Latency Estimation of Big Data Processing Under the MapReduce Framework with Coupling Effects

Lin, Di; Cai, Lingshuang; Zhang, Xiaofeng; Xiao, Zhang; Huo, Jiazhi

doi:10.1007/978-981-15-0187-6_12

Cited by 1 publication

(1 citation statement)

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“…Recently, the MapReduce framework, which enables the fulfillment of the indicated requirements, is gaining popularity. A significant number of researchers point to the significant benefits of using parallel processing paradigms based on the Apache Hadoop MapReduce programming platform in processing Big Data (see e.g., Lin et al, 2020;Maitrey & Jha, 2015;Dittrich & Quiané-Ruiz, 2012). Hadoop MapReduce is a programming approach that allows the implementation of parallel processing algorithms using multiple computing units (nodes) organized in a cluster architecture.…”

Section: Data Analysis Procedures and Algorithmsmentioning

confidence: 99%

Assessment of it Systems Architecture in the Context of Big Data Processing for Smart Cities Development

Szczepaniuk¹,

Szczepaniuk²

2022

Journal of Security and Sustainability Issues

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Effective use of Big Data can significantly support the development of smart cities and the new digital economy. The aim of the article is a multi-criteria evaluation of IT systems in terms of Big Data processing, taking into account the support for the development of smart cities. The article includes theoretical and empirical research. The adopted criteria for assessing the architecture of IT systems relate to barriers to the implementation of the digital economy in smart cities and the guidelines of international data strategies. The evaluation covered, among other things, cybersecurity and the effectiveness of organizing, storing, and producing new information. The research results allowed us to identify the key factors of Big Data processing efficiency. Based on the research results, an effective model of Big Data processing in organizations was developed. In particular, various data models were analyzed as one of the main elements of software architecture of information systems. The research also focused on data processing techniques such as data warehousing, machine learning, and distributed computing. The efficiency factors of IT systems identified in the research reduce barriers to developing global data strategies and smart cities.

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Section: Data Analysis Procedures and Algorithmsmentioning

confidence: 99%