scholarly journals Design and implementation of endogenous security container based on union file system

2021 ◽  
Vol 2078 (1) ◽  
pp. 012080
Author(s):  
Fukang Xing ◽  
Zheng Zhang ◽  
Bolin Ma ◽  
Bingzheng Li
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Fault Tolerance ◽  
Data Processing ◽  
File System ◽  
Experimental Results ◽  
Computing Environment ◽  
Big Data Processing ◽  
Cloud Computing Environment ◽  
Design And Implementation

Abstract In order to solve the increasing attacks on container file system and the IO errors of containers in big data processing scenarios in cloud computing environment, a scheme based on the idea of heterogeneous redundancy in endogenous security and transformation of container union file system was proposed to improve the security and fault tolerance of containers. Based on the above scheme, experiments are carried out on Docker, the most popular container technology, and OverlayFS, the most representative union file system. The experimental results show that this scheme can improve the security and fault tolerance of containers on the premise of ensuring availability, and realize the endogenous security of containers.

Workflow Scheduling for Scientific Application in Homogeneous Cloud Environment

2017 ◽  
Vol 7 (7) ◽  
pp. 137
Author(s):  
. Monika ◽  
Pardeep Kumar ◽  
Sanjay Tyagi
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Large Data ◽  
Workflow Scheduling ◽  
Cloud Environment ◽  
Computing Environment ◽  
Scientific Application ◽  
Cloud Computing Environment ◽  
Flow Of Information

In Cloud computing environment QoS i.e. Quality-of-Service and cost is the key element that to be take care of. As, today in the era of big data, the data must be handled properly while satisfying the request. In such case, while handling request of large data or for scientific applications request, flow of information must be sustained. In this paper, a brief introduction of workflow scheduling is given and also a detailed survey of various scheduling algorithms is performed using various parameter.

Algorithm of Text Categorization Based on Cloud Computing

2013 ◽  
Vol 311 ◽  
pp. 158-163 ◽  
Author(s):  
Li Qin Huang ◽  
Li Qun Lin ◽  
Yan Huang Liu
Keyword(s):  
Cloud Computing ◽  
Text Categorization ◽  
Experimental Results ◽  
Support Vector ◽  
Computing Environment ◽  
Mapreduce Framework ◽  
Cloud Computing Environment ◽  
Environment Map ◽  
Vector Machines ◽  
Parallel Text

MapReduce framework of cloud computing has an effective way to achieve massive text categorization. In this paper a distributed parallel text training algorithm in cloud computing environment based on multi-class Support Vector Machines(SVM) is designed. In cloud computing environment Map tasks realize distributing various types of samples and Reduce tasks realize the specific SVM training. Experimental results show that the execution time of text training decreases with the number of Reduce tasks increasing. Also a parallel text classifying based on cloud computing is designed and implemented, which classify the unknown type texts. Experimental results show that the speed of text classifying increases with the number of Map tasks increasing.

NoSQL Databases

2014 ◽  
pp. 186-215 ◽  
Author(s):  
Ganesh Chandra Deka
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Processing ◽  
Open Source ◽  
Data Storage ◽  
Big Data Processing ◽  
Nosql Databases ◽  
Data Intensive ◽  
Huge Data ◽  
Data Intensive Applications

NoSQL databases are designed to meet the huge data storage requirements of cloud computing and big data processing. NoSQL databases have lots of advanced features in addition to the conventional RDBMS features. Hence, the “NoSQL” databases are popularly known as “Not only SQL” databases. A variety of NoSQL databases having different features to deal with exponentially growing data-intensive applications are available with open source and proprietary option. This chapter discusses some of the popular NoSQL databases and their features on the light of CAP theorem.

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