Multi-cloud Load Distribution for Three-tier Applications

Adekunbi Adewojo, Julian Bass

2022

Abstract

Web-based business applications commonly experience user request spikes called flash crowds. Flash crowds in web applications might result in resource failure and/or performance degradation. To alleviate these challenges, this class of applications would benefit from a targeted load balancer and deployment architecture of a multi-cloud environment. We propose a decentralised system that effectively distributes the workload of three-tier web-based business applications using geographical dynamic load balancing to minimise performance degradation and improve response time. Our approach improves a dynamic load distribution algorithm that utilises five carefully selected server metrics to determine the capacity of a server before distributing requests. Our first experiments compared our algorithm with multi-cloud benchmarks. Secondly, we experimentally evaluated our solution on a multi-cloud test-bed that comprises one private cloud, and two public clouds. Our experimental evaluation imitated flash crowds by sending varying requests using a standard exponential benchmark. It simulated resource failure by shutting down virtual machines in some of our chosen data centres. Then, we carefully measured response times of these various scenarios. Our experimental results showed that our solution improved application performance by 6.7% during resource failure periods, 4.08% and 20.05% during flash crowd situations when compared to Admission Control and Request Queuing benchmarks.

Paper Citation

in Harvard Style

Adewojo A. and Bass J. (2022). Multi-cloud Load Distribution for Three-tier Applications. In Proceedings of the 12th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-758-570-8, pages 296-304. DOI: 10.5220/0011092100003200

in Bibtex Style

@conference{closer22,
author={Adekunbi Adewojo and Julian Bass},
title={Multi-cloud Load Distribution for Three-tier Applications},
booktitle={Proceedings of the 12th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2022},
pages={296-304},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011092100003200},
isbn={978-989-758-570-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - Multi-cloud Load Distribution for Three-tier Applications
SN - 978-989-758-570-8
AU - Adewojo A.
AU - Bass J.
PY - 2022
SP - 296
EP - 304
DO - 10.5220/0011092100003200