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Corresponding Author

Wael Hadeed

Document Type

Article

Keywords

Fog Computing, E-Commerce, Big data, Data centers, Flink framework

Abstract

Cloud computing has always been an essential part of big data analytics, providing several significant benefits such as pooled resources, availability on-demand, and quick scalability. Nevertheless, handling data-intensive workflows in such highly changing environments is still a problem. Excessively allocating resources may unnecessarily increase the operating cost, while insufficiently allocating resources may cause Service Level Agreement (SLA) violations and drop in the Quality of Service (QoS). This document explores the issues around data center deployment in the fast-changing e-commerce industry where continuous technological increments are vital to satisfying ever-changing customer needs. The main aim is to manufacture a sophisticated resource management technique that involves fog computing in which computing and data processing activities are moved closer to the users, thus resulting in performance and responsiveness. In this paper takes advantage of the Apache Flink tool to carry out the dynamic approach in order to bring about data center optimization under fog computing setups. Evaluation shows that the strategy employed cuts down delay duration considerably, puts a distribution on resource usages and raises reliability of the system when compared to conventional cloud ones. This is the proof of how workflows facilitated by fog enable can significantly boost the pace as well as the continuity of an online business thus reflecting the proposed solution's supremacy and relevance in handling complex applications powered by data that are residing in the nowadays digital era. Overall, the proposed e-commerce framework powered by fog computing and Apache Flink achieves average response times of approximately 5.48 milliseconds and 2 milliseconds over two evaluation periods, with a success rate of 91.6% and an estimated standard deviation of 1.43 milliseconds, highlighting its suitability for real-world, low-latency, and scalable e-commerce applications.

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