Scalable Cloud Solutions for Multi-Station Fuel Data Aggregation

Authors: Rohith Varma Vegesna

DOI: https://doi.org/10.5281/zenodo.14880890

Short DOI: https://doi.org/g84935

Country: USA

Full-text Research PDF File:   View   |   Download

Abstract: Scalable cloud-based architectures are vital for managing operational data across multiple fuel stations, especially where each station generates a high volume of dispenser and tank information. This paper explores how an elastic container service (ECS) paired with load balancers can handle fluctuations in data traffic while maintaining low latency and high availability. A containerized microservices approach ensures that each functionranging from dispenser data collection to realtime reconciliationcan be independently scaled and updated. By distributing incoming requests through load balancers, no single service is overwhelmed, and fault isolation is significantly improved. A pilot implementation in an urban environment demonstrates the real-world efficacy of this strategy, emphasizing near realtime data visibility, reduced downtime, and streamlined maintenance. Future directions involve integrating predictive analytics to anticipate demand surges and further refining container orchestration policies for even faster response times.

Keywords: Fuel Stations, ECS, Load Balancers, Microservices, Containerization, Scalability, Real-Time Data, Cloud Computing, Dispenser Monitoring, Data Aggregation

Paper Id: 232134

Published On: 2020-09-08

Published In: Volume 8, Issue 5, September-October 2020

Share this