QoS-aware Resource Provisioning for Big Data Processing in Cloud Computing Environment

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.

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Function of Big Data Processing on E-commerce Development under Cloud Computing Environment

Proceedings of the International Conference on Education, Management and Information Technology ◽

10.2991/icemit-15.2015.8 ◽

2015 ◽

Author(s):

Xianwei Feng

Keyword(s):

Cloud Computing ◽

Big Data ◽

Data Processing ◽

Computing Environment ◽

Big Data Processing ◽

Cloud Computing Environment

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Resource Provisioning and Scheduling of Big Data Processing Jobs

Advances in Data Mining and Database Management - Handbook of Research on Big Data Storage and Visualization Techniques ◽

10.4018/978-1-5225-3142-5.ch014 ◽

2018 ◽

pp. 382-401

Author(s):

Rajni Aron ◽

Deepak Kumar Aggarwal

Keyword(s):

Cloud Computing ◽

Big Data ◽

Data Processing ◽

Research Area ◽

Resource Provisioning ◽

Time Data ◽

Big Data Processing ◽

Cloud Resource Management ◽

Big Data Applications ◽

Cloud Resource

Cloud Computing has become a buzzword in the IT industry. Cloud Computing which provides inexpensive computing resources on the pay-as-you-go basis is promptly gaining momentum as a substitute for traditional Information Technology (IT) based organizations. Therefore, the increased utilization of Clouds makes an execution of Big Data processing jobs a vital research area. As more and more users have started to store/process their real-time data in Cloud environments, Resource Provisioning and Scheduling of Big Data processing jobs becomes a key element of consideration for efficient execution of Big Data applications. This chapter discusses the fundamental concepts supporting Cloud Computing & Big Data terms and the relationship between them. This chapter will help researchers find the important characteristics of Cloud Resource Management Systems to handle Big Data processing jobs and will also help to select the most suitable technique for processing Big Data jobs in Cloud Computing environment.

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Resource Provisioning and Scheduling of Big Data Processing Jobs

Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing ◽

10.4018/978-1-7998-5339-8.ch083 ◽

2021 ◽

pp. 1694-1713

Author(s):

Rajni Aron ◽

Deepak Kumar Aggarwal

Keyword(s):

Cloud Computing ◽

Big Data ◽

Data Processing ◽

Research Area ◽

Resource Provisioning ◽

Time Data ◽

Big Data Processing ◽

Cloud Resource Management ◽

Big Data Applications ◽

Cloud Resource

Cloud Computing has become a buzzword in the IT industry. Cloud Computing which provides inexpensive computing resources on the pay-as-you-go basis is promptly gaining momentum as a substitute for traditional Information Technology (IT) based organizations. Therefore, the increased utilization of Clouds makes an execution of Big Data processing jobs a vital research area. As more and more users have started to store/process their real-time data in Cloud environments, Resource Provisioning and Scheduling of Big Data processing jobs becomes a key element of consideration for efficient execution of Big Data applications. This chapter discusses the fundamental concepts supporting Cloud Computing & Big Data terms and the relationship between them. This chapter will help researchers find the important characteristics of Cloud Resource Management Systems to handle Big Data processing jobs and will also help to select the most suitable technique for processing Big Data jobs in Cloud Computing environment.

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Workflow Scheduling for Scientific Application in Homogeneous Cloud Environment

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v7i7.114 ◽

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.

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