E3S Web Conf.
Volume 412, 2023International Conference on Innovation in Modern Applied Science, Environment, Energy and Earth Studies (ICIES’11 2023)
|Number of page(s)
|17 August 2023
Sustainable MapReduce: Optimizing Security and Efficiency in Hadoop Clusters with Lightweight Cryptography-based Key Management
1 Abdelmalek Essaadi University, Morocco
2 Ibn Tofail University, Morocco
The exponential growth of big data has led to a significant increase in the volume and complexity of data being generated and stored. This trend has created a huge demand for secure storage and processing of big data. Cryptography is a widely used technique for securing data, but traditional cryptography algorithms are often too resource-intensive for big data applications. To address this issue, light weight cryptography algorithms have been developed that are optimized for low computational overhead and low memory utilization. This research paper explores the use of a new sustainable algorithm that utilizes a lightweight cryptographybased key management scheme to optimize MapReduce security and computational efficiency in Hadoop clusters. The proposed sustainable MapReduce algorithm aims to reduce memory and CPU allocation, thereby significantly reducing the energy consumption of Hadoop clusters. The paper emphasizes the importance of reducing energy consumption and enhancing environmental sustainability in big data processing and highlights the potential benefits of using sustainable lightweight cryptography algorithms in achieving these goals. Through rigorous testing and evaluation, the paper demonstrates the effectiveness of the proposed sustainable MapReduce algorithm in improving the energy efficiency and computational performance of Hadoop clusters, making it a promising solution for sustainable big data processing.
Key words: Big Data / Hadoop / Data Security / Sustainable MapReduce / Energy Consumption / Lightweight Cryptography Algorithms / Environmental Sustainability
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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