Optimizing Energy Consumption in Data Centres using AI

Authors

  • Snigdha Gottipati

Keywords:

Artificial Intelligence, data distribution, energy consumption, clustering, prosumers.

Abstract

In the recent era, prosumer growth plays a significant role and makes a lot of advantages and flexibility to create interest in other activities in order to manage the energy to be consumed or produced. As in that kind of system, a lot of data is involved as it needs privacy among the users. In AI, the problem of dependent and identical data distribution problem occurs, and those data contain user information. As that information should be more effective to make a decision-making process by ensuring privacy among the user information. In this paper, a novel AI based data clustering technique is proposed as it improves the degree of data sampling based on multiple iterations. Using this model degree, weight of each client is measure by considering the client distribution of independent and identical problem. Based on the proposed model, communication rounds get reduced, and number of iterations as compared to AIAvg algorithm. Then the data accuracy also gets improved using clustering and weighted clients based on the distribution of non-independent and identical data.    

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Published

27.12.2022

How to Cite

Snigdha Gottipati. (2022). Optimizing Energy Consumption in Data Centres using AI. International Journal of Intelligent Systems and Applications in Engineering, 10(3s), 371–381. Retrieved from https://www.ijisae.org/index.php/IJISAE/article/view/7545

Issue

Vol. 10 No. 3s (2022)

Section

Research Article

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