scholarly journals Efficient Cloud Storage with Data Partitioning and Replication Using Advanced Encryption Standard

2019 ◽  
pp. 223-227
Author(s):  
Abirami. S ◽  
Shanmuga Priya. P
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
High Performance ◽  
Low Cost ◽  
Data Partitioning ◽  
File Access ◽  
Grid Topology ◽  
The Individual ◽  
And Storage ◽  
Aes Encryption Algorithm

Cloud computing associate the computing and storage resources controlled by different operating systems to make available services such as large-scaled data storage and high performance computing to users. The benefits of low-cost, negligible management (from a user's perspective), and greater flexibility come with increased security concerns is one of the most crucial aspects among those prohibiting the wide-spread adoption of cloud computing. The data outsourced to a public cloud must need to be secured. This work gives Division and Replication of Data (DROPs) inside the Cloud for Optimal Performance and Security that judicially fragments user files into portions and replicates them at strategic places in the cloud. The division of a files into fragments is achieved based on a given consumer standards such that the individual fragments do not comprise any meaningful facts. The node separation is ensured by the means of the Grid Topology algorithm. To further improve the retrieval time, replicate fragments over the nodes that generate the highest read/write requests. The data encrypted using AES encryption algorithm. Duplication checking is implementing to provide efficient storage and time based access control for secure file access system.

The Research on Hadoop and Cloud Computing-Based Mass Data Storage Model of Computation

2011 ◽  
Vol 130-134 ◽  
pp. 2899-2902 ◽  
Author(s):  
Fang Peng ◽  
Qing Yun Huang ◽  
Zhao Peng Qian
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Business Model ◽  
Low Cost ◽  
Massive Data ◽  
Distributed Software ◽  
Computer Cluster ◽  
Storage Model ◽  
New Business ◽  
And Storage

Cloud computing as a new business model that allows the user according to their needs using the resource pool which formed by data on a large number of computers. Hadoop, as the distributed software platform is the most widely use of cloud computing. It can run applications on the computer cluster which formed by a large number of low-cost hardware devices, and turn the calculation into data completely then deal with massive data. This article describes the basic framework of Hadoop and the advantages of dealing with massive data, the concept of cloud computing, and research of computing and storage model which base on Hadoop and cloud computing.

Using AI at the Edge and Incremental Machine Learning to Process Onboard Instrument Data

2021 ◽  
Author(s):  
Nicholas Parkyn
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Real Time ◽  
Data Storage ◽  
High Performance ◽  
Heterogeneous Computing ◽  
Low Cost ◽  
Machine Intelligence ◽  
Edge Computing ◽  
Continual Learning

Emerging heterogeneous computing, computing at the edge, machine learning and AI at the edge technology drives approaches and techniques for processing and analysing onboard instrument data in near real-time. The author has used edge computing and neural networks combined with high performance heterogeneous computing platforms to accelerate AI workloads. Heterogeneous computing hardware used is readily available, low cost, delivers impressive AI performance and can run multiple neural networks in parallel. Collecting, processing and machine learning from onboard instruments data in near real-time is not a trivial problem due to data volumes, complexities of data filtering, data storage and continual learning. Little research has been done on continual machine learning which aims at a higher level of machine intelligence through providing the artificial agents with the ability to learn from a non-stationary and never-ending stream of data. The author has applied the concept of continual learning to building a system that continually learns from actual boat performance and refines predictions previously done using static VPP data. The neural networks used are initially trained using the output from traditional VPP software and continue to learn from actual data collected under real sailing conditions. The author will present the system design, AI, and edge computing techniques used and the approaches he has researched for incremental training to realise continual learning.

A New Approach in Cloud Computing User Authentication

Web Services ◽  
2019 ◽  
pp. 1393-1410
Author(s):  
Alaa Hussein Al-Hamami ◽  
Rafal A. Al-Khashab
Keyword(s):  
Cloud Computing ◽  
High Performance ◽  
User Authentication ◽  
Low Cost ◽  
Remote Access ◽  
Security And Privacy ◽  
Main Concern ◽  
Security Measures ◽  
User Privacy ◽  
Is Security

Cloud computing provides the full scalability, reliability, high performance and relatively low cost feasible solution as compared to dedicated infrastructure. These features make cloud computing more attractive to users and intruders. It needs more and complex security measures to protect user privacy and data centers. The main concern in this chapter is security, privacy and trust. This chapter will give a discussion and a suggestion for using cloud computing to preserve security and privacy. The malicious hacker and other threats are considering the major cause of leaking security of the personal cloud due to centralized location and remote accesses to the cloud. According to attacks, a centralized location can be easier target rather than several goals and remote access is insecure technologies which offer a boundary of options for attackers to infiltrate enterprises. The biggest concern is attackers that will use the remote connection as a jumping point to get deeper into an organization.

Architecture for Big Data Storage in Different Cloud Deployment Models

2021 ◽  
pp. 178-208
Author(s):  
Chandu Thota ◽  
Gunasekaran Manogaran ◽  
Daphne Lopez ◽  
Revathi Sundarasekar
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Storage ◽  
High Performance ◽  
Data Services ◽  
Big Data Applications ◽  
Nosql Database ◽  
Amazon Web Services ◽  
Product Domains ◽  
Scalable Database

Cloud Computing is a new computing model that distributes the computation on a resource pool. The need for a scalable database capable of expanding to accommodate growth has increased with the growing data in web world. More familiar Cloud Computing vendors such as Amazon Web Services, Microsoft, Google, IBM and Rackspace offer cloud based Hadoop and NoSQL database platforms to process Big Data applications. Variety of services are available that run on top of cloud platforms freeing users from the need to deploy their own systems. Nowadays, integrating Big Data and various cloud deployment models is major concern for Internet companies especially software and data services vendors that are just getting started themselves. This chapter proposes an efficient architecture for integration with comprehensive capabilities including real time and bulk data movement, bi-directional replication, metadata management, high performance transformation, data services and data quality for customer and product domains.

A Review: Map Reduce Framework for Cloud Computing

2018 ◽  
Vol 7 (4.6) ◽  
pp. 13
Author(s):  
Mekala Sandhya ◽  
Ashish Ladda ◽  
Dr. Uma N Dulhare ◽  
. . ◽  
. .
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Distributed Computing ◽  
Data Storage ◽  
High Performance ◽  
Large Scale ◽  
Distributed Storage ◽  
Large Data ◽  
Mass Data ◽  
Internet Information

In this generation of Internet, information and data are growing continuously. Even though various Internet services and applications. The amount of information is increasing rapidly. Hundred billions even trillions of web indexes exist. Such large data brings people a mass of information and more difficulty discovering useful knowledge in these huge amounts of data at the same time. Cloud computing can provide infrastructure for large data. Cloud computing has two significant characteristics of distributed computing i.e. scalability, high availability. The scalability can seamlessly extend to large-scale clusters. Availability says that cloud computing can bear node errors. Node failures will not affect the program to run correctly. Cloud computing with data mining does significant data processing through high-performance machine. Mass data storage and distributed computing provide a new method for mass data mining and become an effective solution to the distributed storage and efficient computing in data mining. 

Security for the Cloud

2020 ◽  
pp. 68-83
Author(s):  
Shweta Kaushik ◽  
Charu Gandhi
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Smart Phones ◽  
Cloud Environment ◽  
Storage Devices ◽  
Remote Locations ◽  
Confidential Data ◽  
Security Concerns ◽  
Authorized Access ◽  
And Storage

Today's people are moving towards the internet services through cloud computing to acquire their required service, but they have less confidence about cloud computing because all the tasks are handled by the service provider. Cloud system provides features to the owner to store their data on some remote locations and allow only authorized users to access their data according to their access capability. Data security becomes particularly serious in the cloud computing environment because data are scattered in different machines and storage devices including servers, PCs, and various mobile devices such as smart phones. To make the cloud computing be adopted by enterprise, the security concerns of users should be rectified first to make cloud environment trustworthy. The trustworthy environment is the basic prerequisite to win the confidence of users to adopt this technology. However, there are various security concerns that need to be taken care of regarding the trust maintenance between various parties, authorized access of confidential data, data storage privacy, and integrity.

Research on the Design Modes of Cloud Computing in Mobile Learning Systems

2013 ◽  
Vol 380-384 ◽  
pp. 2325-2328
Author(s):  
Chan Juan Liu
Keyword(s):  
Cloud Computing ◽  
Customer Service ◽  
Data Storage ◽  
Mobile Learning ◽  
Low Cost ◽  
Service Multimédia ◽  
Model Cloud ◽  
Network Application ◽  
Effective Network ◽  
Rich Data

As a low-cost, highly effective network application model, Cloud Computing provides a variety of users with virtual and rich data and processing services including data storage , software downloads and maintenance, customer service, multimedia information resource and so on. On the basis of a brief description of cloud computing and its features, this paper focuses on design modes in mobile learning, and explores the educational environment of cloud computing.

Master-Slave Parallel Genetic Algorithm Based on MapReduce Using Cloud Computing

2011 ◽  
Vol 121-126 ◽  
pp. 4023-4027 ◽  
Author(s):  
Guang Ming Li ◽  
Wen Hua Zeng ◽  
Jian Feng Zhao ◽  
Min Liu
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
High Performance ◽  
Low Cost ◽  
Parallel Genetic Algorithm ◽  
Parallel Genetic Algorithms ◽  
Computing Platform ◽  
Speed Up ◽  
Cloud Computing Platform ◽  
High Performance Computer

The implementation platforms of parallel genetic algorithms (PGAs) include high performance computer, cluster and Grid. Contrast with the traditional platform, a Master-slave PGA based on MapReduce (MMRPGA) of cloud computing platform was proposed. Cloud computing is a new computer platform, suites for larger-scale computing and is low cost. At first, describes the design of MMRPGA, in which the whole evolution is controlled by Master and the fitness computing is assigned to Slaves; then deduces the theoretical speed-up of MMRPGA; at last, implements MMRPGA on Hadoop and compares the speed-up with traditional genetic algorithm, the experiment result shows MMRPGA can achieve slightly lower linear speed-up with Mapper’s number.

scholarly journals AN EFFICIENT APPROACH TO IMPLEMENT FEDERATED CLOUDS

2017 ◽  
Vol 10 (13) ◽  
pp. 40
Author(s):  
Pappu Sowmya ◽  
R Kumar
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Low Cost ◽  
Cloud Service ◽  
Cloud Services ◽  
The Internet ◽  
Security Model ◽  
Privacy And Security ◽  
Security Issues ◽  
Internet Users

Cloud computing is one of the trending technologies that provide boundless virtualized resources to the internet users as an important services through the internet, while providing the privacy and security. By using these cloud services, internet users get many parallel computing resources at low cost. It predicted that till 2016, revenues from the online business management spent $4 billion for data storage. Cloud is an open source platform structure, so it is having more chances to malicious attacks. Privacy, confidentiality, and security of stored data are primary security challenges in cloud computing. In cloud computing, ‘virtualization’ is one of the techniques dividing memory into different blocks. In most of the existing systems there is only single authority in the system to provide the encrypted keys. To fill the few security issues, this paper proposed a novel authenticated trust security model for secure virtualization system to encrypt the files. The proposed security model achieves the following functions: 1) allotting the VSM(VM Security Monitor) model for each virtual machine; 2) providing secret keys to encrypt and decrypt information by symmetric encryption.The contribution is a proposed architecture that provides a workable security that a cloud service provider can offer to its consumers. Detailed analysis and architecture design presented to elaborate security model.

scholarly journals Hierarchically Authorized Transactions for Massive Internet-of-Things Data Sharing Based on Multilayer Blockchain

2019 ◽  
Vol 9 (23) ◽  
pp. 5159 ◽  
Author(s):  
Shichang Xuan ◽  
Yibo Zhang ◽  
Hao Tang ◽  
Ilyong Chung ◽  
Wei Wang ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Data Sharing ◽  
Privacy Protection ◽  
High Performance ◽  
The Internet ◽  
Blockchain Technology ◽  
And Storage ◽  
The Internet Of Things

With the arrival of the Internet of Things (IoT) era and the rise of Big Data, cloud computing, and similar technologies, data resources are becoming increasingly valuable. Organizations and users can perform all kinds of processing and analysis on the basis of massive IoT data, thus adding to their value. However, this is based on data-sharing transactions, and most existing work focuses on one aspect of data transactions, such as convenience, privacy protection, and auditing. In this paper, a data-sharing-transaction application based on blockchain technology is proposed, which comprehensively considers various types of performance, provides an efficient consistency mechanism, improves transaction verification, realizes high-performance concurrency, and has tamperproof functions. Experiments were designed to analyze the functions and storage of the proposed system.

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