable damage or catastrophe to various institutions or organizations worldwide. Therefore, this research aims at detecting and preventing any intentional or non-intentional data leakages using dynamic password or key for data decryption security mechanisms. To achieve this the OOADM methodology was adopted. The new system was implemented using ASP.net MVC and Microsoft SQL Server Management Studio as the backend. And by incorporating an Audit trail/Transaction log mechanism, the new system monitors the activities within and outside the computing environment with date and time stamp. Hence, the system can be applied in any environment for the prevention and detection of any data leakage.

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Fuzzy Decoupling Energy Efficiency Optimization Algorithm in Cloud Computing Environment

International Journal of Information Technologies and Systems Approach ◽

10.4018/ijitsa.2021070104 ◽

2021 ◽

Vol 14 (2) ◽

pp. 52-69

Author(s):

Xiaohong Wang

Keyword(s):

Energy Efficiency ◽

Cloud Computing ◽

Optimization Algorithm ◽

Computing System ◽

Computing Environment ◽

Cloud Computing Environment ◽

Efficiency Optimization ◽

Cloud Computing System ◽

Computing Performance

With the vigorous development of information technology, cloud computing, as a distributed computing technology, has become a research hotspot in the industry. The cloud computing system has a huge resource pool. In order to meet user-specific quality of service requests, it needs to perform reasonable scheduling of various tasks. Under the premise of ensuring high computing performance and better service quality in the cloud computing environment, system energy efficiency optimization has become a key issue to be promoted in the promotion of cloud computing. The research purpose of this paper is to study the fuzzy decoupling energy efficiency optimization algorithm in cloud computing environment. This paper designs a fuzzy decoupling energy efficiency optimization scheme.

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A Dynamic Dispatching Method of Resource in Cloud Computing Environment

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.418-420.1060 ◽

2011 ◽

Vol 418-420 ◽

pp. 1060-1063

Author(s):

Hong Wei Zhao ◽

Yan Ning Zhu ◽

Yi Chuan Shao

Keyword(s):

Cloud Computing ◽

Computing System ◽

Computing Environment ◽

Cloud Computing Environment ◽

Comprehensive Service ◽

Cloud Computing System ◽

Service Distribution ◽

Balanced Distribution ◽

Dynamic Dispatching ◽

Utilization Ratio

In order to implement the balanced distribution in Cloud Computing system and to improve the utilization ratio of the resource as well as handling up rate of the system, the system of dynamic dispatching system based on Cloud Computing has been designed and implemented after the study on the Cloud Computing. Firstly, a layered loading balancing scheduling mode has been proposed, providing the structure of the dispatching service system. Secondly, a comprehensive service distribution algorithm has been designed and implemented in consideration of respective local service counts, each join points’ performance, current load distribution and semantic. Finally, the result of the experiment indicates that the scheduling system can improve the efficiency of dispatching service and the utilization ratio in the Cloud Computing system.

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