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IJSTR >> Volume 9 - Issue 9, September 2020 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Big Data Analytics Using Serverless Computing - A Personalized Recommendation System Case Study

[Full Text]

 

AUTHOR(S)

Md. Mijanur Rahman, Md. Hasibul Hasan

 

KEYWORDS

Big Data Processing Architecture, Hierarchical Recurrent Neural Network (HRNN), Amazon Personalization, Serverless cloud computing, Amazon Web Service, Movielens, Scalability.

 

ABSTRACT

The enterprises face challenges to process and get insight from big data. It is very costly to compute and manage massive amounts of data. So, Serverless is such a technology that helps to analyze big data with low cost and high performance. Serverless cloud providers manage the operating system, servers, hardware and execute codes. Developers focus only on writing code rather than managing infrastructure. Serverless development has drawn a lot of attention in the market because customers only charged for executing code. Still, all users are not getting benefit from the Serverless technology due to appropriate solution architecture. Mostly an expert architect can ensure scalability, security, cost efficiency, etc. So users often pay for the right architecture to compute and store data in the Serverless cloud platforms. An architecture has been proposed with reduce charge and improve the performance of big data processing using Serverless technology and it is made using Amazon Web Services (AWS). The proposed architecture is evaluated using a real-world use case. As a case study, Movielens data are used in our model for personalized recommendation using Amazon personalized Hierarchical Recurrent Neural Networks (HRNN) algorithm.

 

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